literature review on nanofluids

A Review on Nanofluids: Properties and Applications

• January 2017
• International Journal Of Advance Research And Innovative Ideas In Education 3(3):3185-3209
• 3(3):3185-3209

• Sai Rajeswari Institute of Technology
• This person is not on ResearchGate, or hasn't claimed this research yet.

• Chandigarh University

Abstract and Figures

Discover the world's research

• 25+ million members
• 160+ million publication pages
• 2.3+ billion citations

• Constantinos S. Psomopoulos
• Prajwal Thorat
• Sudarshan Sanap
• Shashank Gawade
• Sateesh Patil

• Taseer Muhammad
• Durga Bhavani J
• Tami Selvi Gopal

• Nirmala Grace Andrews
• IND LUBR TRIBOL
• Salloom Mu'taz Altarawneh

• J THERM ANAL CALORIM
• Morteza Poushand
• Seyed Aboutaleb Mousavi Parsa
• Shiva Joohari
• Mehdi Faramarzi

• Ali Can Yilmaz
• Ahmet Cosgun

• Ghanshyam Das Agrawal

• N. Nakayama-Ratchford
• I.M. Krieger
• Y.J. Dougherty
• R.L. Gandhi
• S.U.S. Choi
• Ian C. Nelson

• Rengasamy Ponnappan

• Ravi Prasher

• Recruit researchers
• Join for free
• Login Email Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google Welcome back! Please log in. Email · Hint Tip: Most researchers use their institutional email address as their ResearchGate login Password Forgot password? Keep me logged in Log in or Continue with Google No account? Sign up

• Architecture and Design
• Asian and Pacific Studies
• Business and Economics
• Classical and Ancient Near Eastern Studies
• Computer Sciences
• Cultural Studies
• Engineering
• General Interest
• Geosciences
• Industrial Chemistry
• Islamic and Middle Eastern Studies
• Jewish Studies
• Library and Information Science, Book Studies
• Life Sciences
• Linguistics and Semiotics
• Literary Studies
• Materials Sciences
• Mathematics
• Social Sciences
• Sports and Recreation
• Theology and Religion
• Publish your article
• The role of authors
• Promoting your article
• Abstracting & indexing
• Publishing Ethics
• Why publish with De Gruyter
• How to publish with De Gruyter
• Our book series
• Our subject areas
• Your digital product at De Gruyter
• Contribute to our reference works
• Product information
• Tools & resources
• Product Information
• Promotional Materials
• Orders and Inquiries
• FAQ for Library Suppliers and Book Sellers
• Repository Policy
• Free access policy
• Open Access agreements
• Database portals
• For Authors
• Customer service
• People + Culture
• Journal Management
• How to join us
• Working at De Gruyter
• Mission & Vision
• De Gruyter Foundation
• De Gruyter Ebound
• Our Responsibility
• Partner publishers

Your purchase has been completed. Your documents are now available to view.

A comprehensive review of nanofluids with fractional derivatives: Modeling and application

Nanofluids have been widely used as a class of promising working fluids with excellent heat transfer properties. However, the theoretical research on the thermal enhancement mechanism of nanofluids is still in the preliminary stage. Fractional constitutive models provide a new powerful tool to investigate the superior mechanical and thermal properties of nanofluids owing to their advantages in depicting the memory and genetic properties of the system. Fractional nanofluid models have become one of the hot research topics in recent years as better control of flow behavior and heat transfer can be achieved by considering fractional derivatives. The existing studies have indicated that the results obtained by the fractional-order nanofluid model are more consistent with the experimental results than traditional integer-order models. The purpose of this review is to identify the advantages and applications of fractional nanofluid models. First, various definitions of fractional derivatives and correlations of flux utilized in nanofluid modeling are presented. Then, the recent researches on nanofluids with fractional derivatives are sorted and analyzed. The impacts of fractional parameters on flow behaviors and heat transfer enhancement are also highlighted according to the Buongiorno model as well as the Tiwari and Das nanofluid model with fractional operators. Finally, applications of fractional nanofluids in many emerging fields such as solar energy, seawater desalination, cancer therapy, and microfluidic devices are addressed in detail.

1 Introduction

Nanofluids introduced by Choi [ 1 ] have better heat transfer capability than conventional fluids. The anomalous increment of thermal conductivity of nanofluids provides an opportunity to upgrade traditional thermal technology and presents a theoretical challenge to explain their heat transport mechanisms. The specific thermal conductivity of nanofluids makes them attractive as new working fluids in many fields, including solar thermal engineering, cancer treatment, cooling technology, nuclear reactors, and the petroleum industry [ 2 , 3 , 4 ].

In recent years, the research of nanofluids has become one of the research focuses, as shown in Figure 1 . By considering a nanoparticle-fluid relative velocity, Buongiorno [ 5 ] proposed a nonhomogeneous nanofluid model incorporating the effects of Brownian diffusion and thermophoresis. Tiwari and Das [ 6 ] developed a model to analyze behaviors of nanofluids in terms of the nanoparticle volume fraction. It was assumed that the dispersion of nanoparticles in the base fluid is homogeneous. Nanofluid is treated as a dilute mixture of two phases in the Buongiorno model, while it is regarded as a single-phase flow in the Tiwari and Das model. By using these two classical models, nanofluids under various physical conditions have been investigated [ 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 ].

Number of papers on nanofluids published reports by Web of Science.

The current research mainly adopts integer-order partial differential equation methods, which would not be able to deal with the complex behavior and the memory effect of physical flows. The available literature shows that the nonlocal properties make fractional-order differential operators suitable for describing the global correlation of complex dynamic systems, phenomena, and structures [ 15 , 16 , 17 , 18 , 19 ]. Fractional calculus has been employed to solve fluid flow problems in various applications [ 20 , 21 , 22 ]. In addition, the distribution of nano sized nanoparticles in nanofluids exhibits fractal characteristics [ 23 , 24 , 25 , 26 , 27 ]. Some latest researches [ 28 , 29 ] indicate that the results of fractional-order nanofluid models are significantly more consistent with the experimental data compared with the ones obtained from the integer-order nanofluid models, which makes the research on fractional nanofluids become a new hotspot ( Figure 2 ).

Number of papers on fractional nanofluids published reports by Web of Science.

Recent works on fractional nanofluid models are critically reviewed to gain a better understanding of many key parameters affecting the anomalous heat and nanoparticle diffusion in heat and flow control problems. Section 2 outlines various concepts of fractional derivatives applied in nanofluid models. Section 3 is divided into three subsections. Sections 3.1 and 3.2 the studies on fractional models and physical interpretations of conventional nanofluids, Section 3.3 reviews the works on hybrid nanofluids. A wide range of applications concerning fractional nanofluid models is offered in Section 4. Section 5 draws some conclusions.

2 Various definitions of fractional derivatives

Recently, some new definitions have been proposed considering the nonlocal and nonsingular kernel properties with a good memory effect. This section presents some classical and popular definitions of fractional derivatives applied in describing the physical properties of nanofluids.

2.1 Riemann–Liouville (R–L) derivative

The left-hand and right-hand R–L fractional derivatives with order α ( 0 ≤ α < 1 ) on a finite domain [ a , b ] are given by [ 30 ]

respectively. Here, Γ ( ⋅ ) is the Gamma function.

2.2 Caputo derivative

The Caputo derivative is ideal for solving fractional differential equations with initial conditions, which is defined as follows [ 30 ]:

2.3 Grünwald–Letnikov (G–L) derivative

The G–L derivative is a discrete approximation based on the lattice model with extended-range particle interactions. It can be written as follows [ 31 ]:

where α m = α ( α − 1 ) ( α − 2 ) … ( α − m + 1 ) m ! .

2.4 Caputo–Fabrizio (C–F) derivative

The C–F derivative has an extensive application for solving fluid flow problems without singularity [ 32 ]. It is defined as follows:

where 0 < α < 1 , and N ( α ) is a standardization function that N ( 0 ) = N ( 1 ) = 1 .

2.5 Atangana–Baleanu (A–B) derivative

The A–B derivative has no singularity [ 33 ], which is defined by the generalized Mittag–Leffler function as follows:

where 0 < α < 1 and E α ( − t α ) = ∑ k = 0 ∞ ( − t ) α k Γ ( α k + 1 ) is the Mettag–Leffler function.

2.6 Prabhakar derivative

Prabhakar function plays an irreplaceable role in understanding the divergent dielectric properties of disordered materials and heterogeneous structures. Prabhakar derivative is defined as follows [ 34 ]:

where E α , β γ ( z ) = ∑ n = 0 ∞ Γ ( γ + n ) z n n ! Γ ( γ ) Γ ( α n + β ) , α , β , γ , z ∈ C , and ℜ ( α ) > 0 is the three-parameter Mittag–Leffler function.

2.7 Conformable derivative

The conformable fractional derivative is given by the following form [ 35 ]:

where α refers to the order of the fractional derivative. It is shown that this definition is in accordance with the classical definition of polynomial and first-order derivatives for the cases 0 ≤ α < 1 and α = 1 , respectively.

2.8 Constant-proportional Caputo derivative

In 2020, Baleanu et al . [ 36 ] reported that the constant-proportional Caputo fractional derivative, which is a combination of R–L and Caputo fractional derivatives, is defined as follows:

where α is the order.

The fractional-order derivatives of various definitions provide more tools for describing the physical phenomena and heat transfer characteristics of nanofluids and also make it possible for the fractional-order models to go deep into new research fields.

3 Fractional models

It is worth noting that the study of fractional models for nanofluids is still in its infancy due to the complexity of fractional operators. To explain the dramatic augmentation of heat transfer efficiency for nanofluids, increasing attention has been focused on nanofluid modeling by using the fractional derivative. The Buongiorno nanofluid model as well as the Tiwari and Das nanofluid model are two highly cited models for studying the flow and thermal properties of mono and hybrid nanofluids [ 2 ]. This section is a comprehensive literature review on investigations by modifying these two models with fractional derivatives and assumptions for different kinds of nanofluids.

3.1 The fractional Buongiorno model for nanofluids

First, the fractional operators were employed to establish the constitutive relationships of viscoelastic fluids [ 37 , 38 , 39 , 40 ]. The fractional flow configuration of a rate-type anomalous nanofluid was studied in ref. [ 41 ]. The Caputo fractional derivative was utilized to the velocity field, while the energy and concentration equations were still partial differential equations of integer order described by the Buongiorno model. The finite element method was applied to approximate the velocity, temperature, and concentration fields between two parallel plates. The study of fractional flows of nanofluids has attracted more and more attention due to the development of numerical computation methods for highly nonlinear terms and coupled nonlinear equations. The fractional-order thin film nanofluid flow was considered over an inclined rotating plane [ 42 ], where the Caputo derivative was applied to transform the first-order differential equations into a system of fractional differential equations by the Adams-type predictor–corrector method.

Recent researches show that the thermal conductivity of nanofluids cannot be predicted by conventional laws as the suspended particles dramatically augment the thermal conductivity of nanofluids [ 43 ]. Shen et al . [ 44 ] proposed a renovated Buongiorno model to study Sisko’s nanofluids. The fractional Cattaneo heat conduction in this article [ 44 ] was proposed as follows:

where τ 0 denotes relaxation time, and β is the order with β ! = Γ ( 1 + β ) . By using this heat flux, the corresponding energy equation was given as [ 44 ]

By solving the energy equation numerically, it is shown that the fractional model with Caputo time derivative in Sisko’s nanofluids has a short memory of previous states. It is therefore easy to conclude that the renovated fractional Buongiorno model could be regarded as a candidate model to explore the anomalous heat transport of non-Newtonian nanofluids.

In addition to the time-fractional derivative, the space-fractional derivative has also been used to simulate the nonlocal property of the flow, which means the state depending on the whole region. Whereafter, Zhang et al . [ 45 ] provided a new heat conduction as follows:

where k denotes the thermal conductivity, σ is introduced to maintain the dimensional balance of the constitutive equation, ∂ β / ∂ t β is the Caputo fractional derivative of order β , and for T = T ( t , x , y ) , the operator ∇ γ T is defined as follows [ 45 ]:

with δ ( 0 ≤ δ ≤ 1 ) being the weight coefficient. The symbols ∂ γ T ∂ x γ and ∂ γ T ∂ ( − x ) γ are the left and right R–L fractional derivatives of order γ ( n − 1 ≤ γ < n ) . By incorporating this heat conduction, the energy equation could be written as follows [ 45 ]:

By solving this model, it was found that the memory of the heat conduction process could be indicated by the intersection points of concentration profiles, and the heat conduction loss is less. Therefore, this model lays a foundation for further research on the application of fractional calculus in the field of viscoelastic nanofluids.

Anwar [ 46 ] analyzed convective phenomena in a nanofluid flow and proposed a new relationship between the energy flux and the diffusion mass flu as follows:

where τ 1 and α ( 0 ≤ α < 1 ) represent the relaxation time and the order, respectively. On the other hand, he also applied the operator 1 + τ 1 α Γ ( 1 + α ) ∂ α ∂ t α to the concentration equation given in the Buongiorno model, which is helpful to understand the hereditary and memory characteristics of viscoelastic nanofluids.

In addition, some new definitions of fractional derivatives have been proposed and applied to the study of nanofluids in recent years. Ahmed and Arafa [ 47 ] considered a non-Newtonian magnetohydrodynamic nanofluid flow and entropy generation with a Caputo derivative or a conformable derivative in the governing equations over a vertical plate. The results indicated that the Nusselt number is reduced as the order of the fractional derivative approaches one. In another work, Ahmed [ 48 ] investigated a natural convection nanofluid flow in wavy walls by using the time and space conformable fractional derivative in the governing equations of the Buongiorno mathematical model. The findings showed that the rate of the nanofluid flow increases as the order of the fractional derivatives decreases. Arafa et al . [ 49 ] studied an unsteady magnetohydrodynamic (MHD) nanofluid due to microorganisms using the A–B derivative, which gives a good approximation compared with the Caputo derivative.

It is necessary to note that investigation of the entropy generation optimization for nanofluid models is meaningful due to the wide applications in different systems such as natural convection, evaporative cooling, solar thermal, air separators, microchannel, and so on [ 50 ]. So far, little research has been done on entropy generation analysis of nanofluids with fractional derivatives so far. It is believed that this will be a new research hot topic in the near future.

3.2 The fractional Tiwari–Das model for nanofluids

Extending the Tiwari and Das model, the anomalous transport of particles in nanofluids has been described using fractional calculus [ 51 , 52 ]. The thermophysical properties of base fluids and nanoparticles are listed in Table 1 .

Thermophysical properties of the base fluid and nanoparticles at 20°C [ 80 , 86 , 101 , 125 , 134 ]

3.2.1 Nanofluid models with conventional fractional derivatives

To the best of our knowledge, Pan et al . [ 53 ] proposed an alternative explanation for the anomalous heat transport of nanofluids by using space fractional derivative first. They concluded that the thermal conductivity of the nanofluid is affected by the motion of non-Newtonian fluids and the nonuniform spatial distribution of nanoparticles. In response, the space-fractional derivative was introduced to model the energy equation given by [ 53 ]

where the parameters are given in Table 2 with the subscripts n f , f , and s corresponding to nanofluid, base fluid, and nanoparticle, respectively. The results revealed that the space-fractional temperature equation could be a potential candidate to explain the enhancement of thermal conductivity. Subsequently, they extended the space-fractional thermal transport equation by using the Caputo derivative to describe convective heat transfer in the boundary-layer flow [ 54 ] and steady mixed convection of nanofluids [ 55 ].

Physical properties of nanofluids [ 56 ]

Cao et al . [ 57 ] studied a fractional Maxwell nanofluid over a moving plate and formulated the governing equations with Caputo’s definition as follows:

which were solved numerically by the finite difference method. Their results showed that the order of the time fractional derivative and relaxation time have a noticeable impact on the characteristics of nanofluid flow and heat transfer. Via replacing the time derivative of an integer order with that of fractional order, various nanofluids including Poiselliue/Couette, Maxwell, Oldroyd-B, Jeffrey, and Brinkman have been investigated under different physical conditions [ 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 ]. It has been found that the heat transfer rate of fractional nanofluids is better than that of ordinary nanofluids. Furthermore, the influence of nanoparticle shapes on the nanofluid has also been investigated under different physical conditions [ 67 , 68 , 69 , 70 ]. The results indicated that the heat transfer is the strongest for containing spherical nanoparticles, which agrees the physical fact.

Ahmed et al . [ 71 ] studied the natural convection heat transfer of nanofluid through a rectangular vertical channel. A thermal process with power-law weakly memory was considered by Povstenko [ 72 ], namely,

Based on this generalized Fourier law, the convection flow of nanofluids with various nanoparticles between two vertical parallel walls has been investigated [ 73 , 74 , 75 , 76 ]. It indicated that the nanofluid models with fractional generalized Fourier’s law show the memory effect, which could not be demonstrated by the integer-order models.

Asjad et al . [ 77 ] considered an MHD viscous nanofluid flow with fractional generalized Newton’s law, fractional generalized Fourier’s law, and Fick’s law with Caputo derivative. The expression for the heat flux q was formulated as the following fractional form:

By using this fractional heat flux, mixed convection magnetohydrodynamics nanofluids [ 78 ], viscoelastic nanofluid flow with suspended carbon nanotubes [ 79 ], and MHD Maxwell’s nanofluids with SWCNT and MWCNT [ 80 ] have been discussed to achieve more control on heat transfer.

In addition, some steady nanofluid models were studied by applying the Caputo derivative to the ordinary differential equation system directly [ 81 , 82 ]. The G–L derivative was also adopted to discuss double rotations between an inner wavy shape and a hexagonal-shaped cavity [ 83 ]. The primary outcomes of this work indicated that the double rotation process mainly depends on the time-fractional derivative. To gain a better insight into the memory behavior of nanofluid, the variable-order fractional derivative was implemented in the governing equations to study unsteady natural-convection Jeffrey’s nanofluids over an oscillating plate [ 84 ]. Up to now, there have been few studies of variable-order fractional nanofluid models. However, the variable-order fractional calculus is ideal for describing the memory and hereditary properties because that the memory and nonlocality of the system may change with time, space, or other conditions [ 22 ]. Therefore, it is notable to mention that further investigations should be dedicated to variable-order fractional nanofluid models.

3.2.2 Nanofluid models with new fractional derivatives

Taking advantage of the C–F derivative, exact analytical solutions were established for the dimensionless temperature and velocity fields of nanofluids over a moving vertical plate [ 85 ]. The researchers considered different nanoparticles concluding copper, copper oxide, silver, aluminum, and titanium oxide. Results suggested that the heat transfer enhancement of nanofluids wit Cu was the strongest, while the enhancement effect of nanofluids containing TiO 2 nanoparticles was the weakest. Moreover, the heat transfer is better with spherical nanoparticles than those containing cylindrical nanoparticles, which is in good agreement with experimental results.

Ali et al . [ 86 ] considered generalized Couette’s flow of coupled stress nanofluid via the C–F derivative. They revealed that the rate of heat transfer can be increased to 12.38% by adding MoS 2 in regular engine oil. The C–F derivative was also used for thermal analysis in a coaxial cylinder of Oldroyd-B nanofluids [ 87 ]. Furthermore, a comparative study between the Caputo and C–F fractional models was presented in the study by Aleem et al . [ 88 ] for an MHD nanofluid flow, which showed that the C–F model declines faster than the Caputo model and hence is more suitable to exhibit the flowing memory.

The kernel of the A–B derivative is based on the generalized Mittag–Leffler function without singularity and locality, which gives a better description of memory in different scaled structures. The A–B derivative was applied to study molybdenum disulfide nanofluids with magnetic field and a porous medium [ 89 ]. This newly introduced fractional derivative was also applied to study the generalized Brinkman-type nanofluids [ 90 ] and convective flow of nanofluids [ 91 ]. Many works have followed to investigate nanofluids with this fractional-order derivative [ 92 , 90 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 ]. To have better insight into the various rheological parameters, a comparison of A–B and C–F fractional operators was also performed for temperature and velocity fields of nanofluids with different nanoparticles [ 103 , 104 , 105 , 106 , 107 , 108 , 109 , 110 ].

The governing equations of nanofluids have also been modeled using the Prabhakar derivative and the conformable derivative to describe the generalized memory effect recently. For Prabhakar-like thermal transport, carbon nanotube nanofluids [ 111 , 112 ] and Casson nanofluids [ 113 ] have been considered. It was found that fractional parameters were meaningful in experimental data fitting in some heating and cooling phenomena. In addition, the conformable fractional derivative was used to study a power-law nanofluid flow [ 114 ]. The main outcomes of this study revealed that the increase in the fractional order augments the average Nusselt number regardless of time. From the aforementioned developments, it could be concluded that the fractional solution is more effective than the classical solution.

Because of the advantages these new definitions, it is clear that nanofluid modeling with modeling with new derivatives develops into the growth period. However, some in-depth problems gradually appear. Optimization on the parameters, comparison with experimental data, and analysis of physical phenomena have become their further development shackles, which are theoretical and practical problems that need addressing.

3.3 Fractional models for hybrid nanofluids

Hybrid nanofluids are formed by suspending two or more kinds of nanoparticles in a base fluid [ 115 ]. It was found that the thermal characteristics of hybrid nanofluids are better than the base fluid and mono nanofluids [ 116 ]. This field has attracted experimental studies [ 117 , 118 ] and theoretical researches [ 119 , 120 , 121 , 122 , 123 , 124 , 125 , 126 , 127 , 128 , 129 , 130 ]. The general relations of thermophysical properties of hybrid nanofluids are given in Table 3 with the subscripts h n f , f , s 1 , and s 2 corresponding to hybrid nanofluid, base fluid, and two different nanoparticles, respectively.

Physical properties of hybrid nanofluids [ 131 ]

To better capture the flow patterns and thermal behaviors of hybrid nanofluids, different fractional derivatives have been employed to model the governing equations. By using the Caputo derivative in constitutive relations, Casson hybrid nanofluids [ 132 , 133 ], hybrid nanofluids with aluminum and copper nanoparticles [ 134 , 135 ], and hybrid Maxwell’s nanofluids [ 136 ] have been investigated. Their observations demonstrated that water-based hybrid nanofluids have higher temperature and velocity than engine oil-based hybrid nanofluids, and an increase in the order of the fractional derivative leads to the decrease in both the local and average Nusselt numbers.

The constant-proportional Caputo derivative has been applied to study aluminum and copper hybrid nanofluids due to pressure gradient [ 137 ], Brinkman-type hybrid nanofluids holding titanium dioxide and silver nanoparticles [ 138 ], as well as MHD free convection flow of hybrid nanofluids with hybridized copper and aluminum oxide nanoparticles [ 139 ].

C–F and A–B fractional models were also built for hybrid nanofluids. Gohar et al . [ 140 ] considered hybrid nanofluids with Al 2 O 3 and MWCNT nanoparticles using the C–F derivative. Their results showed that the binding strength of cement slurry improves through a sizable increase of suspending hybrid nanoparticles. The C–F fractional derivative has also been applied to investigate a convection flow of water-based hybrid nanofluids with Cu and Al 2 O 3 [ 141 , 142 ] and the MHD hybrid nanofluids with hybridized silver and titanium dioxide in a microchannel [ 143 ]. To further analyze the thermal and flow behaviors of hybrid nanofluids, C–F and A–B fractional models were formulated to explain flow patterns and thermal behaviors of sodium alginate-based hybrid nanofluids [ 144 ]. The analysis of MHD hybrid nanofluids comprising of MoS 2 and Fe 3 O 4 nanoparticles employing A–B derivative was also presented by Anwar et al . [ 145 ]. The observed results implied that the fractional models are more effective for enhancing the heat transfer rate and limiting the shear stress.

In conclusion, various fractional operators have been applied to study the flow and heat mass transfer of mono and hybrid nanofluids. It is necessary to seek the most suitable fractional operators to model the heat and mass transfer properties of nanofluids. To better simulate complex fluid flow and heat and mass transfer of nanofluid, construction of efficient numerical methods and parameter estimation based on experimental data are suggested for future works. It is worth noting that there are few high precision numerical solutions for nonlinear governing equations of fractional nanofluids. So it is necessary to study high-precision numerical methods and their stability and convergence of a general form of nonlinear governing equations for nanofluid models.

Applications of nanofluids.

4 Applications of fractional nanofluids

The increase in thermal conductivity and heat transfer coefficient enables nanofluids attractive as new working fluids or coolants in many emerging applications such as radiators, heat exchangers, aircraft engine cooling, electronic cooling, space shuttle thermal protection, and aircraft environmental control systems [ 146 , 3 ]. Due to memory and the nonlocality property in many complex systems, fractional nanofluids have also shown great potential for applications in some important fields such as solar energy, seawater desalination, human health, and microfluidic devices ( Figure 3 ).

4.1 Solar energy

Solar energy has proved to be free renewable energy with the least effect on the environment. The latest researches have indicated that nanofluids can enhance the collection and heat transfer rate of solar energy [ 147 , 148 , 149 ].

Nanofluid is regarded as an alternative source to produce solar energy in thermal engineering and solar installations. In an application to solar energy, Aman et al . [ 150 ] used the Caputo time fractional derivative to MHD Poiseuille flow of nanofluids with graphene nanoparticles, which showed that fractional nanofluids have a higher rate of heat transfer and Sherwood’s number than ordinary nanofluids. Abro et al . [ 151 ] presented a rotating Jeffrey nanofluid model via the C–F fractional operator and considered single, and multi-walled carbon nanotubes. Their results indicated that the incoming sunlight can be absorbed more effectively via introducing a fractional-order operator.

Sheikh et al . [ 152 ] carried out a comparative analysis of C–F and A–B fractional models on the application of nanofluids to enhance the performance of solar collectors. In another work, they provided the mathematical formulation for water-based nanofluids with CeO 2 and Al 2 O 3 to increase the heat transfer rate of solar equipment [ 153 ]. Considering the influence of the transverse magnetic field, Aamina et al . [ 154 ] developed a nanofluid model to predict the heat transport properties of solar collector in a rotating frame. Currently, more and more researchers have paid attention to the application of fractional nanofluid models on solar energy. It is believed that breakthroughs will be made in this area in the near future.

4.2 Water cleaning and desalination

The shortage of fresh water is recognized as one of the global problems to be solved urgently. Many desalination process systems have been developed recently. One of these systems that has attracted much attention is the solar still as it realizes seawater desalination through solar energy [ 155 , 156 , 157 ]. The implementation of nanofluids provides a promising way to improve the productivity of the solar still. It has been found that the solar still output is greatly affected by nanoparticles such as copper oxide, graphene, and titanium oxide [ 158 , 159 , 160 ].

Most works related to solar still systems were based on ordinary differential equations, which led to a high error between the numerical and actual values in simulation systems. Until very recently, the fractional derivative has been introduced into modeling solar desalination systems that integrate directly with a photovoltaic panel. El-Gazar Hamdy Hassan et al . [ 161 ] studied hybrid nanofluids and saline water preheating using C–F and R–L fractional derivatives. Their results revealed that the best agreement with experimental data was achieved by the R–L derivative with an error of 3.59%, while the error produced by employing the classical derivative reached 18.9%. Utilizing the R–L derivative, they also simulated the thermal performance of solar still on the desalination system [ 29 ]. The theoretical results showed an agreement between the proposed fractional model and the experimental data with an error of 1.486% in summer and 3.243% in winter compared to an error of 24.1 and 20.08% in the case of applying the integer-order derivative. Researchers have begun to notice that this method is very efficient in dealing with desalination problems.

4.3 Human health

For the majority of patients, cancer is fatal. Recent investigations indicate that gold nanoparticles can penetrate widely throughout the body. More importantly, gold nanoparticles are capable of producing heat for tumor-selective photothermal therapy and cancer treatment [ 162 , 163 ].

In 2018, Mekheimer et al . [ 164 ] studied the blood flow containing gold nanoparticles in a gap between two coaxial tubes. The results indicated that the gold nanoparticles are effective for drug delivery systems as they can increase the temperature distribution to destroy cancer cells. Recently, viscoelastic models with fractional-order different equations were chosen to describe blood movements [ 165 ]. Currently, there are still very few studies on the application of fractional nanofluid models to cancer treatment for human health. We hope fractional calculus and nanofluid can play a vital role in human health, which is designed to handle some challenging issues in this application.

4.4 Microfluidic devices

Nanofluids in microfluidic systems are considered to have enormous potential because of their superior heat transfer properties [ 166 ]. To improve the thermal and electric conductivity of microfluidic systems, electrified nanofluid flow with suspended carbon nanotubes over a stretching sheet was considered by Anwar et al . [ 79 ]. The mathematical formulation of the flow problem was modeled with Caputo fractional derivatives to achieve better control of flow behavior and heat transfer.

In various microfluidic devices, currently, the electroosmotic flow is one of the widely used microfluidic driving methods because of the ability to create continuous pulseless flows and eliminate moving parts [ 167 , 168 , 169 ]. To offer new insights for the nonlinear issues, the fractional Cattaneo model is applied to study the unsteady electroosmotic flow of second-grade hybrid nanofluid through a vertical annulus and microchannel [ 170 , 171 ]. The results showed that the fractional-order parameter provides a crucial memory effect on the velocity and temperature fields. The superiority of fractional model of electroosmotic flow of nanofluids for microfluidic systems has yet to be explored.

5 Conclusion

The current work provides an overview of recent researches and developments on nanofluid models with fractional derivatives. The enhanced thermal conductivity of mono and hybrid nanofluids leads to significant practical and potential applications. The anomalous thermal behavior of these fluids could not be explained by existing theories. On the one hand, this provides a great opportunity for researchers because the new properties encourage studies of new models of heat transfer and efforts to develop a comprehensive theory. On the other hand, the challenge is greater than ever due to the difficulty of matching the theory with experiments. In recent years, fractional calculus has been introduced to study the anomalous thermal behavior of nanofluids. Since fractional derivatives provide greater flexibility for the heat transfer control, recent investigations have witnessed increasing interest and developments of fractional nanofluids models.

During the last few years, many definitions of fractional derivatives have been introduced to describe the physical phenomena and constitutive equations of materials. It has been found that the fractional derivatives may have good memory effect. However, while providing more tools for research on nanofluids, there is also a challenge in choosing which one is more appropriate with experimental data. Currently, in addition to the research work of high-precision numerical algorithm, it is necessary to carry out experimental analysis on heat and mass transfer characteristics of non-Newtonian nanofluids, study the internal laws of the non-Newtonian nanoparticle flow, and explore the physical significance of qualitative analysis of fractional-order parameters through parameter inversion. Practical application of fractional nanofluid models in solar energy, desalination, human health, microfluidic devices, and other emerging fields is also worthy of further exploration and research.

Funding information : This research was supported by the Natural Science Foundation of Fujian Province (Grant no. 2019J01646).

Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

Conflict of interest: The authors state no conflict of interest.

[1] Choi SUS. Enhancing thermal conductivity of fluids with nanoparticles. Asme Fed. 1995;231:99. Search in Google Scholar

[2] Kasaeian A, Azarian RD, Mahian O, Kolsi L, Chamkha AJ, Wongwises S, et al. Nanofluid flow andheat transfer in porous media: A review of the latest developments. Int J Heat Mass Transfer. 2017;107:778–91. 10.1016/j.ijheatmasstransfer.2016.11.074 Search in Google Scholar

[3] Sajid MU, Ali HM. Recent advances in application of nanofluids in heat transfer devices: a critical review. Renewable Sustainable Energy Rev. 2019;103:556–92. 10.1016/j.rser.2018.12.057 Search in Google Scholar

[4] Gupta M, Singh V, Kumar R, Said Z. A review on thermophysical properties of nanofluids and heat transfer applications. Renewable Sustainable Energy Rev. 2017;74:638–70. 10.1016/j.rser.2017.02.073 Search in Google Scholar

[5] Buongiorno J. Convective transport in nanofluids. J Heat Transfer. 2006;128:240–50. 10.1115/1.2150834 Search in Google Scholar

[6] Tiwari RK, Das MK. Heat transfer augmentation in a two-sided lid-driven differentially heated square cavity utilizing nanofluids. Int J Heat Mass Transf. 2007;50:2002–18. 10.1016/j.ijheatmasstransfer.2006.09.034 Search in Google Scholar

[7] Mahdy A, Ahmed SE. Laminar free convection over a vertical wavy surface embedded in a porous medium saturated with a nanofluid. Trans Porous Med. 2012;91:423–35. 10.1007/s11242-011-9852-4 Search in Google Scholar

[8] Nield DA, Kuznetsov AV. Thermal instability in a porous medium layer saturated by a nanofluid: a revised model. Int J Heat Mass Transf. 2014;68:211–4. 10.1016/j.ijheatmasstransfer.2013.09.026 Search in Google Scholar

[9] Sheremet MA, Dinarvand S, Pop I. Effect of thermal stratification on free convection in a square porous cavity filled with a nanofluid using Tiwari and Das nanofluid model. Phys E. 2015;69:332–41. 10.1016/j.physe.2015.02.005 Search in Google Scholar

[10] Sheremet MA, Pop I, Bachok N. Effect of thermal dispersion on transient natural convection in a wavy-walled porous cavity filled with a nanofluid: Tiwari and Das nanofluid model. Int J Heat Mass Transf. 2016;92:1053–60. 10.1016/j.ijheatmasstransfer.2015.09.071 Search in Google Scholar

[11] Ramzan M, Chung JD, Ullah N. Radiative magnetohydrodynamic nanofluid flow due to gyrotactic microorganisms with chemical reaction and non-linear thermal radiation. Int J Mech Sci. 2017;130:1–40. 10.1016/j.ijmecsci.2017.06.009 Search in Google Scholar

[12] Lu DC, Farooq U, Hayat T, Rashidie MM, Ramzan M. Computational analysis of three layer fluid model including a nanomaterial layer. Int J Heat Mass Transf. 2018;122:222–8. 10.1016/j.ijheatmasstransfer.2018.01.080 Search in Google Scholar

[13] Selimefendigil F, Chamkha AJ. Magneto hydrodynamics mixed convection in a power law nanofluid-filled triangular cavity with an opening using Tiwari and Das nanofluid model. J Therm Anal Calorim. 2019;135:419–36. 10.1007/s10973-018-7037-x Search in Google Scholar

[14] Reddy MG, Kumar KG. Cattaneo-Christov heat flux feature on carbon nanotubes filled with micropolar liquid over a melting surface: a stream line study. Int Commun Heat Mass Transf. 2021;122:105142. 10.1016/j.icheatmasstransfer.2021.105142 Search in Google Scholar

[15] Liu F, Zhuang P, Liu Q. Numerical methods of fractional partial differential equations and applications. China: Science Press; 2015. Search in Google Scholar

[16] Liu F, Zhuang P, Turner I, Anh V, Burrage K. A semi-alternating direction method for a 2-D fractional FitzHugh-Nagumo monodomain model on an approximate irregular domain. J Comput Phys. 2015;293:252–63. 10.1016/j.jcp.2014.06.001 Search in Google Scholar

[17] Liu F, Feng L, Anh V, Li J. Unstructured-mesh Galerkin finite element method for the two-dimensional multi-term time-space fractional Bloch-Torrey equations on irregular convex domains. Comput Math Appl. 2019;78:1637–50. 10.1016/j.camwa.2019.01.007 Search in Google Scholar

[18] Sun HG, Zhang Y, Baleanu D, Chen W, Chen YQ. A new collection of real world applications of fractional calculus in science and engineering. Commun Nonlinear Sci Numer Simul. 2018;64:213–31. 10.1016/j.cnsns.2018.04.019 Search in Google Scholar

[19] Zhang H, Liu F, Chen S, Anh V, Chen J. Fast numerical simulation of a new time-space fractional option pricing model governing European call option. Appl Math Comput. 2018;339:186–98. 10.1016/j.amc.2018.06.030 Search in Google Scholar

[20] Cai J, Hu X, Xiao B, Zhou Y, Wei W. Recent developments on fractal-based approaches to nanofluids and nanoparticle aggregation. Int J Heat Mass Transf. 2017;105:623–37. 10.1016/j.ijheatmasstransfer.2016.10.011 Search in Google Scholar

[21] Sulochana C, Ashwinkumar GP. Impact of Brownian moment and thermophoresis on magnetohydrodynamic flow of magnetic nanofluid past an elongated sheet in the presence of thermal diffusion. Multidiscip Model Mater Struct. 2018;14:744–55. 10.1108/MMMS-12-2017-0168 Search in Google Scholar

[22] Sun H, Chang A, Zhang Y, Chen W. A review on variable-order fractional differential equations: mathematical foundations, physical models, numerical methods and applications. Fract Calc Appl Anal. 2019;22:1 10.1515/fca-2019-0003 Search in Google Scholar

[23] Xu J, Yu B, Zou M, Xu P. A new model for heat conduction of nanofluids based on fractal distributions of nanoparticles. J Phys D Appl Phys. 2006;39:4486–90. 10.1088/0022-3727/39/20/028 Search in Google Scholar

[24] Xiao B, Yu B, Wang Z, Chen L. A fractal model for heat transfer of nanofluids by convection in a pool. Phys Lett A. 2009;373:4178–81. 10.1016/j.physleta.2009.09.020 Search in Google Scholar

[25] Gharagozloo PE, Goodson KE. Aggregate fractal dimensions and thermal conduction in nanofluids. J Appl Phys. 2010;108:074309. 10.1063/1.3481423 Search in Google Scholar

[26] Qi X. Prediction of heat transfer of nanofluid on criticalheat flux based on fractal geometry. Chin Phys B. 2013;22:014402. 10.1088/1674-1056/22/1/014402 Search in Google Scholar

[27] Wei W, Cai J, Hu X, Han Q, Liu S, Zhou Y. Fractal analysis of the effect of particle aggregation distribution on thermal conductivity of nanofluids. Phys Lett A. 2016;380:2953–6. 10.1016/j.physleta.2016.07.005 Search in Google Scholar

[28] El-Gazar EF, Hassan H, Rabia SI, Zahra WK. Study of the impact of using hybrid nanofluid and saline water preheating on the performance of both integrated solar still and photovoltaic panel using fractional modeling. Eur Phys J Plus. 2021;136:717. 10.1140/epjp/s13360-021-01654-y Search in Google Scholar

[29] El-Gazar EF, Zahra WK, Hassan H, Rabia SI. Fractional modeling for enhancing the thermal performance of conventional solar still using hybrid nanofluid: Energy and exergy analysis. Desalination. 2021;503:114847. 10.1016/j.desal.2020.114847 Search in Google Scholar

[30] Podlubny I. Fractional differential equations. New York: Academic Press; 1999. Search in Google Scholar

[31] Diethelm K. The analysis of fractional differential equations: an application oriented exposition using differential operators of Caputo type. Berlin: Springer Science and Business Media; 2010. 10.1007/978-3-642-14574-2 Search in Google Scholar

[32] Caputo M, Fabrizio M. A new definition of fractional derivative without singular kernel. Progr Fract Differ Appl. 2015;1:1–13. Search in Google Scholar

[33] Atangana A, Baleanu D. New fractional derivatives with nonlocal and non-singular kernel: theory and application to heat transfer model. Therm Sci. 2016;2:763. 10.2298/TSCI160111018A Search in Google Scholar

[34] Polito F, Tomovski Z. Some properties of Prabhakar-type fractional calculus operators. Fract Differ Calc. 2016;6:73–94. 10.7153/fdc-06-05 Search in Google Scholar

[35] Khalil R, AlHorani M, Yousef A, Sababheh M. A new definition of fractional derivative. J Comput Appl Math. 2014;264:65. 10.1016/j.cam.2014.01.002 Search in Google Scholar

[36] Baleanu D, Fernandez A, Akgul A. On a fractional operator combining proportional and classical diferintegrals. Mathematics. 2020;8:360. 10.3390/math8030360 Search in Google Scholar

[37] Koeller RC. Applications of fractional calculus to the theory of viscoelasticity. J Appl Mech. 1984;51:299–307. 10.1115/1.3167616 Search in Google Scholar

[38] Bagley RL, Torvik PJ. A theoretical basis for the application of fractional calculus to viscoelasticity. J Rheol. 1983;27:201–10. 10.1122/1.549724 Search in Google Scholar

[39] Liu Y, Zheng L, Zhang X. Unsteady MHD Couette flow of a generalized Oldroyd-B fluid with fractional derivative. Comput Math Appl. 2011;61:443–50. 10.1016/j.camwa.2010.11.021 Search in Google Scholar

[40] Bazhlekova E, Bazhlekov I. Unidirectional flows of fractional Jeffreys fluids: thermodynamic constraints and subordination. Comput Math Appl. 2017;73:1363–76. 10.1016/j.camwa.2016.12.009 Search in Google Scholar

[41] Anwar MS, Rasheed A. Simulations of a fractional rate type nanofluid flow with non-integer Caputo time derivatives. Comput Math Appl. 2017;74:2485–502. 10.1016/j.camwa.2017.07.041 Search in Google Scholar

[42] Gul T, Khan MA, Khan A, Shuaib M. Fractional-order three-dimensional thin-film nanofluid flow on an inclined rotating disk. Eur Phys J Plus. 2018;133:500. 10.1140/epjp/i2018-12315-4 Search in Google Scholar

[43] Xuan YM, Li Q. Heat transfer enhancement of nanofluids. Int J Heat Fluid Flow. 2000;21:58–64. 10.1016/S0142-727X(99)00067-3 Search in Google Scholar

[44] Shen M, Chen L, Zhang M, Liu F. A renovated Buongiornos model for unsteady Sisko nanofluid with fractional Cattaneo heat flux. Int J Heat Mass Transf. 2018;126:277–86. 10.1016/j.ijheatmasstransfer.2018.05.131 Search in Google Scholar

[45] Zhang M, Shen M, Liu F, Zhang H. A new time and spatial fractional heat conduction model for Maxwell nanofluid in porous medium. Comput Math Appl. 2019;78:1621–36. 10.1016/j.camwa.2019.01.006 Search in Google Scholar

[46] Anwar MS. Numerical study of transport phenomena in a nanofluid using fractional relaxation times in Buongiorno model. Phys Scr. 2020;95:035211. 10.1088/1402-4896/ab4ba9 Search in Google Scholar

[47] Ahmed SE, Arafa AM. Impacts of the fractional derivatives on unsteady magnetohydrodynamics radiative Casson nanofluid flow combined with Joule heating. Phys Scr. 2020;95:095206. 10.1088/1402-4896/abab37 Search in Google Scholar

[48] Ahmed SE. Effect of fractional derivatives on natural convection in a complex-wavy-wall surrounded enclosure filled with porous media using nanofluids. Z Angew Math Mech. 2020;100:201800323. 10.1002/zamm.201800323 Search in Google Scholar

[49] Arafa AAM, Rashed ZZ, Ahmed SE. Radiative MHD bioconvective nanofluid flow due to gyrotactic microorganisms using Atangana-Baleanu Caputo fractional derivative. Phys Scr. 2021;96:055211. 10.1088/1402-4896/abe82d Search in Google Scholar

[50] Mahian O, Kianifar A, Kleinstreuer C, Al-Nimr M, Pop I, Sahin AZ, et al. A review of entropy generation in nanofluid flow. Int J Heat Mass Transf. 2013;65:514–32. 10.1016/j.ijheatmasstransfer.2013.06.010 Search in Google Scholar

[51] Chen W, Zhang J, Zhang J. A variable-order time-fractional derivative model for chloride ions sub-diffusion in concrete structures. Fract Calc Appl Anal. 2013;16;76–92. 10.2478/s13540-013-0006-y Search in Google Scholar

[52] Sun H, Zhang Y, Chen W, Reeves DM. Use of a variable index fractional derivative model to capture transient dispersion in heterogeneous media. J Contam Hydrol. 2014;157:47–58. 10.1016/j.jconhyd.2013.11.002 Search in Google Scholar PubMed

[53] Pan M, Zheng L, Liu F, Zhang X. Modeling heat transport in nanofluids with stagnation point flow using fractional calculus. Appl Math Modell. 2016;40:8974–84. 10.1016/j.apm.2016.05.044 Search in Google Scholar

[54] Pan M, Zheng L, Liu F, Liu C, Chen X. A spatial-fractional thermal transport model for nanofluid in porous media. Appl Math Modell. 2018;53:622–34. 10.1016/j.apm.2017.08.026 Search in Google Scholar

[55] Pan M, Zheng L, Liu C, Liu F, Lin P, Chen G. A stochastic model for thermal transport of nanofluid in porous media: derivation and applications. Comput Math Appl. 2018;75:1226–36. 10.1016/j.camwa.2017.10.022 Search in Google Scholar

[56] Oztop HF, Abu-Nada E. Numerical study of natural convection in partially heated rectangular enclosures filled with nanofluids. Int J Heat Fluid Flow. 2008;29:1326–36. 10.1016/j.ijheatfluidflow.2008.04.009 Search in Google Scholar

[57] Cao Z, Zhao. J, Wang Z, Liu F, Zheng L. MHD flow and heat transfer of fractional Maxwell viscoelastic nanofluid over a moving plate. J Molecular Liquids. 2016;222:1121–7. 10.1016/j.molliq.2016.08.012 Search in Google Scholar

[58] Fetecau C, Vieru D, Azhar WA. Natural convection flow of fractional nanofluids over an isothermal vertical plate with thermal radiation. Appl Sci. 2017;7:247. 10.3390/app7030247 Search in Google Scholar

[59] Aman S, Khan I, Ismail Z, Salleh MZ. Applicataions of faactioanal derivatives to nanofluids: exact and numerical solutions. Math Model Nat Phenom. 2018;13:2. 10.1051/mmnp/2018013 Search in Google Scholar

[60] Shen M, Chen S, Liu F. Unsteady MHD flow and heat transfer of fractional Maxwell viscoelastic nanofluid with Cattaneo heat flux and different particle shapes. Chin J Phys. 2018;56:1199–211. 10.1016/j.cjph.2018.04.024 Search in Google Scholar

[61] Zhang Y, Jiang J, Bai Y. MHD flow and heat transfer analysis of fractional Oldroyd-B nanofluid between two coaxial cylinders. Comput Math Appl. 2019;78:3408–21. 10.1016/j.camwa.2019.05.013 Search in Google Scholar

[62] Roohi R, Heydari MH, Bavi O, Emdad H. Chebyshev polynomials for generalized Couette fow of fractional Jefrey nanofuid subjected to several thermochemical effects. Eng Comput. 2021;37:579–95. 10.1007/s00366-019-00843-9 Search in Google Scholar

[63] Hamid M, Zubair T, Usman M, Haq RU. Numerical investigation of fractional-order unsteady natural convective radiating flow of nanofluid in a vertical channel. AIMS Math. 2019;4:1416–29. 10.3934/math.2019.5.1416 Search in Google Scholar

[64] Razzaq A. Heat and mass transfer analysis of Brinkman type fractional nanofluid over a vertical porous plate with velocity slip and Newtonian heating. Punjab Univ J Math. 2019;51:45–69. Search in Google Scholar

[65] Saqib M, Ali F, Khan I, Sheikh NA, Khan A. Entropy generation in gifferent types of fractionalized nanofluids. Arabian J Sci Eng. 2019;44:531–40. 10.1007/s13369-018-3342-8 Search in Google Scholar

[66] Sheikh NA, Ching DL, Khan I, Ahmad A, Ammad S. Concrete based Jeffrey nanofluid containing Zinc Oxide nanostructures: application in cement industry. Symmetry. 2020;12:1–17. 10.3390/sym12061037 Search in Google Scholar

[67] Anwar T, Kumam P, Thounthong P, Sitthithakerngkiet K. Nanoparticles shape effects on thermal performance of Brinkman-typeferrofluid under heat injection/consumption and thermal radiation: a fractional model with non-singular kernel and non-uniform temperature and velocity conditions. J Mol Liq. 2021;335:116107. 10.1016/j.molliq.2021.116107 Search in Google Scholar

[68] Anwar T, Kumam P, Shah Z, Sitthithakerngkiet K. Significance of shape factor in heat transfer performance of Molybdenum-Disulfide nanofluid in multiple flow situations:a comparative fractional study. Molecules. 2021;26:3711. 10.3390/molecules26123711 Search in Google Scholar PubMed PubMed Central

[69] Madhura KR, Atiwali B, Iyengar SS. Influence of nanoparticle shapes on natural convection flow with heat and mass transfer rates of nanofluids with fractional derivative. Math Meth Appl Sci. 2021;7404:1–17. 10.1002/mma.7404 Search in Google Scholar

[70] Saqib M, Khan I, Shafe S, Mohamad AQ. Shape efect on MHD fow of time fractional Ferro-Brinkman type nanofuid with ramped heating. Sci Rep. 2021;11:3725. 10.1038/s41598-020-78421-z Search in Google Scholar PubMed PubMed Central

[71] Ahmed N, Vieru D, Fetecau C, Shah NL. Convective flows of generalized time-nonlocal nanofluids through a vertical rectangular channel. Phys Fluids. 2018;30:052002. 10.1063/1.5032165 Search in Google Scholar

[72] Povstenko Y. Thermoelasticity based on fractional telegraph equation. In: Fractional thermoelasticity, part of the solid mechanics and its applications. Vol. 219. Częstochowa: Springer; 2015. 10.1007/978-3-319-15335-3_7 Search in Google Scholar

[73] Hajizadeh A, Shah NA, Shah SIA, Animasaun IL, Rahimi-Gorji M, Alarifi IM. Free convection flow of nanofluids between two vertical plates with damped thermal flux. J Mol Liq. 2019;289:110964. 10.1016/j.molliq.2019.110964 Search in Google Scholar

[74] Liang Y, Tlili I, Farooq MU, Butt K. Magnetohydrodynamics free convection flow of Carbon nanotubes viscous nanofluids over an infinite plate with Newtonian heating and fractional derivative. Math Meth Appl Sci. 2020;6481:1–11. 10.1002/mma.6481 Search in Google Scholar

[75] Ahmed N, Shah NA, Ahmad B, Shah SIA, Ulhaq S, Rahimi-Gorji M. MHD convective flow of fractional nanofluid between vertical plates. J Appl Comput Mech. 2019;5:592–602. Search in Google Scholar

[76] Sheikh NA, Ching DLC, Khan I, Sakidin HB, Jamil M, Khalid HU, et al. Fractional model for MHD flow of Casson fluid with cadmium telluride nanoparticles using the generalized Fouriers law. Sci Rep. 2021;11:16117. 10.1038/s41598-021-95528-z Search in Google Scholar PubMed PubMed Central

[77] Asjad MI, Aleem M, Ahmadian A, Salahshour S, Ferrara M. New trends of fractional modeling and heat and mass transfer investigation of (SWCNTs and MWCNTs)-CMC based nanofluids flow over inclined plate with generalized boundary conditions. Chinese J Phys. 2020;66:497–516. 10.1016/j.cjph.2020.05.026 Search in Google Scholar

[78] Khan AQ, Rasheed A. Mixed convection magnetohydrodynamics flow of a nanofluid with heat transfer: a numerical study. Math Problems Eng. 2019:8129564. 10.1155/2019/8129564 Search in Google Scholar

[79] Anwar MS, Ahmad RTM, Shahzad T, Irfan M, Ashraf MZ. Electrified fractional nanofluid flow with suspended carbon nanotubes. Comput Math Appl. 2020;80:1375–86. 10.1016/j.camwa.2020.07.005 Search in Google Scholar

[80] Babitha, Madhura KR, Makinde OD. Computational study on heat transfer and MHD-electrified flow of fractional Maxwell nanofluids suspended with SWCNT and MWCNT. Heat Transfer. 2021;50:5813–34. 10.1002/htj.22150 Search in Google Scholar

[81] Gul T, Khan MA, Noman W, Khan I, Alkanhal TA, Tlili I. Fractional order forced convection carbon nanotube nanofluid flow passing over a thin needle. Symmetry. 2019;11:312. 10.3390/sym11030312 Search in Google Scholar

[82] Gul T, Anwar H, Khan MA, Khan I, Kumam P. Integer and non-integer order study of the GO-W/GO-EG nanofluids flow by means of Marangoni convection. Symmetry. 2019;11:640. 10.3390/sym11050640 Search in Google Scholar

[83] Aly AM, Raizah Z, Al-Hanaya A. Double rotations between an inner wavy shape and a hexagonal-shaped cavity suspended by NEPCM using a time-fractional derivative of the ISPH method. Int Commun Heat Mass Transf. 2021;127:105533. 10.1016/j.icheatmasstransfer.2021.105533 Search in Google Scholar

[84] Al-Hanaya Roohi RA, Heydari MH, Sun HG. Numerical study of unsteady natural convection of variable-order fractional Jeffrey nanofluid over an oscillating plate in a porous medium involved with magnetic, chemical and heat absorption effects using Chebyshev cardinal functions. Eur Phys J Plus. 2019;134:535. 10.1140/epjp/i2019-12873-9 Search in Google Scholar

[85] Azhar WA, Vieru D, Fetecau C. Free convection flow of some fractional nanofluids over a moving vertical plate with uniform heat flux and heat source. Phys Fluids. 2017;29:082001. 10.1063/1.4996034 Search in Google Scholar

[86] Ali F, Ahmad Z, Arif M, Khan I, Nisar KS. A time fractional model of generalized couette flow of couple stress nanofluid with heat and mass transfer: applications in engine oil. IEEE Access. 2020;8:146944. 10.1109/ACCESS.2020.3013701 Search in Google Scholar

[87] Abro KA, Abdon A. A computational technique for thermal analysis in coaxial cylinder of one-dimensional flow of fractional Oldroyd-B nanofluid. Int J Ambient Energy. 2022;43(1):5357–65. 10.1080/01430750.2021.1939157 Search in Google Scholar

[88] Aleem M, Asjad MI, Shaheen A, Khan I. MHD Influence on different water based nanofluids (TiO2, Al2O3, CuO) in porous medium with chemical reaction and newtonian heating. Chaos Solitons Fractals. 2020;130:109437. 10.1016/j.chaos.2019.109437 Search in Google Scholar

[89] Abro KA, Hussain M, Baig MM. An analytic study of molybdenum disulfide nanofluids using the modern approach of Atangana-Baleanu fractional derivatives. Eur Phys J Plus. 2017;132:439. 10.1140/epjp/i2017-11689-y Search in Google Scholar

[90] Jan SAA, Ali F, Sheikh NA, Khan I, Saqib M, Gohar M. Engine oil based generalized brinkman-type nano-liquid with molybdenum disulphide nanoparticles of spherical shape: Atangana-Baleanu fractional model. Numer Meth Partial Differ Equ. 2018;34:1472–88. 10.1002/num.22200 Search in Google Scholar

[91] Saqib M, Khan I, Shafie S. Application of Atangana-Baleanu fractional derivative to MHD channel flow of CMC-based-CNTs nanofluid through a porous medium. Chaos Solitons Fractals. 2018;116:79–85. 10.1016/j.chaos.2018.09.007 Search in Google Scholar

[92] Abro KA, Rashidi MM, Khan I, Abro IA, Tassaddiq A. Analysis of Stokes second problem for Nanofluids using modern approach of Atangana-Baleanu fractional derivative. J Nanofluids. 2018;7:738–47. 10.1166/jon.2018.1486 Search in Google Scholar

[93] Khan I. New idea of Atangana and Baleanu fractional derivatives to human blood flow in nanofluids. Chaos. 2019;29:013121. 10.1063/1.5078738 Search in Google Scholar PubMed

[94] Saqib M, Ali F, Khan I, Sheikh NA, Shafie SB. Convection in ethylene glycol-based molybdenum disulfide nanofluid. J Therm Anal Calorim. 2019;135:523–32. 10.1007/s10973-018-7054-9 Search in Google Scholar

[95] Saqib M, Khan I, Shafie S. Shape effect in magnetohydrodynamic free convection flow of sodium alginate-ferrimagnetic nanofluid. J Therm Sci Eng Appl. 2019;11:041019–1. 10.1115/1.4044201 Search in Google Scholar

[96] Abro KA, Laghari MH, Gomez-Aguilar JF. A aplication of Atangana-Baleanu fractional derivative to carbon nanotubes based non-Newtonian nanofluid: applications in nanotechnology. J Appl Comput Mech 2020;6:1260–9. Search in Google Scholar

[97] Ali F, Saqib M, Khan I, Sheikh NA. Heat transfer analysis in ethylene glycol based molybdenum disulfide generalized nanofluid via Atangana-Baleanu fractional derivative approach. Studies in systems, fractional derivatives with Mittag-Leffler kernel. 2019;194:217–33. 10.1007/978-3-030-11662-0_13 Search in Google Scholar

[98] Tassaddiq A, Khanb I, Nisar KS. Heat transfer analysis in sodium alginate based nanofluid using MoS2 nanoparticles: Atangana-Baleanu fractional model. Chaos Solitons Fractals. 2020;130:109445. 10.1016/j.chaos.2019.109445 Search in Google Scholar

[99] Arif M, Ali. F, Khan I, Nisar KS. A time fractional model with non-singular kernel the generalized Couette flow of fouple stress nanofluid. IEEE Access. 2020;8:77378–95. 10.1109/ACCESS.2020.2982028 Search in Google Scholar

[100] Saqib M, Kasim ARM, Mohammad NF, Ling D, Ching C, Shafie S. Application of fractional derivative without singular and local kernel to enhanced heat transfer in CNTs manofluid over an inclined plate. Symmetry. 2020;12:768. 10.3390/sym12050768 Search in Google Scholar

[101] Khan I, Saqib M, Alqahtani AM. Channel flow of fractionalized H2O-based CNTs nanofluids with Newtonian heating. Discrete Contin Dyn Syst. 2020;13:769–79. 10.3934/dcdss.2020043 Search in Google Scholar

[102] Murtaza S, Iftekhar M, AliAamina F, Khan I. Exact analysis of non-Linear electro-osmotic flow of generalized Maxwell nanofluid: applications in aoncrete based nano-materials. IEEE Access. 2020;4:99. 10.1109/ACCESS.2020.2988259 Search in Google Scholar

[103] Abro KA, Chandio AD, Abro IA, Khan I. Dual thermal analysis of magnetohydrodynamic flow of nanofluids via modern approaches of Caputo-Fabrizio and Atangana-Baleanu fractional derivatives embedded in porous medium. J Therm Anal Calorim. 2019;135:2197–207. 10.1007/s10973-018-7302-z Search in Google Scholar

[104] Abro KA, Khan I, Nisar KS, Alsagri AS. Effects of carbon nanotubes on magnetohydrodynamic flow of methanol based nanofluids via Atangana-Baleanu and Caputo-Fabrizio derivatives. Therm Sci. 2019;23:883–98. 10.2298/TSCI180116165A Search in Google Scholar

[105] Abro KA, Soomro M, Atangana A, GomezAguilar JF. Thermophysical properties of Maxwell nanofuids via fractional derivatives with regular kernel. J Therm Anal Calorim. 2022;147:449–59. 10.1007/s10973-020-10287-9 Search in Google Scholar

[106] Abro KA, Siyal A, Atangana A. Thermal stratifcation of rotational second grade fuid through fractional diferential operators. J Therm Anal Calorim. 2021;143:3667–76. 10.1007/s10973-020-09312-8 Search in Google Scholar

[107] Ali F, Murtaza S, Sheikh NA, Khan I. Heat transfer analysis of generalized Jeffery nanofluid in a rotating frame: Atangana-Balaenu and Caputo-Fabrizio fractional models. Chaos Solitons Fractals. 2019;129:1–5. 10.1016/j.chaos.2019.08.013 Search in Google Scholar

[108] Xiao Y, Shah NA, Irshad T. Magneto-hydrodynamics natural convection flows of viscous carbon nanotubes nanofluids with generalized Fourier’s law in a vertical cylinder. Math Meth Appl Sci. 2020;6566:1–6. 10.1002/mma.6566 Search in Google Scholar

[109] Danish Ikram M, Imran Asjad M, Ahmadian A, Ferrara M. A new fractional mathematical model of extraction nanofluids using clay nanoparticles for different based fluids. Math Meth Appl Sci. 2020;6568:1–14. 10.1002/mma.6568 Search in Google Scholar

[110] Saqib M, Khan I, Chu Y, Qushairi A, Shafie S, Nisar KS. Multiple fractional solutions for magnetic bio-nanofluid using Oldroyd-B model in a porous medium with ramped wall heating and variable velocity. Appl Sci. 2020;10:3886. 10.3390/app10113886 Search in Google Scholar

[111] Elnaqeeb T, Shah NA, Mirza IA. Natural convection flows of carbon nanotubes nanofluids with Prabhakar-like thermal transport. Math Meth Appl Sci. 2020;1–14. 10.1002/mma.6584 Search in Google Scholar

[112] Tanveer M, Ullah S, Shah NA, Thermal analysis of free convection fows of viscous carbon nanotubes nanofuids with generalized thermal transport: a Prabhakar fractional model. J Therm Anal Calorim. 2021;144:2327–36. 10.1007/s10973-021-10643-3 Search in Google Scholar

[113] Wang F, Asjad MI, Zahid M, Iqbal A, Ahmad H, Alsulami MD. Unsteady thermal transport flow of Casson nanofluids with generalized Mittage Leffler kernel of Prabhakaras type. J Mater Res Technol. 2021;14:1292–300. 10.1016/j.jmrt.2021.07.029 Search in Google Scholar

[114] Arafa AM, Rashed ZZ, Ahmed SE. Radiative fow of non Newtonian nanofuids within inclined porous enclosures with time fractional derivative. Sci Rep. 2021;11:5338. 10.1038/s41598-021-84848-9 Search in Google Scholar PubMed PubMed Central

[115] Azwadi CSN, Adamu IM, Jamil MM. Preparation methods and thermal performance of hybrid nanofluids. J Adv Rev Sci Res. 2016;241:13–23. Search in Google Scholar

[116] Hossein K, Saeed A, Hootan M, Rasool K, Somchai W, Masoud A. A comprehensive review on rheological behavior of mono and hybrid nanofluids: effective parameters and predictive correlations. Int J Heat Mass Transf. 2018;127:997–1012. 10.1016/j.ijheatmasstransfer.2018.07.103 Search in Google Scholar

[117] Baby TT, Ramaprabhu S. Experimental investigation of the thermal transport properties of a carbon nanohybrid dispersed nanofluid. Nanoscale. 2011;3(5):2208–14. 10.1039/c0nr01024c Search in Google Scholar PubMed

[118] Huang D, Wu Z, Sunden B. Effects of hybrid nanofluid mixture in plate heat exchangers. Exp Thermal Fluid Sci. 2016;72:190–6. 10.1016/j.expthermflusci.2015.11.009 Search in Google Scholar

[119] Hussanan A, Salleh MZ, Khan I, Shafie S. Convection heat transfer in micropolar nanofluids with oxide nanoparticles in water, kerosene and engine oil. J Mol Liq. 2017;229:482–8. 10.1016/j.molliq.2016.12.040 Search in Google Scholar

[120] Aman S, Khan I, Ismail Z, Salleh MZ, Alshomrani AS, Alghamdi MS. Magnetic field effect on Poiseuille flow and heat transfer of carbon nanotubes along a vertical channel filled with Casson fluid. AIP Adv. 2017;7:015036. 10.1063/1.4975219 Search in Google Scholar

[121] Bing KY, Hussanan A, Mohamed KKA, Sarif NM, Ismail Z, Salleh MZ. Thermal radiation effect on MHD flow and heat transfer of Williamson nanofluids over a stretching sheet with Newtonian heating. AIP Confer Proc. 2017;1830:020022. 10.1063/1.4980885 Search in Google Scholar

[122] Fallah B, Dinarvand S, Yazdi ME, Rostami MN, Pop I. MHD flow and heat transfer of SiC-TiO2/DO hybrid nanofluid due to a permeable spinning disk by a novel algorithm. J Appl Comput Mech. 2019;5:976–88. Search in Google Scholar

[123] Reddy MG, Shehzad SA. Molybdenum disulfide and magnesium oxide nanoparticle performance on micropolar Cattaneo-Christov heat flux model. Appl Math Mech Engl Ed. 2021;42:541–52. 10.1007/s10483-021-2713-9 Search in Google Scholar

[124] Tripathi1 D, Prakash J, Reddy MG, Kumar R. Numerical study of electroosmosis-induced alterations in peristalticpumping of couple stress hybrid nanofluids through microchannel. Indian J Phys. 2021;95:2411–21. 10.1007/s12648-020-01906-0 Search in Google Scholar

[125] Izady M, Dinarvand S, Pop I, Chamkha AJ. Flow of aqueous Fe2O3-CuO hybrid nanofluid over a permeable stretching/shrinking wedge: a development on Falkne-Skan problem. Chinese J Phys. 2021;74:406–20. 10.1016/j.cjph.2021.10.018 Search in Google Scholar

[126] Mousavi SM, Rostami MN, Yousefi M, Dinarvand S, Pop I, Sheremet MA. Dual solutions for Casson hybrid nanofluid flow due to a stretching/shrinking sheet: A new combination of theoretical and experimental models. Chinese J Phys. 2021;71:574–88. 10.1016/j.cjph.2021.04.004 Search in Google Scholar

[127] Jabbaripour B, Nademi Rostami M, Dinarvand S, Pop I. Aqueous aluminium-copper hybrid nanofluid flow past a sinusoidal cylinder considering three-dimensional magnetic field and slip boundary condition. Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering. 10.1177/09544089211046434 . Search in Google Scholar

[128] Safw N, Norihan K, Arifin M, Pop I. Magnetohydrodynamics (MHD) boundary layer flow of hybrid nanofluid over a moving plate with Joule heating. Alexandria Eng J. 2022;61:1938–45. 10.1016/j.aej.2021.07.032 Search in Google Scholar

[129] Alsaedi A, Muhammad K, Hayat T. Numerical study of MHD hybrid nanofluid flow between two coaxial cylinders. Alexandr Eng J. 2022;61:8355–62. 10.1016/j.aej.2022.01.067 Search in Google Scholar

[130] Berrehal H, Dinarvand S, Khan I. Mass-based hybrid nanofluid model for entropy generation analysis of flow upon a convectively-warmed moving wedge. Chinese J Phys. 2022;77:2603–16. 10.1016/j.cjph.2022.04.017 Search in Google Scholar

[131] Dinarvand S. Nodal/saddle stagnation-point boundary layer flow of CuOCAg/water hybrid nanofluid: a novel hybridity model. Microsyst Technol. 2019;25:2609–23. 10.1007/s00542-019-04332-3 Search in Google Scholar

[132] Aman S, Zokriderivative SM, Ismail Z, Salleh MZ, Khan I. Effect of MHD and porosity on exact solutions and flow of a Hybrid Casson-nanofluid. J Adv Res Fluid Mech Therm Sci. 2018;44:131–9. Search in Google Scholar

[133] Aman S, Zokri SM, Ismail Z, Salleh MZ, Khan I. Casson model of MHD flow of SA–Based hybrid nanofluid using Caputo time-fractional models. Defect Diffusion Forum Online. 2019;390:83–90. 10.4028/www.scientific.net/DDF.390.83 Search in Google Scholar

[134] Ahmed SE. Caputo fractional convective flow in an inclined wavy vented cavity filled with a porous medium using Al2O3-Cu hybrid nanofluids. Int Commun Heat Mass Transf. 2020;116:104090. 10.1016/j.icheatmasstransfer.2020.104690 Search in Google Scholar

[135] Ali R, Asjad MI, Akgul A. An analysis of a mathematical fractional model of hybrid viscous nanofluids and its application in heat and mass transfer. J Comput Appl Math. 2021;383:113096. 10.1016/j.cam.2020.113096 Search in Google Scholar

[136] Ali R, Asjad MI, Aldalbahi A, Gorji MR, Rahaman M. Convective fow of a Maxwell hybrid nanofuid due to pressure gradient in a channel. J Therm Anal Calorim. 2021;143:1319–29. 10.1007/s10973-020-10304-x Search in Google Scholar

[137] Ali R, Akgul A, Asjad MI. Power law memory of natural convection flow of hybrid nanofluids with constant proportional Caputo fractional derivative due to pressure gradient. Pramana-J Phys. 2020;94:131. 10.1007/s12043-020-01997-8 Search in Google Scholar

[138] DanishIkram M, Asjad MI, Akgul A, Baleanu D. Effects of hybrid nanofluid on novel fractional model of heat transfer flow between two parallel plates. Alexandria Eng J. 2021;60:3593–604. 10.1016/j.aej.2021.01.054 Search in Google Scholar

[139] Chu Y, Ikram MD, Asjad MI, Ahmadian A, Ghaemi F. Infuence of hybrid nanofuids and heat generation on coupled heat and mass transfer fow of a viscous fuid with novel fractional derivative. J Therm Anal Calorim. 2021;144:2057–77. 10.1007/s10973-021-10692-8 Search in Google Scholar

[140] Gohar M, Ali F, Khan I, Sheikh NA, Shah A. The unsteady flow of generalized hybrid nanofluids: applications in cementitious materials. J Australian Ceramic Soc. 2019;55:657–66. 10.1007/s41779-018-0275-3 Search in Google Scholar

[141] Ahmad M, Imran MA, Nazar M. Mathematical modeling of (Cu-Al2O3)water based Maxwell hybrid nanofluids with Caputo-Fabrizio fractional. Adv Mech Eng. 2020;12(9):1–11. 10.1177/1687814020958841 Search in Google Scholar

[142] Saqib M, Khan I, Shafie S. Application of fractional differential equations to heat transfer in hybrid nanofluid: modeling and solution via integral transforms. Adv Differ Equ. 2019;2019:52. 10.1186/s13662-019-1988-5 Search in Google Scholar

[143] Saqib M, Shafie S, Khan I, Chu Y, Nisar KS. Symmetric MHD channel flow of nonlocal fractional model of BTF containing hybrid nanoparticles. Symmetry. 2020;12:663. 10.3390/sym12040663 Search in Google Scholar

[144] Anwar T, Kumam P, Thounthong P. A comparative fractional study to evaluate thermalperformance of NaAlg-MoS2-Co hybrid nanofluid subject to shape factor and dual ramped conditions. Alexandria Eng J. 2022;61(3):2166–87. 10.1016/j.aej.2021.06.085 Search in Google Scholar

[145] Anwar T, Kumam P, Thounthong P. Fractional modeling and exact solutions to analyze thermal performance of Fe3O4-MoS2-Water hybrid nanofluid flow over an inclined surface with ramped heating and ramped boundary motion. IEEE Access. 2021;9:12389. 10.1109/ACCESS.2021.3051740 Search in Google Scholar

[146] Ye X, Kandlikar SG, Li C. Viscosity of nanofluids containing anisotropic particles: a critical review and a comprehensive model. Eur Phys J E. 2019;42:159. 10.1140/epje/i2019-11923-7 Search in Google Scholar PubMed

[147] Otanicar TP, Phelan PE, Prasher RS, Rosengarten G, Taylor RA. Nanofluid based direct absorption solar collector. J Renewable Sustainable Energy. 2010;2:033102. 10.1063/1.3429737 Search in Google Scholar

[148] Loganathan P, Nirmal Chand P, Ganesan P. Radiation effects on an unsteady natural convective flow of a nanofluid past an infinite vertical plate. Nano Br Rep Rev. 2013;8:1–10. 10.1142/S179329201350001X Search in Google Scholar

[149] Bait O, Ameur MS. Enhanced heat and mass transfer in solar stills using nanofluids: a review. Solar Energy. 2018;170:694–722. 10.1016/j.solener.2018.06.020 Search in Google Scholar

[150] Aman S, Khan I, Ismail Z, Salleh MZ, Tlili I. A new Caputo time fractional model for heat transfer enhancement of water based graphene nanofluid: an application to solar energy. Results Phys. 2018;9:1352–62. 10.1016/j.rinp.2018.04.007 Search in Google Scholar

[151] Abro KA, Memon AA, Abro SH, Khan I, Tlili I. Enhancement of heat transfer rate of solar energy via rotating Jeffrey nanofluids using Caputo-Fabrizio fractional operator: an application to solar energy. Energy Reports. 2019;5:41–49. 10.1016/j.egyr.2018.09.009 Search in Google Scholar

[152] Sheikh NA, Ali F, Khan I, Gohar M, Saqib M. On the applications of nanofluids to enhance the performance of solar collectors: A comparative analysis of Atangana-Baleanu and Caputo-Fabrizio fractional models. Eur Phys J Plus. 2017;132:540. 10.1140/epjp/i2017-11809-9 Search in Google Scholar

[153] Sheikha NA, Ali F, Khand I, Gohar M. A theoretical study on the performance of a solar collector using CeO2 and Al2O3 water based nanofluids with inclined plate: Atangana-Baleanu fractional model. Chaos Solitons Fractals 2018;115:135–42. 10.1016/j.chaos.2018.08.020 Search in Google Scholar

[154] Aamina, Ali F, Khan I, Sheikh NA, Gohar M. Exact solutions for the Atangana-Baleanu time-fractional model of a Brinkman-type nanofluid in a rotating frame: applications in solar collectors. Eur Phys J Plus. 2019;134:119. 10.1140/epjp/i2019-12455-y Search in Google Scholar

[155] ElBialy E, Shalaby M. An experimental investigation of a v-corrugated absorber single basin solar still using PCM. Desalination. 2016;398:147–255. Search in Google Scholar

[156] Panchal H, Sadasivuni KK, Suresh M, Yadav S. Performance analysis of evacuated tubes coupled solar still with double basin solar still and solid fins. Int J Ambient Energy. 2022;41(9):1031–7. 10.1080/01430750.2018.1501745 Search in Google Scholar

[157] Elbar ARA, Hassan H. An experimental work on the performance of solar still incorporating with wind turbine and thermal energy storage unit, Desalin Water Treat. 2019;165:24–34. 10.5004/dwt.2019.24492 Search in Google Scholar

[158] Elango T, Kannan A, Murugavel KK, Performance study on single basin single slope solar still with different water nanofluids. Desalination. 2015;360:45–51. 10.1016/j.desal.2015.01.004 Search in Google Scholar

[159] Sharshir SW, Peng G, Wu L, Yang N, Essa FA, Elsheikh AH, et al. Enhancing the solar still performance using nanofluids and glass cover cooling: experimental study. Appl Therm Eng. 2017;113:684–93. 10.1016/j.applthermaleng.2016.11.085 Search in Google Scholar

[160] Rashidi S, Akar S, Bovand M, Ellahi R. Volume of fluid model to simulate the nanofluid flow and entropy generation in a single slope. Solar Still. 2018;115:400–10. 10.1016/j.renene.2017.08.059 Search in Google Scholar

[161] El-Gazar Hamdy Hassan EF, Rabia SI, Zahra WK. Fractional modeling for enhancing the thermal performance of conventional solar still using hybrid nanofluid: Energy and exergy analysis. Eur Phys J Plus. 2021;136:717. Search in Google Scholar

[162] Khan AK, Rashid R, Murtaza G, Zahra A. Gold nanoparticles: synthesis and applications in drug delivery. Tropical J Pharm Res. 2014;13:1169–77. 10.4314/tjpr.v13i7.23 Search in Google Scholar

[163] Eldabe NT, Moatimid GM, El-Shekhipy AA, Aballah NF. Peristaltic blood flow with gold nanoparticles on a Carreau nanofluid through a non-Darcian porous medium. J Biomaterials Nanobiotechnol. 2018;9:0487707. 10.4236/jbnb.2018.94019 Search in Google Scholar

[164] Mekheimer KS, Hasona WM, Abo-Elkhair RE, Zaher AZ. Peristaltic blood flow with gold nanoparticles as a third grade nanofluid in catheter: application of cancer therapy. Phys Lett A. 2018;382:85–93. 10.1016/j.physleta.2017.10.042 Search in Google Scholar

[165] Abdelsalam SI, Mekheimer KS, Zaher AZ. Alterations in blood stream by electroosmotic forces of hybrid nanofluid through diseased artery: Aneurysmal/stenosed segment. Chinese J Phys. 2020;67:314–29. 10.1016/j.cjph.2020.07.011 Search in Google Scholar

[166] Al-Habahbeh OM, Al-Saqqa M, Safi M, Khater TA. Review of magneto hydrodynamic pump applications. Alexandria Eng J. 2016;55(2):1347–58. 10.1016/j.aej.2016.03.001 Search in Google Scholar

[167] Cao L, Zhang P, Si X. Electroosmotic fow of two-layer fuid containing Oldroyd-B fuid with fractional derivative in a rotating microparallel channel. Microfluidics Nanofluidics. 2022;26:34. 10.1007/s10404-022-02539-x Search in Google Scholar

[168] Liang P, Wang S, Zhao M. Numerical study of rotating electroosmotic flow of Oldroyd-B fluid in a microchannel with slip boundary condition. Chinese J Phys. 2020;65:459–71. 10.1016/j.cjph.2020.02.025 Search in Google Scholar

[169] Abd Elmaboud Y. Electroosmotic flow of generalized Burgers’ fluid with Caputo–Fabrizio derivatives through a vertical annulus with heat transfer. Alex Eng J. 2020;59:4563–75. 10.1016/j.aej.2020.08.012 Search in Google Scholar

[170] Alsharif AM, Abdellateef AI, Elmaboud YA, Abdelsalam SI. Performance enhancement of a DC-operated micropump with electroosmosis in a hybrid nanofluid: fractional Cattaneo heat flux problem. Appl Math Mech -Engl Ed. 2022;43:931–44. 10.1007/s10483-022-2854-6 Search in Google Scholar

[171] Alsharif AM, Abd Elmaboud Y. Electroosmotic flow of generalized fractional second grade fluid with fractional Cattaneo model through a vertical annulus. Chinese J Phys. 2022;77:1015–28. 10.1016/j.cjph.2021.08.021 Search in Google Scholar

© 2022 the author(s), published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

• X / Twitter

Supplementary Materials

Please login or register with De Gruyter to order this product.

Journal and Issue

Articles in the same issue.

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Open access
• Published: 15 September 2023

A critical insight on nanofluids for heat transfer enhancement

• Abdul Hai Alami 1 , 2 ,
• Mohamad Ramadan 3 , 4 ,
• Muhammad Tawalbeh 1 , 2 ,
• Salah Haridy 2 , 5 , 6 ,
• Shamma Al Abdulla 1 ,
• Haya Aljaghoub 2 , 5 ,
• Mohamad Ayoub 1 , 2 ,
• Adnan Alashkar 7 ,
• Mohammad Ali Abdelkareem 1 , 2 &
• Abdul Ghani Olabi 1 , 2  

Scientific Reports volume  13 , Article number:  15303 ( 2023 ) Cite this article

3806 Accesses

5 Citations

Metrics details

• Materials science
• Mechanical engineering
• Nanoscale materials

There are numerous reports and publications in reputable scientific and engineering journals that attribute substantial enhancement in heat transfer capabilities for heat exchangers once they employ nanofluids as working fluids. By definition, a nanofluid is a working fluid that has a small volume fraction (5% or less) of a solid particle with dimensions in the nanoscale. The addition of this solid material has a reported significant impact on convective heat transfer in heat exchangers. This work investigates the significance of the reported enhancements in many recent related publications. Observations on these publications’ geographical origins, fundamental heat transfer calculations, experimental setups and lack of potential applications are critically made. Heat transfer calculations based on methodologies outlined in random selection of available papers were conducted along with a statistical analysis show paradoxically inconsistent conclusion as well as an apparent lack of complete comprehension of convective heat transfer mechanism. In some of the surveyed literature for example, heat transfer coefficient enhancements were reported to be up to 27% and 48%, whereas the recalculations presented in this work restrain proclaimed enactments to ~ 3.5% and − 4% (no enhancement), respectively. This work aims at allowing a healthy scientific debate on whether nanofluids are the sole answer to enhancing convective heat transfer in heat exchangers. The quantity of literature that confirms the latter statement have an undeniable critical mass, but this volition could be stemming from and heading to the wrong direction. Finally, the challenges imposed by the physical nature of nanoparticles, as well as economic limitations caused by the high price of conventional nanoparticles such as gold (80$/g), diamond (35$/g), and silver (6$/g) that hinder their commercialization, are presented.

Similar content being viewed by others

The significance of chemical reaction, thermal buoyancy, and external heat source to optimization of heat transfer across the dynamics of Maxwell nanofluid via stretched surface

Significance of heat transfer rate in water-based nanoparticles with magnetic and shape factors effects: Tiwari and Das model

Conjugate buoyant convective transport of nanofluids in an enclosed annular geometry

Introduction.

There are many scientific points of contention in the presentation of results for the claimed enhancement in either the working fluid heat transfer properties (thermophysical) or in the alleged enhancement of heat transfer in general. This fact is found to be true for the majority of the articles reviewed in this work, where the definition and calculation of heat transfer and its desired departure from the baseline working fluid performance is either not clear or completely erroneous.

It is well-known that convective heat transfer is one of the most complex phenomena in heat transfer. Physically, it commences as conduction between a solid surface and adjacent static fluid molecules, which is so far from a pure conduction problem and heat transfer can be determined accurately and easily. But as the molecules gain (or lose) thermal energy, their specific volume also changes accordingly, and a relative motion is initiated by the thermally induced density gradient like hot air balloons. This motion capitalizes on the intrinsically generated buoyancy force. As fluid motion gains more momentum (signified by the velocity increase of particles), the mechanism of heat transfer switches to convection, as the conditions for conduction are no longer applicable and its contribution diminishes.

Heat transfer by convection is a complex phenomenon, as it is directly influenced by several interdependent factors that relate not only to fluid type or properties but also to the nature of fluid flow. It is important to mention a trivial fact that may be inconspicuous for students and researchers of convective heat transfer. This mode of heat transfer is unimportant if it is not in direct contact with a solid surface at a temperature different than that of the working fluid. Anything far enough from the solid surface (or body) is free from thermal and viscous effects that arise due to the proximity of the fluid to that solid. The geometrical shape, surface roughness and physical boundaries of the solid play a significant role in the quality of heat transfer within the fluid as it is responsible for mixing vigor and thus the homogeneity of the heat transfer. The thermophysical properties of the fluid, on the other hand, are also responsible for the quality of heat transfer between the fluid molecules. The thermal conductivity, heat capacity and density are all factors that directly affect heat transfer and it is desirable to couple the fluid flow parameters and thermophysical properties of the fluid in such a manner as to achieve an as high as possible heat transfer effectiveness.

This work discusses the limitations and implications of conventional heat transfer coefficient calculation methods. A summary on previously conducted literature review is shown in Table 1 . They provide insights on the preparation of nanofluids, enhancements as proclaimed by corresponding researchers, as well as the utilization of nanofluids across different applications. However, they seem to lack perspective on the calculations carried out by the reported research, which may give a false sense of enhancement in some cases. As the conducted literature review reveals that only a small percentage of authors have thoroughly assessed the convective heat transfer problem from both fluid flow and thermophysical properties perspectives. Discretizing problems, leading to measuring the thermophysical properties of nanomaterials and applying deterministic heat transfer equations, without taking into account the biases introduced by this approach, is a common ground between a myriad of published works. Moreover, experimental setups for heat transfer measurement lack sensitivity and error analysis. Which is why this work puts into perspective the recalculation of the convective heat transfer coefficients from previously published work, utilizing suitable convective heat transfer relations to examine the proclaimed enhancements. Furthermore, the paper examines maintenance and implementation challenges of using nanofluids in practical heat exchangers, including agglomeration, impaired heat transfer, and the high cost of conventional nanoparticles.

Convective heat transfer basics and enhancements

Analyzing the interaction of the two complex sets of influential parameters (fluid flow and thermophysical) has been the holy grail of any research in convective heat transfer. Fluid dynamics is currently governed by the relationships established by Navier–Stokes and documented by their equations. In these equations, the effects of interaction of body, pressure, and viscous forces on the change of velocity in both magnitude and direction in all three dimensions is detailed. These famous equations sets still cannot be analytically solved and thus cannot be applied to scenarios under laboratory control, let alone in real life applications.

What Bernoulli was able to achieve in simplifying the Navier–Stokes equation for one dimensional, incompressible, and inviscid flow (a single line, simple equation) has resulted in all domestic, industrial, military and aerospace advancements relating to fluid flow to date. Of course, his equations needed modifiers in the form of friction graphs (Moody diagram) or compressible flow assumptions (polytropic flow around shockwaves).

As for heat transfer analysis, even with the rare situations where the thermophysical properties are unambiguously defined, once the convective mechanism becomes the most dominant heat transfer mode the estimation of energy transfer can be too divergent from real or measured values. The relative simplicity of Newton’s law of cooling, which is the following equation:

where Q is the heat transfer in [J], A is the solid surface area in contact with the fluid in [m 2 ], \({T}_{s}\) and \({T}_{\infty }\) are surface and ambient temperatures in [K], respectively.

The convective heat transfer coefficient, h in [J/m 2 K], seems deceptively easy to determine from this straightforward relationship. But if one is to examine its values from any heat transfer textbook, its variation can be from 2 J/m 2 K for natural convection of air up to 100,000 J/m 2 K for turbulent flow heat transfer that involves phase change of a liquid working fluid. This is an indication of the complexity of the heat transfer problem under convection. The accuracy in determining the convective heat transfer coefficient so it can be plugged into Eq. ( 1 ) proves to be an unsurmountable impasse for any practical application, mainly due to the lack of direct coupling of heat transfer with the influence of fluid flow.

By consulting most practical heat transfer textbooks and speaking from a pragmatic engineering perspective, empirical formulas were heavily used by engineers and practitioners to facilitate the speed with which they obtained answers to heat transfer problems. All empirical formulas are practical and save extensive (and precious) time needed to setup and solve analytical or simulation models. The empirical models are currently properly documented in literature and are taught in most engineering heat transfer courses. The main and obvious drawback of employing empirical formulas in heat transfer is that they all come with a disclaimer that if their boundary conditions are not obeyed or experimental constraints observed, the results can be off by as much as 30% in some cases. Still, for most practical applications, this percentage is a small price to pay if a solution is offered in a fraction of the time needed for simulation and with a clear error margin that can be incorporated into a factor of safety that has a finite and measurable effect on the price of the heat transfer solution being designed.

Experimental assessment of convective heat transfer

Convective heat transfer phenomenon is quite complex, and its mathematical analysis requires rigorous solution of multi-variate and multi-dimensional system of differential equations. One pathway to follow the empirical router and feed simplified forms of these differential equations with well-designed experimental results. The empirical formulae used to assess convective heat transfer take the following general form:

where Nu is the dimensionless Nusselt number, h is the convective heat transfer coefficient in [J/m 2 K], k is the thermal conductivity of the fluid in [J/mK], D is a characteristic length in [m] (can be L in the case of flat plates, D if the flow is around a curved body), Re is the Reynolds number [dimensionless] and Pr is Prandtl number [dimensionless], C, m and n are coefficients that correspond to the original data fit and are available in all heat transfer textbooks.

Eq. ( 2 ) has two parts and is solved for Nu from a fluid flow perspective first. This part involves evaluating Re as well as selecting a value for Prandtl number, which relates momentum diffusivity to thermal diffusivity (which is almost fixed for specific fluids and available in literature). Then, the convective heat transfer coefficient can be estimated by multiplying the freshly found Nusselt number with the thermal conductivity of the fluid and dividing it by the characteristic length. The value of ( h ) can then be substituted into Eq. ( 1 ) and the heat transfer is estimated with the pertinent accuracy limitation that might necessitate quoting the value with a higher and a lower limit and make the design decision accordingly.

The above procedure, with its limitations and implications might be clear for all scholars working with heat transfer. In order to carry out such a standardized test, there are different aspects that should be taken into account, including sample preparation with uniform dispersion and a stable homogeneous nanofluid. Moreover, preventative measures must be upheld to avoid agglomeration and precipitation. Furthermore, characterization techniques that take into account the thermal conductivity of both nanoparticles and nanofluids, viscosity measurements, particle size distribution, and the Zeta potential which studies the dispersion of nanoparticles within nanofluids with time, must be conducted. There is also a need for standardized nanofluids to measure the performance of rising nanofluid combinations upon. Additionally, measurement conditions including temperature, flow velocity, viscosity, and density should be reported in order to allow the reproduction of reported results, all while taking into account error, statistical, and uncertainty analysis.

What this work found in most of the literature surveyed, however, is that only a small percentage of authors went through the exercise of comprehensively assessing the convective heat transfer problem from both fluid flow and thermophysical properties perspectives. The discretization of the naturally continuous and interconnected problem of convective heat transfer is the trap that most researchers appear to have fallen into. As the readers will later see, most authors measured the thermophysical properties of the nanomaterial to be added to the fluid in a certain proportion, adjusted these properties for the nanofluid as an arithmetic average of the amount of fluid times its properties, with the amount of nanomaterial times its properties, and plugged these numbers into deterministic heat transfer equations, which provided a seemingly impressive lines conforming on one another. This is the first major source of bias that will be highlighted in this paper.

The other source of bias that will be discussed in this work is the experimental setups for heat transfer measurement. Most of the setups have thermocouples and thermometers that measures temperature change and plots the performance of the nanofluid at different concentrations of nanomaterial in the solvent. The thermophysical properties are also plotted, but the number of publications that carries out sensitivity analysis or a correct error analysis are also limited. So far, and as will be presented later, the data show obvious overlap with baseline readings, where the whole enhancement would appear to be within the natural variation of the instruments and the process.

Finally, the promised enhancement that these nanofluids offer in heat transfer for heat exchangers will be examined from maintenance and implementation points of view. Most heat exchanging equipment are sensitive to nanoscale particles accumulation over their lifetime, as these particles cause malfunctions or can impede heat transfer. There is also the issue of the cost of such material, as many authors opt for gold and sometimes diamond nanoparticles that have limited chances of being recovered or recycled in the system without significant loss.

Geographical distribution of publications

Research on nanofluids has increased dramatically in the last decade, where numerous experimental and theoretical investigations have been carried out on different aspects of nanofluids 6 . In this analysis, a Scopus database search was conducted to highlight scientific research papers published using the keyword “Nanofluids”. This search and subsequent analysis covers years 2010 to 2022, and shown in Fig.  1 . A total of 124 countries and territories contributed articles to the scene. Where India ranked top in nanofluid publications with 5524 papers. Similarly, researchers in Iran and China published 3907 and 3885 papers, respectively. Furthermore, Pakistan, Saudi Arabia, Malaysia, the United States, Egypt, Turkey, and the United Kingdom also made notable contributions. In terms of publication types, Fig.  2 . shows that the majority of these publications are journal articles, followed by conference papers, reviews, and others.

Publications on nanofluids by region between 2010 and 2022.

Classification of publications.

Heat exchanger design

To be able to compare enhancement in heat transfer due to working fluid substitution, the American Society of Mechanical Engineers (ASME) standards should be invoked. These standards, coupled with engineering heat transfer textbooks single out the double-pipe counter flow heat exchanger as the De facto basis of comparison of different heat transfer changes attributed to the utilization of different working fluid. Usually, the basic run consists of pure water circulated into the heat exchanger using pumps, while temperature variations at inlets and exits of the cold side vs. hot side are recorded and compared. Different flow rates, and thus Re numbers, are also tried so that the temperature profile at steady state operation is then used to estimate Nu and consequently find an estimate to the convective heat transfer coefficient.

In general, there is a lack of consensus in literature as which heat exchanger geometry should be the standard for testing heat transfer enhancements from the addition of nanofluids. Although the simple double-pipe heat exchanger equipped with appropriate temperature, pressure and flow telemetry and data acquisition setup would be expected to standardize the outcome of such experiments and make any comparison more valid and valuable. The most common heat exchangers used for experiments are the circular tube, double pipe and shell-and-tube types. A summary of each is given in the following sections, along with reflections from the authors on the significance of claimed heat transfer enhancement in cited literature.

Circular tube heat exchanger

Convective heat transfer through circular tubes is vital to investigate, due to the multitude of applications that depend on the heat transfer characteristics of fluids inside such tubes. Circular tubes are employed in heat exchangers, boilers, cooling, and solar thermal techniques such as parabolic trough collectors. The application of nanofluids to improve the heat characteristics of fluids inside circular tubes has been extensively studied both experimentally 7 , 8 , 9 and analytically 10 , 11 . The convective heat transfer coefficient of the fluid inside the circular tube is calculated using the following equation:

where the Nusselt number depends on various variables such as the flow type, boundary conditions, Reynolds and Prandtl numbers. For instance, the Nusselt number for a fully developed laminar flow in a circular tube with constant wall temperature be calculated using the following correlation:

For fully developed laminar flow in a circular tube with constant wall heat flux, the Nusselt number can be calculated using the following correlation:

For turbulent flow regimes in a circular tube with constant wall temperature, the Nusselt number can be calculated using the following correlation known as the Dittus Boelter correlation:

For turbulent flow regimes in a circular tube with constant wall heat flux, the Nusselt number can be calculated using the following correlation:

Bianco et al. 12 numerically investigated the heat characteristic of a fully developed laminar flow water-Al 2 O 3 nanofluid in a circular tube. The variation of the Reynolds number and the volume fraction on the convective heat transfer was also studied. The Reynolds number varied between 250, 500, 750, and 1050 respectively. While volume fractions of 1% and 4% were employed. The numerical results showed an improvement of 14% in the convective heat transfer coefficient for a volume fraction of 4% and a Reynolds number of 250. Nevertheless, by employing the same parameters from the study and calculating the improvement in the heat transfer coefficient through the above correlations, an improvement of merely 10% is recorded. This showcases that the calculation of the convective heat transfer coefficient through suitable Nusselt number correlations yields less enhancement, also shown in Fig.  3 12 .

Comparison between present work calculations and Bianco 12 for the heat transfer coefficient.

Ali 10 experimentally investigated the convective heat transfer of SiO 2 /water turbulent flow inside a copper circular tube. The volumetric concentrations of the SiO 2 particles was varied between 0.001%, 0.003%, and 0.007%. The experimental results reported an increase in heat transfer coefficient of approximately 27% when using SiO 2 nanoparticles at a concentration of 0.007%, compared to deionized water, at the highest Reynolds number of 19,500. At a lower concentration of 0.001% SiO 2 nanoparticles, the maximum enhancement in heat transfer was observed to be around 8–9%. As the concentration of SiO 2 nanoparticles increased, there was an observed increase in convective heat transfer coefficient. Nevertheless, by utilizing the above correlations and calculating the heat transfer coefficient through the Nusselt number, an increase of only 2.94% and 3.44% was recorded for the heat transfer coefficient of the nanofluids at concentrations of 0.007% and 0.001%, respectively. Table 2 shows a comparison between the obtained results from 10 and the calculated results.

Karabulut et al. 9 carried out a numerical and experimental analysis to study the convective heart transfer of graphene oxide (GO)/ water nanofluid under turbulent flow inside a circular tube. The convective heat transfer coefficient was obtained through numerical analysis, then utilized to calculate the value of the Nusselt number. The results obtained in this study can be summarized as follows: The average increase in the convection heat transfer coefficient was 29% when using a nanofluid with 0.01 vol% GO concentration, at a Reynolds number of 5032. However, when the concentration of GO-DW was increased to 0.02 vol%, the enhancement in the convection heat transfer coefficient reached 48%. Once again, calculating the convective heat transfer based on the above correlations and utilizing the same exact parameters, yielded that the presence of nanoparticles adversely affected the heat transfer characteristics. For instance, the addition of 0.01% GO reduced the convective heat transfer by 5% and the addition of 0.02% reduced it by 4%. Table 3 shows a comparison between the obtained results from 9 and the calculated results.

Double pipe heat exchanger

Concentric tube heat exchangers are widely utilized across various applications, serving purposes such as air-conditioning, oil cooling, refrigeration, engine cooling, and material processing. As a result, concentric tube heat exchangers can be used in several industries, including chemical, refinery, and pharmaceutical industries. The widespread use of concentric tube heat exchangers is due to their low cost, high reliability 13 , simple design, and robust configuration 14 . A concentric tube heat exchanger generates a temperature gradient by employing various fluid streams at unique temperatures in parallel, divided by a pipe. This, in return, causes forced convection, resulting in heat transfer 15 . However, there are several disadvantages accompanied with concentric tube heat exchangers. For instance, a concentric tube heat exchanger can lose heat due to its large outer shells. As a result, various researchers attempted to enhance the heat transfer properties of a concentric heat exchanger via different methods such as induced surface vibrations, and air bubbles injection 16 , 17 . The most predominant method is by using nanofluids 18 .

Several researchers reported that the using nanofluids in concentric tube heat exchangers can enhance thermal conductivity, Nusselt number, and convective heat transfer properties of the nanofluid 19 , 20 , 21 . For instance, Akyürek et al. 22 investigated the heat transfer and pressure drop characteristics of Al 2 O 3 -Water nanofluids in a concentric tube heat exchanger with and without wire coil turbulators. The investigation showed that Nusselt number increased with an increase in the particle concentration and Reynolds number, leading to an enhancement in the heat transfer coefficient. The authors used Gnielinski’s equations for computing the Nu and friction factor to validate their experimental results. Equations ( 8 ) and ( 9 ) demonstrate Gnielinski’s equations for the Nusselt number and friction factor, respectively 23 . The reported Nusselt number associated with the 1.6% Al 2 O 3 -Water nanofluid at a Re number of 20,000 is between 350 and 400. However, based on the correlations presented in Eqs. ( 10 ) and ( 11 ), the calculated Nusselt number is approximately 170.93. This Nusselt number is computed based on friction factor of 0.0261, Re number of 20,000, volume fraction of 1.6%, and Pr of 10.07669. The Pr number is acquired based on Eq. ( 12 ). The significant difference between these Nusselt numbers suggests that the enhancement of the Nusselt number is far less than it is mentioned.

where Cp nf is the specific heat of the nanofluid, M nf is the viscosity of the nanofluid, and K nf is the thermal conductivity of the nanofluid.

In the same way, Sonawane et al. 18 investigated the heat transfer properties of Al 2 O 3 -Water nanofluids in a copper concentric tube heat exchanger. The authors compared the heat transfer of the nanofluid to the base fluid (water). The study showed that the nanofluids exhibited higher heat transfer rates as the concentration of the nanofluid increased. Nonetheless, the authors claimed that the Nusselt number of the nanofluid at 3% concentration is between 15 and 16; whereas, after calculating the Nusselt number by the correlation demonstrated in Eq. ( 6 ), the Nusselt number is around 26.16. The Nusselt number was computed after setting the Re number to 4000 and Pr value found to be around 4.061 and the friction factor is approximately 0.0414. Similarly, Khalifa and Banwan 24 studied the increase in the heat transfer rate after adding y -Al 2 O 3 nanoparticles to water in a concentric tube heat exchanger. The authors reported that the enhancement in the convective heat transfer increased as the nanoparticle volume fraction and flow rate increased. Furthermore, the authors attained a maximum enhancement of 20% in the Nusselt number and 22.8% in the heat transfer coefficient at 1% volume fraction and 6026 Re number. In order to validate the accuracy of the Nusselt number and heat transfer coefficient, the authors compared these values to the values estimated based on empirical correlations. The Dittus-Boelter correlation, as shown in Eq. ( 6 ), was employed to estimate the Nusselt number. The values from the experimental setup and from the Dittus-Boelter correlation were highly correlated. However, the Dittus-Boelter correlation is only used under the condition that the Re number is higher than 10,000. Nonetheless, the highest Re number in this study is 6026, indicating that this correlation might compute inaccurate results. Through this correlation, the Nusselt number at 1% volume fraction and at 6026 Re number is between 55 and 65. Nevertheless, the correlation presented in Eq. ( 10 ) showed a different Nusselt number from the one computed by the Dittus-Boelter correlation. The correlation showed that the Nusselt number is around 41.261, the friction factor is 0.0364, and the Pr number is 4.4071. The computed Nusselt number is much lower than that reported by the authors, suggesting a lower enhancement in the heat transfer coefficient.

Shell and tube heat exchangers

Due to its small size and high heat transfer rate, the shell and tube design is the most commonly employed design in heat exchangers. In general, to increase the heat transfer rate through heat exchangers, fluids with high heat transfer coefficients are used 25 . In this section, the heat transfer coefficient of shell and tube heat exchangers applying different nanofluids are investigated and compared with other correlations from literature. Said et al. 26 , examined the heat transfer characteristics of a CuO/water nanofluid mixture. The nanoparticle concentrations employed were 0.05, 0.1, and 0.3 vol%. Twenty eight carbon steel tubes and one carbon steel shell were used for the experimental setup. CuO/water was circulated within the heat exchanger's tube section. In addition to the experimental investigation, a theoretical model was created to verify the outcomes. The findings demonstrated that for the same fluid inlet temperatures and mass flow rates, the convective heat transfer coefficient obtained when using the proposed nanofluid is more than when using the basefluid. The heat transfer enhancement achieved was 7%. The input and output data were obtained and then validated as shown in Table 4 using the implemented correlation. Nusselt number was calculated using the correlation in Eq. ( 13 ) for concentrations up to 2 vol% and for turbulent flow:

where dp is the nanoparticle diameter (50 nm).

The heat transfer coefficient is then calculated based on the Nusselt number from Eq. ( 13 ):

The results were validated after getting close values of Nu and h to the values reported in the paper which are 18.9 and 2255.39 (W/m 2  K) respectively. Hence, proving the enhancement in the heat transfer coefficient compared to water with h value equal to 1998.47 W/m 2 K.

Similarly, Ghozatloo et al. 27 investigated the heat transfer coefficients of water-based graphene nanofluids in the point of entry as well as in laminar conditions using a shell and tube heat exchanger. A flowrate of 0.8 L/min was used for establishing the laminar flow. Based on their findings, introducing 0.075% graphene to the base fluid improved the thermal conductivity up to 31.83% at saturation concentrations of graphene and improved the heat transfer coefficient depending on the conditions of flow. At 38 °C, the convective heat transfer coefficient of graphene nanofluids increased by 35.6% in comparison with purified water using an amount of 0.1 wt%. In the conducted analysis, the local heat transfer coefficient was determined based on the fluid temperature in  x i  section ( T fi ) and test part inner wall temperature ( T wi ). Then, h was calculated from:

where q″ is the constant heat flux of 5429 W/m 2 . Then, the average heat transfer coefficient was calculated by taking the arithmetic mean of the obtained local heat transfer coefficients.

In our analysis, Shah’s correlation for laminar flow was used to validate the Nusselt number as shown in Eq. ( 15 ) 28 . It is also important to note that the analysis was conducted for the different volume concentration of graphene used.

where L is the length of the horizontal circular copper tube used.

Then, the heat transfer coefficient is calculated based on the Nusselt number from Eq. ( 13 ). In Table 5 , the average heat transfer coefficients, which depend on the average temperature, are shown which indicate notable variations. In the conducted analysis, by increasing the temperature and concentration of graphene nanoparticles, the average heat transfer coefficient increases. However, in the results obtained in Table 6 after calculation based on the correlations, a different trend is found where the heat transfer coefficient was increasing to the threshold of 0.048vol% in KRG-4 sample where it decreased. Table 6 shows the calculated heat transfer coefficient using water and nanofluids.

Farajollahi et al. 29 examined the heat transfer properties of γ-Al 2 O 3 /water and TiO 2 /water nanofluids in a shell and tube heat exchanger with turbulent flow conditions. The effects of Peclet number, volume concentration of suspended nanoparticles, and particle type on heat transfer were studied. Data related to the velocity and flow rates were missing, hence, the velocity was calculated based on the Peclet number as shown in Eq. ( 16 ) in order to obtain other parameters from Eqs. ( 3 ) and ( 13 ).

Furthermore, the viscosity of the nanofluid was calculated using Eq. ( 17 ):

where ϕ is the volume concentration of the nanoparticles.

The calculations were implemented using the different volume percentages of TiO 2 and using the obtained Peclet number. In their work, the correlation in Eq. ( 13 ) was used to calculate the Nu before determining the heat transfer coefficient. A significant difference is found between both results, using 0.15%, 0.3%, 0.5% and 0.75% of TiO 2, as shown in Fig.  4 .

Comparison between present work calculations of the heat transfer coefficient and Farajollahi et al. 29 .

Anitha et al. 30 reported the testing of three types of nanofluids, namely Al 2 O 3 -Cu-Water, Cu-Water, and Al 2 O 3 -Water for different volume concentrations of 1%, 2%, 4%, 8%, 10%, and 20%. According to the authors, the Reynold’s number that was used for the analysis was equal to 844.4, which falls into the laminar flow region.

For a circular tube, which is the case for the tube in a shell-and-tube heat exchanger, that harbors a laminar flow, the Nusselt number is independent of the Reynold’s and Prandtl numbers for a constant heat flux, bearing a constant value of 4.36 as shown in Eq. ( 5 ) 31 .

In their work, the authors calculated the heat transfer coefficient using Eq. ( 14 ):

With a diameter of 0.033 m, the only thing left that can have a significant impact on the heat transfer coefficient is the value of the thermal conductivity of each corresponding nanofluid, which does not change much with changing the concentration. The value of the heat transfer coefficient in the present work is calculated using the following equation:

However, there is barely any significant variation of the thermal conductivity values, that according to Eq. ( 18 ) ultimately dictate any changes in the values of the heat transfer coefficient. Which is why in this present work, the values of the heat transfer coefficient were recalculated using the aforementioned Nusselt correlation in Eq. ( 18 ).

The values presented by Anitha et al. are at least 10 times more than the values obtained through the suitable Nusselt correlation for laminar flow in circular tube with a constant heat flux. Figure  5 is a visual representation of that undeniable difference. The values calculated in the present work indicate that there is no enhancement in the heat transfer coefficient associated with the addition of nanoparticles, no matter the vol%, contrary to those shown by Anitha et al.

Comparison between heat transfer coefficient values recalculated in the present work and those found in Anitha et al. 30 .

In a similar work conducted by Kuman and Sonawane 32 , they tested the effect of enhancing the heat transfer coefficient by adding Fe 2 O 3 nanoparticles to water and ethylene glycol (EG), in the tube of a shell-and-tube heat exchanger. Throughout the conducted tests, they maintained the hot stream and two constant temperatures 50  \(^\circ\) C and 80  \(^\circ\) C, while ranging the vol% of the nanoparticles from 0.01 to 0.08. The reported thermal conductivity values ranged from 0.614 to 0.651 W/mK and 0.252 to 0.296 W/mK with changing the vol% from 0.01 to 0.08 for Fe 2 O 3 -water and EG, respectively. For a constant hot stream temperature operation, the Nusselt number is constant in the laminar flow region, similar to the case mentioned earlier, however having a different value as shown in Eq. ( 4 )

With a tube diameter of 0.0107 m, the heat transfer coefficient is only a function of the thermal conductivity and is obtained through the following equation.

However, the authors used Eq. ( 14 ) to obtain h, and then used those values of h to obtain values for Nu.

The base comparison between the present work and that conducted by Kumar and Sonawane will be confined to the laminar region of their reported work, which is presented in Fig.  6 . Moreover, throughout their tests, they did not exceed a Re of 10,000, all while using correlations for Nu comparison that are only valid at Re > 10,000, such as the Dittus-Boelter and the Gnielinksi correlation, which is invalid.

Comparison between heat transfer coefficient values recalculated in the present work and those found in Kumar and Sonawane 32 .

Challenges and limitations of nanofluids

Microstructure-imposed challenges.

There are various challenges that are imposed solely by the microstructure of nanoparticles which are revealed by an analysis of the existing scientific literature 33 . A common issue is regarding the uniform dispersion of nanoparticles within the base fluid. The use of Scanning Electron Microscopy (SEM) by researchers often reveals clumped regions of nanoparticles which raises concerns about the reliability and effectiveness of such mixtures and enhancements.

Figure  7 presents the current causes and challenges imposed by the microstructure of nanofluids.

Summary of microstructure issues in nanofluids.

Uniform dispersion of nanoparticles in a base fluid is a core condition for ensuring optimal heat transfer performance of nanofluids. Despite extensive efforts by researchers in the surveyed literature, achieving a homogeneous dispersion remains a significant challenge. This is traced back to various factors that collectively contribute to this phenomenon, including high surface energy of nanoparticles that lead to a natural tendency to form clusters and agglomerate. Strong forces such as Van Der Waals attractions, can, and in most cases do, overcome the repulsive forces between nanoparticles 34 . The formation of agglomerates can be seen in following works 35 , 36 , 37 , 38 , 39 . Because it is more economical and straightforward, producing nanofluid by dispersing nanoparticles in base fluid using the two-step method has become prevalent on a large scale, which ultimately affects the commercialization of nanofluids. The main disadvantage of this approach is agglomeration caused by Van Der Waals forces and the cohesive strength of the individual nanoparticles 40 . This continues to be a concern in the production and use of nanofluids because this behavior has an effect on the entire fluid stability. Fluid flow properties in porous media, such as viscosity, in addition to cooling applications, can be restricted by such agglomeration 41 . Sedimentation, abrasion and reduced nanofluid enhancement effects are the negative impacts that may occur as a result of agglomeration 42 .

Moreover, the interaction between the nanoparticles and the base fluid extremely influences the dispersion behavior. The addition of surface modifiers and surfactants is often done to improve the compatibility between the base fluid and nanoparticles 43 . However, despite these efforts, nanoparticles may still experience poor dispersion due to confined interactions with the base fluid, as can be seen in most published literature. Properties, such as the base fluid viscosity and surface tension, play a crucial role in governing these interactions and consequently the nanoparticles dispersion 44 and are claimed to have an effect on heat transfer. More importantly, the non-uniform dispersion of nanoparticles in base fluids poses significant challenges when attempting to elevate these nanofluids from waivered laboratory findings to real-world applications.

Commercialization and scaling-up challenges

There are two main challenges that hinder the commercialization and utilization of nanofluids in large-scale heat exchangers. First, potential adverse physical effects of the solid matter on the internal workings of candidate systems. Nanoparticles used in experiments in available literature are strikingly similar to materials that cause internal fouling of heat exchanger pipes. Given the uncertainty in calculating heat transfer enhancements achieved exclusively because of the addition of nanoparticles, as well as the significantly higher heat transfer enhancement that result from increasing the working fluid flow rate (at constant heat input), there is a lack of commercially available products on the market that utilize nanofluids. There have been 24 patents involving devices and technologies that employ nanofluids since 2001 45 from solar collectors to microchip cooling applications, which impose application-specific challenges, but so far there exists no market penetration for nanofluid based devices.

The second reason for product availability is the price of nanoparticles. The most effective nanoparticles reported in literature are either gold, diamond, or silver, which are estimated to cost around 80$/g, 35$/g, and 6$/g, respectively. The volume fraction of these particles and their non-recyclability preclude any enthusiasm in employing them on a wide scale. The high prices of nanofluids are due to numerous factors, involving material costs, preparation costs (which include reagent, surfactant, ultrasound bath, and stirrers), and labor costs. Also, the documented techniques for synthesis are frequently modified and differ from one application to another. As a result, there is inadequate knowledge and data to properly determine the price of nanofluids, which adds another obstacle 46 . Moreover, the stability of nanoparticles in nanofluids is a gray area in that specific field of research. Researchers apply what is known as the Zeta potential test in order to test for the stable dispersion of nanoparticles and their resistance to precipitation. However, practical long-term stability of nanofluids has yet to be tested. Additionally, long term effects of nanofluids, whether on human health or environmental toxicity, are still vague. Despite the proclaimed advancements in nanofluids research there have yet to be comprehensive studies regarding the long-term exposure and interactions of nanofluids within targeted systems. Furthermore, nanofluids should be assessed for their capability to retain their required characteristics over operating conditions (e.g., thermal conductivity following heating and cooling cycles). The development of nanofluids based on water with the required improved thermal and mechanical properties is still a challenge 42 . Due to that, there has yet to be a breakthrough in mainstream markets where most consumers reside. Solid work has to be laid out which harbors stability and efficiency, to convince industries and end consumers to adopt nanofluids as a replacement for well-established heat transfer fluid alternatives. A summary of the steps and measures required, as well as the challenges to be addressed for nanofluids' commercialization is shown in Fig.  8 .

Steps and measures for nanofluids commercialization.

This study presented an overview of the seemingly hot topic of nanofluid utilization for heat transfer enhancement. In particular, issues pertinent to a consensus-by-volition in calculating heat transfer coefficients, h, in nanofluids research. Many studies rely on simplistic equations, such as q/ \(\Delta\) T, which overshadows the undeniable complexity of convective heat transfer phenomena. Even in studies that utilize empirical formulae that involve the Nusselt number, Nu, many erroneous validation steps resulted from correlations made at invalid ranges of Reynolds numbers or depending solely on the minute changes in the thermal conductivity of the working fluid due to increased volume fraction (quantity) of nanofluid. Most of papers reporting on the latter have neatly plotted graphs due to said small changes in volume fraction that rarely relied on experimental rigor to determine the constants in the Nusselt equation. Furthermore, in laminar flow regimes, where Nu remains constant, it is essential to recognize that h is primarily a function of the thermal conductivity in that case, rather than Re, which does not significantly change with the addition of nanoparticles.

In its current form, the nanofluids research area requires a standard for independently evaluating the effect of nanoparticles addition to working fluids. The available results in literature indicate that increasing the flow rate within the heat exchanger could enhance the heat transfer at higher order of magnitudes compared to any enhancement gained from nanoparticle addition. And finally, the independence of the results is overshadowed with the specificity of the geographic region and repetition of certain lead figures in the field. A more critical and impartial standards must be set for a field that is growing as fast and vast as nanofluids.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Sajid, M. U. & Ali, H. M. Thermal conductivity of hybrid nanofluids: A critical review. Int. J. Heat Mass Transf. 126 , 211–234. https://doi.org/10.1016/j.ijheatmasstransfer.2018.05.021 (2018).

Article   CAS   Google Scholar  

Sajid, M. U. & Ali, H. M. Recent advances in application of nanofluids in heat transfer devices: A critical review. Renew. Sustain. Energy Rev. 103 , 556–592. https://doi.org/10.1016/j.rser.2018.12.057 (2019).

Chakraborty, S. & Panigrahi, P. K. Stability of nanofluid: A review. Appl. Therm. Eng. 174 , 115259. https://doi.org/10.1016/j.applthermaleng.2020.115259 (2020).

Vallejo, J. P., Prado, J. I. & Lugo, L. Hybrid or mono nanofluids for convective heat transfer applications. A critical review of experimental research. Appl. Therm. Eng. 203 , 117926. https://doi.org/10.1016/j.applthermaleng.2021.117926 (2022).

Colangelo, G., Diamante, N. F., Milanese, M., Starace, G. & de Risi, A. A critical review of experimental investigations about convective heat transfer characteristics of nanofluids under turbulent and laminar regimes with a focus on the experimental setup. Energies 14 (18), 6004. https://doi.org/10.3390/en14186004 (2021).

Yang, L. & Hu, Y. Toward TiO 2 nanofluids—part 1: Preparation and properties. Nanoscale Res. Lett. 12 , 417. https://doi.org/10.1186/s11671-017-2184-8 (2017).

Article   ADS   CAS   PubMed   PubMed Central   Google Scholar  

Fotukian, S. M. & Nasr Esfahany, M. Experimental study of turbulent convective heat transfer and pressure drop of dilute CuO/water nanofluid inside a circular tube. Int. Commun. Heat Mass Transf. 37 (2), 214–219. https://doi.org/10.1016/j.icheatmasstransfer.2009.10.003 (2010).

Zeinali Heris, S., Nasr Esfahany, M. & Etemad, S. G. Experimental investigation of convective heat transfer of Al 2 O 3 /water nanofluid in circular tube. Int. J. Heat Fluid Flow 28 (2), 203–210. https://doi.org/10.1016/j.ijheatfluidflow.2006.05.001 (2007).

Karabulut, K., Buyruk, E. & Kilinc, F. Experimental and numerical investigation of convection heat transfer in a circular copper tube using graphene oxide nanofluid. J. Braz. Soc. Mech. Sci. Eng. 42 (5), 1–16. https://doi.org/10.1007/s40430-020-02319-0 (2020).

Ali, H. M. In tube convection heat transfer enhancement: SiO 2 aqua based nanofluids. J. Mol. Liq. https://doi.org/10.1016/j.molliq.2020.113031 (2020).

Article   Google Scholar  

Bahiraei, M. A numerical study of heat transfer characteristics of CuO–water nanofluid by Euler-Lagrange approach. J. Therm. Anal. Calorim. 123 (2), 1591–1599. https://doi.org/10.1007/s10973-015-5031-0 (2016).

Bianco, V., Manca, O. & Nardini, S. Performance analysis of turbulent convection heat transfer of Al 2 O 3 water-nanofluid in circular tubes at constant wall temperature. Energy 77 , 403–413. https://doi.org/10.1016/j.energy.2014.09.025 (2014).

Khedkar, R. S., Sonawane, S. S. & Wasewar, K. L. Water to nanofluids heat transfer in concentric tube heat exchanger: Experimental study. Procedia Eng. 51 , 318–323. https://doi.org/10.1016/j.proeng.2013.01.043 (2013).

Shah, R. K., Subbarao, E. C. & Mashelkar, R. A. Heat Transfer Equipment Design (CRC Press, 1988).

Google Scholar  

Naterer, G. F. Heat Transfer in Single and Multiphase Systems (CRC Press, 2002).

Book   Google Scholar  

Setareh, M., Saffar-Avval, M. & Abdullah, A. Experimental and numerical study on heat transfer enhancement using ultrasonic vibration in a double-pipe heat exchanger. Appl. Therm. Eng. 159 , 113867 (2019).

Pourhedayat, S., Sadighi Dizaji, H. & Jafarmadar, S. Thermal-exergetic behavior of a vertical double-tube heat exchanger with bubble injection. Exp. Heat Transf. 32 (5), 455–468 (2019).

Article   ADS   CAS   Google Scholar  

Sonawane, S. S., Khedkar, R. S. & Wasewar, K. L. Study on concentric tube heat exchanger heat transfer performance using Al 2 O 3 –water based nanofluids. Int. Commun. Heat Mass Transf. 49 , 60–68. https://doi.org/10.1016/j.icheatmasstransfer.2013.10.001 (2013).

Khedkar, R. S., Sonawane, S. S. & Wasewar, K. L. Heat transfer study on concentric tube heat exchanger using TiO 2 –water based nanofluid. Int. Commun. Heat Mass Transf. 57 , 163–169. https://doi.org/10.1016/j.icheatmasstransfer.2014.07.011 (2014).

Wen, D. & Ding, Y. Experimental investigation into convective heat transfer of nanofluids at the entrance region under laminar flow conditions. Int. J. Heat Mass Transf. 47 (24), 5181–5188 (2004).

Qasim, M., Kamran, M. S., Ammar, M., Jamal, M. A. & Javaid, M. Y. Heat transfer enhancement of an automobile engine radiator using ZnO water base nanofluids. J. Therm. Sci. 29 (4), 1010–1024 (2020).

Akyürek, E. F., Geliş, K., Şahin, B. & Manay, E. Experimental analysis for heat transfer of nanofluid with wire coil turbulators in a concentric tube heat exchanger. Results Phys. 9 , 376–389. https://doi.org/10.1016/j.rinp.2018.02.067 (2018).

Article   ADS   Google Scholar  

Gnielinski, V. New equations for heat and mass transfer in turbulent pipe and channel flow. Int. Chem. Eng. 16 (2), 359–368 (1976).

Khalifa, A. J. N. & Banwan, M. A. Effect of volume fraction of γ-Al 2 O 3 nanofluid on heat transfer enhancement in a concentric tube heat exchanger. Heat Transf. Eng. 36 (16), 1387–1396 (2015).

Gupta, S. K., Verma, H. & Yadav, N. A review on recent development of nanofluid utilization in shell & tube heat exchanger for saving of energy. Mater. Today Proc. 54 (3), 579–589. https://doi.org/10.1016/j.matpr.2021.09.455 (2022).

Said, Z., Rahman, S. M. A., El Haj Assad, M. & Alami, A. H. Heat transfer enhancement and life cycle analysis of a Shell-and-Tube Heat Exchanger using stable CuO/water nanofluid. Sustain. Energy Technol. Assess. 31 , 306–317. https://doi.org/10.1016/j.seta.2018.12.020 (2019).

Ghozatloo, A., Rashidi, A. & Shariaty-Niassar, M. Convective heat transfer enhancement of graphene nanofluids in shell and tube heat exchanger. Exp. Therm. Fluid Sci. 53 , 136–141. https://doi.org/10.1016/j.expthermflusci.2013.11.018 (2014).

Prończuk, M. & Krzanowska, A. Experimental investigation of the heat transfer and pressure drop inside tubes and the shell of a minichannel shell and tube type heat exchanger. Energies 14 , 8563. https://doi.org/10.3390/en14248563 (2021).

Farajollahi, B., Etemad, S. G. & Hojjat, M. Heat transfer of nanofluids in a shell and tube heat exchanger. Int. J. Heat Mass Transf. 53 (1–3), 12–17. https://doi.org/10.1016/j.ijheatmasstransfer.2009.10.019 (2010).

Article   CAS   MATH   Google Scholar  

Anitha, S., Thomas, T., Parthiban, V. & Pichumani, M. What dominates heat transfer performance of hybrid nanofluid in single pass shell and tube heat exchanger?. Adv. Powder Technol. 30 (12), 3107–3117. https://doi.org/10.1016/j.apt.2019.09.018 (2019).

“Laminar vs. Turbulent-Nusselt Number|Correlations|nuclear-power.com.” https://www.nuclear-power.com/nuclear-engineering/heat-transfer/convection-convective-heat-transfer/laminar-vs-turbulent-nusselt-number/ (Accessed 27 May 2023).

Kumar, N. & Sonawane, S. S. Experimental study of Fe 2 O 3 /water and Fe 2 O 3 /ethylene glycol nanofluid heat transfer enhancement in a shell and tube heat exchanger. Int. Commun. Heat Mass Transf. 78 , 277–284. https://doi.org/10.1016/j.icheatmasstransfer.2016.09.009 (2016).

Bahiraei, M., Monavari, A. & Moayedi, H. Second law assessment of nanofluid flow in a channel fitted with conical ribs for utilization in solar thermal applications: Effect of nanoparticle shape. Int. J. Heat Mass Transf. 151 , 119387. https://doi.org/10.1016/j.ijheatmasstransfer.2020.119387 (2020).

Esquivel-Sirvent, R. Finite-size effects of Casimir–van der Waals forces in the self-assembly of nanoparticles. Physics 5 (1), 322–330. https://doi.org/10.3390/physics5010024 (2023).

Sreehari, S., Joseph, A. & Thomas, S. Development of a low cost nanofluid based direct absorption solar collector. Mater. Today Proc. 22 , 2424–2430. https://doi.org/10.1016/j.matpr.2020.03.368 (2020).

Talebizadehsardari, P., Shahsavar, A., Toghraie, D. & Barnoon, P. An experimental investigation for study the rheological behavior of water–carbon nanotube/magnetite nanofluid subjected to a magnetic field. Phys. A Stat. Mech. Appl. 534 , 122129. https://doi.org/10.1016/j.physa.2019.122129 (2019).

Singh, V., Gupta, M. & Kumar, A. Investigating the morphology and thermophysical properties of Al 2 O 3 and CuO nanofluids. IOP Conf. Ser. Mater. Sci. Eng. 577 (1), 012052. https://doi.org/10.1088/1757-899X/577/1/012052 (2019).

Kumar, R. S. & Sharma, T. Stable SiO 2 –TiO 2 composite-based nanofluid of improved rheological behaviour for high-temperature oilfield applications. Geosyst. Eng. 23 (1), 51–61. https://doi.org/10.1080/12269328.2020.1713909 (2020).

Nallusamy, S. Thermal conductivity analysis and characterization of copper oxide nanofluids through different techniques. J. Nano Res. 40 , 105–112. https://doi.org/10.4028/www.scientific.net/JNanoR.40.105 (2016).

Jen Wai, O., Gunnasegaran, P. & Hasini, H. Effect of hybrid nanofluids concentration and swirling flow on jet impingement cooling. Nanomaterials 12 (19), 3258. https://doi.org/10.3390/nano12193258 (2022).

Article   CAS   PubMed   PubMed Central   Google Scholar  

Nwidee, L. N., Barifcani, A., Sarmadivaleh, M. & Iglauer, S. Nanofluids as novel alternative smart fluids for reservoir wettability alteration. In Novel Nanomaterials—Synthesis and Applications . https://doi.org/10.5772/intechopen.72267 .

ChavezPanduro, E. A., Finotti, F., Largiller, G. & Lervåg, K. Y. A review of the use of nanofluids as heat-transfer fluids in parabolic-trough collectors. Appl. Therm. Eng. 211 , 118346. https://doi.org/10.1016/j.applthermaleng.2022.118346 (2022).

Yu, F. et al. Dispersion stability of thermal nanofluids. Prog. Nat. Sci. Mater. Int. 27 (5), 531–542. https://doi.org/10.1016/j.pnsc.2017.08.010 (2017).

Ahammed, N., Asirvatham, L. G. & Wongwises, S. Effect of volume concentration and temperature on viscosity and surface tension of graphene–water nanofluid for heat transfer applications. J. Therm. Anal. Calorim. 123 (2), 1399–1409. https://doi.org/10.1007/s10973-015-5034-x (2016).

Cheng, L. Nanofluid Heat Transfer Technologies (2009).

Alagumalai, A. et al. Conceptual analysis framework development to understand barriers of nanofluid commercialization. Nano Energy 92 , 106736. https://doi.org/10.1016/j.nanoen.2021.106736 (2022).

Download references

Author information

Authors and affiliations.

Sustainable and Renewable Energy Engineering Department, University of Sharjah, P.O. Box 27272, Sharjah, United Arab Emirates

Abdul Hai Alami, Muhammad Tawalbeh, Shamma Al Abdulla, Mohamad Ayoub, Mohammad Ali Abdelkareem & Abdul Ghani Olabi

Sustainable Energy & Power Systems Research Centre, RISE, University of Sharjah, P.O. Box 27272, Sharjah, United Arab Emirates

Abdul Hai Alami, Muhammad Tawalbeh, Salah Haridy, Haya Aljaghoub, Mohamad Ayoub, Mohammad Ali Abdelkareem & Abdul Ghani Olabi

School of Engineering, Lebanese International University LIU, Mazraa, P.O. Box: 146404, Beirut, Lebanon

Mohamad Ramadan

School of Engineering, International University of Beirut BIU, Mazraa, P.O. Box: 146404, Beirut, Lebanon

Industrial Engineering and Engineering Management Department, University of Sharjah, P.O. Box 27272, Sharjah, United Arab Emirates

Salah Haridy & Haya Aljaghoub

Benha Faculty of Engineering, Benha University, P.O. Box 13511, Benha, Egypt

Salah Haridy

Materials Science and Engineering PhD Program, American University of Sharjah, P.O. Box 26666, Sharjah, United Arab Emirates

Adnan Alashkar

You can also search for this author in PubMed   Google Scholar

Contributions

Conceptualization, A.H.A., methodology, A.H.A.; M.T.; M.R.; M.A.; A.Y. and A.A., formal analysis, A.H.A.; M.A.; A.Y.; A.A.; H.A. and S.A.A. investigation, S.H.; A.H.A.; M.A.; A.Y. and A.A.; resources,A.H.A., data curation, A.H.A.; M.A.; A.Y.; H.A; S.A.A.; and A.A., writing—original A.H.A.; M.A.; A.Y.; H.A.; S.A.A. and A.A.; draft preparation, A.H.A.; M.A.; A.Y.; A.A.; H.A., M.A.A.; A.G.O. and S.A.A.

Corresponding author

Correspondence to Abdul Hai Alami .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

Alami, A.H., Ramadan, M., Tawalbeh, M. et al. A critical insight on nanofluids for heat transfer enhancement. Sci Rep 13 , 15303 (2023). https://doi.org/10.1038/s41598-023-42489-0

Download citation

Received : 19 June 2023

Accepted : 11 September 2023

Published : 15 September 2023

DOI : https://doi.org/10.1038/s41598-023-42489-0

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

By submitting a comment you agree to abide by our Terms and Community Guidelines . If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Information

• Author Services

Initiatives

You are accessing a machine-readable page. In order to be human-readable, please install an RSS reader.

All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess .

Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications.

Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive positive feedback from the reviewers.

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

Original Submission Date Received: .

• Active Journals
• Find a Journal
• Proceedings Series
• For Authors
• For Reviewers
• For Editors
• For Librarians
• For Publishers
• For Societies
• For Conference Organizers
• Open Access Policy
• Institutional Open Access Program
• Special Issues Guidelines
• Editorial Process
• Research and Publication Ethics
• Article Processing Charges
• Testimonials
• Preprints.org
• SciProfiles
• Encyclopedia

Article Menu

• Subscribe SciFeed
• Recommended Articles
• PubMed/Medline
• Google Scholar
• on Google Scholar
• Table of Contents

Find support for a specific problem in the support section of our website.

Please let us know what you think of our products and services.

Visit our dedicated information section to learn more about MDPI.

JSmol Viewer

A review of nanofluids as coolants for thermal management systems in fuel cell vehicles.

1. Introduction

1.1. nanofluid overview, 1.2. nanofluid application in different types of vehicles, 1.2.1. nanofluid application in oil-fueled vehicles.

• Nanofluid application in oil-fueled vehicles’ cooling systems
• Nanofluid applications in oil-fueled vehicles’ air conditioner systems
• Nanofluid applications in oil-fueled vehicles’ lubrication systems
• Nanofluid applications in oil-fueled vehicles’ exhaust power generation systems

1.2.2. Nanofluid Application in Electric Vehicles

1.2.3. nanofluid application in fuel cell vehicles, 2. nanofluid application in thermal management systems of fuel cell vehicles, 2.1. thermal management system structure, 2.2. cooling performance improvement of thermal management system, 2.2.1. heat-production components.

• Cooling techniques for fuel cells
• Cooling techniques for batteries
• Cooling techniques for other components

2.2.2. Heat-Dissipation Components

3. nanofluids as coolants in fuel cell vehicles, 3.1. nanofluid thermophysical properties, 3.2. nanofluid thermal conductivity model, 3.3. single and hybrid nanofluids, 4. the challenges of nanofluid application in fuel cell vehicles, 4.1. nanofluid stability and cleaning.

• Nanofluid stability
• Nanofluid cleaning

4.2. Nanofluids in the Cooling Process

4.2.1. nanofluid erosion and abrasion of the microchannel surface, 4.2.2. pump transport power, 4.2.3. nanofluid electrical conductivity, 5. research directions for nanofluids in the future, 5.1. nanofluid stability improvement, 5.2. hybrid nanofluid application, 5.3. reduction in erosion and abrasion by nanofluids, 5.4. thermal conductivity model of nanofluids, 5.5. electrical conductivity of nanofluids, 6. conclusions, author contributions, data availability statement, conflicts of interest, nomenclature.

• Choi, S.U.S. A new field of scientific research and innovative applications. Heat Transf. Eng. 2008 , 29 , 429–431. [ Google Scholar ] [ CrossRef ]
• Frank, M.; Papanikoulaou, M.; Drikakis, D.; Salonitis, K. Heat transfer across a fractal surface. J. Chem. Phys. 2019 , 151 , 134705. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Frank, M.; Drikakis, D. Solid-like heat transfer in confined liquids. Microfluid. Nanofluidics 2017 , 21 , 148. [ Google Scholar ] [ CrossRef ]
• Ghorbanian, J.; Beskok, A. Scale effects in nano-channel liquid flows. Microfluid. Nanofluidics 2016 , 20 , 121. [ Google Scholar ] [ CrossRef ]
• Papanikolaou, M.; Frank, M.; Drikakis, D. Nanoflow over a fractal structure. Phys. Fluids 2016 , 28 , 082001. [ Google Scholar ] [ CrossRef ]
• Liu, Y.C.; Wang, Q.; Li, Z.; Tao, W. Dynamics and density profile of water in nanotubes as one-dimensional fluid. Langmuir 2005 , 21 , 12025–12030. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• McGaughey, A.J.H.; Kaviany, M. Thermal conductivity decomposition and analysis using molecular dynamics simulations Part II. Complex silica structures. Int. J. Heat Mass Transf. 2004 , 47 , 1799–1816. [ Google Scholar ] [ CrossRef ]
• Sun, G.X.; Bonaccurso, E.; Franz, V.; Butt, H.J. Confined liquid: Simultaneous observation of a molecularly layered structure and hydrodynamic slip. J. Chem. Phys. 2002 , 117 , 10311. [ Google Scholar ] [ CrossRef ]
• Jafari, S.M.; Jabari, S.S.; Dehnad, D.; Shahidi, S.A. Heat transfer enhancement in thermal processing of tomato juice by application of nanofluids. Food Bioprocess Technol. 2017 , 10 , 307–316. [ Google Scholar ] [ CrossRef ]
• Jafari, S.M.; Saramnejad, F.; Dehnad, D. Designing and application of a shell and tube heat exchanger for nanofluid thermal processing of liquid food products. J. Food Process Eng. 2018 , 41 , e12658. [ Google Scholar ] [ CrossRef ]
• Jafari, S.M.; Jabari, S.S.; Dehnad, D.; Shahidi, S.A. Effects of thermal processing by nanofluids on Vitamin C, total phenolics and total soluble solids of tomato juice. J. Food Sci. Technol.-Mysore 2017 , 54 , 679–686. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Salari, S.; Jafari, S.M. Application of nanofluids for thermal processing of food products. Trends Food Sci. Technol. 2020 , 97 , 100–113. [ Google Scholar ] [ CrossRef ]
• Tarafdar, P.; Sirohi, R.; Negi, T.; Singh, S.; Badgujar, P.C.; Shahi, N.C.; Kumar, S.; Sim, S.J.; Pandey, A. Nanofluid research advances: Preparation, characteristics, and applications in food processing. Food Res. Int. 2021 , 150 , 110751. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Zhao, M.N.; Yang, X.Y.; Feng, J.; Li, Y.; Dong, H.L.; Ren, J.; Xia, X.F. Research progress on the application of nanofluid in liquid food sterilization and its action mechanism. Sci. Technol. Food Ind. 2022 , 43 , 481–487. [ Google Scholar ]
• Xiong, Q.G.; Altnji, S.; Tayebi, T.; Izadi, M.; Hajjar, A.; Sunden, B.; Li, L.K.B. A comprehensive review on the application of hybrid nanofluids in solar energy collectors. Sustain. Energy Technol. Assess. 2021 , 47 , 101341. [ Google Scholar ] [ CrossRef ]
• Khanafer, K.; Vafai, K. A review on the applications of nanofluids in solar energy field. Renew. Energy 2018 , 123 , 398–406. [ Google Scholar ] [ CrossRef ]
• Panduro, E.A.C.; Finotti, F.; Largiller, G.; Lervag, K.Y. A review of the use of nanofluids as heat-transfer fluids in parabolic-trough collectors. Appl. Therm. Eng. 2022 , 211 , 118346. [ Google Scholar ] [ CrossRef ]
• Cui, F.Y.; Liu, F.H.; Tong, Y.J.; Wang, S.F.; Guo, W.G.; Han, T.L. Energy and exergy assessment of evacuated tube solar collector using water, Fe 3 O 4 nanofluid and Fe 3 O 4 /MWCNT hybrid nanofluid. Process Saf. Environ. Prot. 2023 , 163 , 236–243. [ Google Scholar ] [ CrossRef ]
• Tong, Y.J.; Lee, H.; Kang, W.; Cho, H.H. Energy and exergy comparison of a flat-plate solar collector using water, Al 2 O 3 nanofluid, and CuO nanofluid. Appl. Therm. Eng. 2019 , 159 , 113959. [ Google Scholar ] [ CrossRef ]
• Tong, Y.J.; Chi, X.N.; Kang, W.; Cho, H.H. Comparative investigation of efficiency sensitivity in a flat plate solar collector according to nanofluids. Appl. Therm. Eng. 2020 , 174 , 115346. [ Google Scholar ] [ CrossRef ]
• Hamzat, A.K.; Omisanya, M.I.; Sahin, A.Z.; Oyetunji, O.R.; Olaitan, N.A. Application of nanofluid in solar energy harvesting devices: A comprehensive review. Energy Convers. Manag. 2022 , 266 , 115790. [ Google Scholar ] [ CrossRef ]
• Sattar, A.; Farooq, M.; Amjad, M.; Saeed, M.A.; Nawaz, S.; Mujtaba, M.A.; Mujtaba, S.; El-Sherbeeny, A.M.; Soudagar, M.E.M.; Filho, E.P.B.; et al. Performance evaluation of a direct absorption collector for solar thermal energy conversion. Energies 2020 , 13 , 4956. [ Google Scholar ] [ CrossRef ]
• Chinchole, A.S.; Dasgupta, A.; Kulkarni, P.P.; Chandraker, D.K.; Nayak, A.K. Exploring the use of alumina nanofluid as emergency coolant for nuclear fuel bundle. J. Therm. Sci. Eng. Appl. 2019 , 11 , 021007. [ Google Scholar ] [ CrossRef ]
• Rahnama, Z.; Ansarifar, G.R. Predicting and optimizing the thermal-hydraulic, natural circulation, and neutronics parameters in the NuScale nuclear reactor using nanofluid as a coolant via machine learning methods through GA, PSO and HPSOGA algorithms. Ann. Nucl. Energy 2021 , 161 , 108375. [ Google Scholar ] [ CrossRef ]
• Kouloulias, K.; Sergis, A.; Hardalupas, Y.; Barrett, T.R. Visualisation of subcooled pool boiling in nanofluids. Fusion Eng. Des. 2019 , 146 , 153–156. [ Google Scholar ] [ CrossRef ]
• Hadad, K.; Kowsar, Z. Twofold application of nanofluids as the primary coolant and reactivity controller in a PWR reactor: Case study VVER-1000 in normal operation. Ann. Nucl. Energy 2016 , 97 , 179–182. [ Google Scholar ] [ CrossRef ]
• Kang, M.; Jee, C.; Park, S.; Bang, I.C.; Heo, G. Design process of the nanofluid injection mechanism in nuclear power plants. Nanoscale Res. Lett. 2011 , 6 , 363. [ Google Scholar ] [ CrossRef ]
• Ghorbanali, Z.; Talebi, S. Investigation of a nanofluid-based natural circulation loop. Prog. Nucl. Energy 2020 , 129 , 103494. [ Google Scholar ] [ CrossRef ]
• Ghazanfari, R.; Talebi, M.; Khorsandi, J.; Abdolahi, R. Effects of water based Al 2 O 3 , TiO 2 , and CuO nanofluids as the coolant on solid and annular fuels for a typical VVER-1000 core. Prog. Nucl. Energy 2016 , 91 , 285–294. [ Google Scholar ] [ CrossRef ]
• Bafrani, H.A.; Noori-kalkhoran, O.; Gei, M.; Ahangari, R.; Mirzaee, M.M. On the use of boundary conditions and thermophysical properties of nanoparticles for application of nanofluids as coolant in nuclear power plants; a numerical study. Prog. Nucl. Energy 2020 , 126 , 103417. [ Google Scholar ] [ CrossRef ]
• Khuwaileh, B.A.; Al-Hamadi, F.I.; Hartanto, D.; Said, Z.; Ali, M. On the performance of nanofluids in APR 1400 PLUS7 assembly: Neutronics. Ann. Nucl. Energy 2020 , 144 , 107508. [ Google Scholar ] [ CrossRef ]
• Nematolahi, M.; Behzadinejad, B.; Golestani, A. Feasibility study of using nanofluids as a neutron absorber in reactor emergency core cooling system. Int. J. Hydrogen Energy 2015 , 40 , 15192–15197. [ Google Scholar ] [ CrossRef ]
• Bang, I.A.; Kim, J.H.F. Thermal-fluid characterizations of ZnO and SiC nanofluids for advanced nuclear power plants. Nucl. Technol. 2017 , 170 , 16–27. [ Google Scholar ] [ CrossRef ]
• Saadati, H.; Hadad, K.A.; Rabiee, A. Safety margin and fuel cycle period enhancements of VVER-1000 nuclear reactor using water/silver nanofluid. Nucl. Eng. Technol. 2018 , 50 , 639–647. [ Google Scholar ] [ CrossRef ]
• Wang, Y.; Wu, J.A. Single bubble dynamic behavior in Al 2 O 3 /H 2 O nanofluid on downward-facing heating surface. Nucl. Eng. Technol. 2016 , 48 , 915–924. [ Google Scholar ] [ CrossRef ]
• El-Masry, J.F.; Bou-Hamdan, K.F.; Abbas, A.H.; Martyushev, D.A. A comprehensive review on utilizing nanomaterials in enhanced oil recovery applications. Energies 2023 , 16 , 691. [ Google Scholar ] [ CrossRef ]
• Zhao, M.W.; Lv, W.J.; Li, Y.Y.; Dai, C.L.; Wang, X.K.; Zhou, H.D.; Zou, C.W.; Gao, M.W.; Zhang, Y.; Wu, Y.N. Study on the synergy between silica nanoparticles and surfactants for enhanced oil recovery during spontaneous imbibition. J. Mol. Liq. 2018 , 261 , 373–378. [ Google Scholar ] [ CrossRef ]
• Zhao, M.W.; Song, X.G.; Lv, W.J.; Wu, Y.N.; Dai, C.L. The preparation and spontaneous imbibition of carbon-based nanofluid for enhanced oil recovery in tight reservoirs. J. Mol. Liq. 2020 , 313 , 113564. [ Google Scholar ] [ CrossRef ]
• Cao, J.; Chen, Y.P.; Zhang, J.; Wang, X.J.; Wang, J.; Shi, C.X.; Ning, Y.F.; Wang, X.M. Preparation and application of nanofluid flooding based on polyoxyethylated graphene oxide nanosheets for enhanced oil recovery. Chem. Eng. Sci. 2021 , 247 , 117023. [ Google Scholar ] [ CrossRef ]
• Cao, J.; Chen, Y.P.; Xu, G.R.; Wang, X.L.; Li, Y.; Zhao, S.; Liu, C.L.; Wang, X.M. Study on interface regulation effects of Janus nanofluid for enhanced oil recovery. Colloids Surf. A Physicochem. Eng. Asp. 2022 , 653 , 129880. [ Google Scholar ] [ CrossRef ]
• Alsedrani, M.Q.; Chala, G.T. Investigation of the effects of silica nanofluid for enhanced oil recovery applications: CFD Simulation Study. Arab. J. Sci. Eng. 2022 , 48 , 9139–9158. [ Google Scholar ] [ CrossRef ]
• Liu, R.; Lu, J.Y.; Pu, W.F.; Xie, Q.; Lu, Y.Y.; Du, D.J.; Yang, X.R. Synergetic effect between in-situ mobility control and micro-displacement for chemical enhanced oil recovery (CEOR) of a surface-active nanofluid. J. Pet. Sci. Eng. 2021 , 205 , 108983. [ Google Scholar ] [ CrossRef ]
• Maaref, S.; Kantzas, A.; Bryant, S.L. The effect of water alternating solvent based nanofluid flooding on heavy oil recovery in oil-wet porous media. Fuel 2020 , 282 , 118808. [ Google Scholar ] [ CrossRef ]
• Soleimani, H.; Baig, M.K.; Yahya, N.; Khodapanah, L.; Sabet, M.; Demiral, B.M.R.; Burda, M. Impact of carbon nanotubes based nanofluid on oil recovery efficiency using core flooding. Results Phys. 2018 , 9 , 39–48. [ Google Scholar ] [ CrossRef ]
• Amani, H. Synergistic effect of biosurfactant and nanoparticle mixture on microbial enhanced oil recovery. J. Surfactants Deterg. 2017 , 20 , 589–597. [ Google Scholar ] [ CrossRef ]
• Kumar, R.S.; Ganat, T.A.; Sharma, T. Performance evaluation of silica nanofluid for sand column transport with simultaneous wettability alteration: An approach to environmental issue. J. Clean. Prod. 2021 , 303 , 127047. [ Google Scholar ] [ CrossRef ]
• Jafarbeigi, E.; Kamari, E.; Salimi, F.; Mohammadidoust, A. Experimental study of the effects of a novel nanoparticle on enhanced oil recovery in carbonate porous media. J. Pet. Sci. Eng. 2021 , 195 , 107602. [ Google Scholar ] [ CrossRef ]
• Cao, J.; Chen, Y.P.; Wang, X.J.; Zhang, J.; Li, Y.; Hua, Z.; Wang, X.M.; Zhao, S. Low-salinity nanofluid–A smart fluid enhanced oil recovery method. Colloids Surf. A Physicochem. Eng. Asp. 2022 , 648 , 129204. [ Google Scholar ] [ CrossRef ]
• Bai, Y.; Pu, C.S.; Li, X.; Huang, F.F.; Liu, S.; Liang, L.; Liu, J. Performance evaluation and mechanism study of a functionalized silica nanofluid for enhanced oil recovery in carbonate reservoirs. Colloids Surf. A Physicochem. Eng. Asp. 2022 , 652 , 129939. [ Google Scholar ] [ CrossRef ]
• Alomair, O.A.; Alajmi, A.F. A novel experimental nanofluid-assisted steam flooding (NASF) approach for enhanced heavy oil recovery. Fuels 2022 , 313 , 122691. [ Google Scholar ] [ CrossRef ]
• Al-Yaari, A.; Ching, D.L.C.; Sakidin, H.; Muthuvalu, M.S.; Zafar, M.; Alyousifi, Y.; Saeed, A.A.H.; Bilad, M.R. Thermophysical properties of nanofluid in two-phase fluid flow through a porous rectangular medium for enhanced oil recovery. Nanomaterials 2022 , 12 , 1011. [ Google Scholar ] [ CrossRef ]
• Mock, J. Fuel Cell Coolant Optimization and Scale Up ; Dynalene Inc.: Whitehall, PA, USA, 2011. [ Google Scholar ]
• Yaw, C.T.; Koh, S.P.; Sandhya, M.; Kadirgama, K.; Tiong, S.K.; Ramasamy, D.; Sudhakar, K.; Samykano, M.; Benedict, F.; Tan, C.H. Heat transfer enhancement by hybrid nano additives-graphene nanoplate-lets/cellulose nanocrystal for the automobile cooling system (Radiator). Nanomaterials 2023 , 13 , 808. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Ahmed, S.A.; Ozkaymak, M.; Sözen, A.; Menlik, T.; Fahed, A. Improving car radiator performance by using TiO 2 -water nanofluid. Eng. Sci. Technol. Int. J. 2018 , 21 , 996–1005. [ Google Scholar ] [ CrossRef ]
• Elibol, E.A.; Turgut, O.; Aktas, F.; Senol, H.; Celik, A.F. Experimental investigation on heat transfer and flow characteristics of TiO 2 -water nanofluid in a heavy vehicle radiator. J. Therm. Anal. Calorim. 2023 , 148 , 977–994. [ Google Scholar ] [ CrossRef ]
• Said, Z.; Assad, M.E.H.; Hachicha, A.A.; Bellos, E.; Abdelkareem, M.A.; Alazaizeh, D.Z.; Yousef, B.A.A. Enhancing the performance of automotive radiators using nanofluids. Renew. Sustain. Energy Rev. 2019 , 112 , 183–194. [ Google Scholar ] [ CrossRef ]
• Elibol, E.A.; Turgut, O. Heat transfer and fluid flow characteristics in a long offset strip fin channel by using TiO 2 -Water nanofluid. Arab. J. Sci. Eng. 2022 , 47 , 15415–15428. [ Google Scholar ] [ CrossRef ]
• Palaniappan, B.; Ramasamy, V. Thermodynamic analysis of fly ash nanofluid for automobile (heavy vehicle) radiators. J. Therm. Anal. Calorim. 2019 , 136 , 223–233. [ Google Scholar ] [ CrossRef ]
• Yasuri, A.K.; Soleimani, E. An experimental study on the simultaneous effect of nanofluid and tube insert on the thermal performance of an automobile cooling system. J. Appl. Fluid Mech. 2021 , 14 , 1559–1566. [ Google Scholar ]
• Sandhya, D.; Reddy, M.C.S.; Rao, V.V. Improving the cooling performance of automobile radiator with ethylene glycol water based TiO 2 nanofluids. Int. Commun. Heat Mass Transf. 2016 , 78 , 121–126. [ Google Scholar ]
• Ali, M.; El-Leathy, A.M.; Al-Sofyany, Z. The effect of nanofluid concentration on the cooling system of vehicles radiator. Adv. Mech. Eng. 2014 , 6 , 962510. [ Google Scholar ] [ CrossRef ]
• Sokhal, G.S.; Gangacharyulu, D.; Bulasara, V.K. Influence of copper oxide nanoparticles on the thermophysical properties and performance of flat tube of vehicle cooling system. Vacuum 2018 , 157 , 268–276. [ Google Scholar ] [ CrossRef ]
• Kumar, V.; Sahoo, R.R. Exergy and energy performance for wavy fin radiator with a new coolant of various shape nanoparticle-based hybrid nanofluids. J. Therm. Anal. Calorim. 2020 , 143 , 3911–3922. [ Google Scholar ] [ CrossRef ]
• Goudarzi, K.; Jamali, H. Heat transfer enhancement of Al 2 O 3 -EG nanofluid in a car radiator with wire coil inserts. Appl. Therm. Eng. 2017 , 118 , 510–517. [ Google Scholar ] [ CrossRef ]
• Sheikhzadeh, G.A.; Fakhari, M.M.; Khorasanizadeh, H. Experimental investigation of laminar convection heat transfer of Al 2 O 3 -ethylene glycol-water nanofluid as a coolant in a car radiator. J. Appl. Fluid Mech. 2017 , 10 , 209–219. [ Google Scholar ] [ CrossRef ]
• Hussein, A.M.; Baker, R.A.; Kadirgama, K.; Sharma, K.V. Heat transfer enhancement using nanofluids in an automotive cooling system. Int. Commun. Heat Mass Transf. 2014 , 53 , 195–202. [ Google Scholar ] [ CrossRef ]
• Heris, S.Z.; Shokrgozar, S.; Poorpharhang, S.; Shanbedi, M.; Noie, S.H. Experimental study of heat transfer of a car radiator with CuO/ethylene glycol-water as a coolant. J. Dispers. Sci. Technol. 2014 , 35 , 677–684. [ Google Scholar ] [ CrossRef ]
• Kumar, A.; Chand, P.; Hassan, M.A. Louvered finned car radiator with MWCNT-SiO 2 hybrid nanofluid: An experimental approach. Powder Technol. 2023 , 415 , 118176. [ Google Scholar ] [ CrossRef ]
• Naraki, M.; Peyghambarzadeh, S.M.; Hashemabadi, S.H.; Vermahmoudi, Y. Parametric study of overall heat transfer coefficient of CuO/water nanofluids in a car radiator. Int. J. Therm. Sci. 2013 , 66 , 82–90. [ Google Scholar ] [ CrossRef ]
• Seraj, M.; Yahya, S.M.; Badruddin, I.A.; Anqi, A.E.; Asjad, M.; Khan, Z.A. Multi-response optimization of nanofluid-based I. C. engine cooling system using fuzzy PIV method. Processes 2020 , 8 , 30. [ Google Scholar ] [ CrossRef ]
• Sonage, B.K.; Mohanan, P. Miniaturization of automobile radiator by using zinc-water and zinc oxide-water nanofluids. J. Mech. Sci. Technol. 2021 , 29 , 2177–2185. [ Google Scholar ] [ CrossRef ]
• Sahoo, R.R. Effect of various shape and nanoparticle concentration based ternary hybrid nanofluid coolant on the thermal performance for automotive radiator. Heat Mass Transf. 2021 , 57 , 873–887. [ Google Scholar ] [ CrossRef ]
• Sahoo, R.R. Thermo-hydraulic characteristics of radiator with various shape nanoparticle-based ternary hybrid nanofluid. Powder Technol. 2020 , 370 , 18–28. [ Google Scholar ] [ CrossRef ]
• Vajjha, R.S.; Das, D.K.; Namburu, P.K. Numerical study of fluid dynamic and heat transfer performance of Al 2 O 3 and CuO nanofluids in the flat tubes of a radiator. Int. J. Heat Fluid Flow 2010 , 31 , 613–621. [ Google Scholar ] [ CrossRef ]
• Shankara, R.P.; Banapurmath, N.R.; D’Souza, A.; Sajjan, A.M.; Ayachit, N.H.; Khan, T.M.Y.; Badruddin, I.A.; Kamangar, S. An insight into the performance of radiator system using ethylene glycol-water based graphene oxide. Alex. Eng. J. 2022 , 61 , 5155–5167. [ Google Scholar ] [ CrossRef ]
• Peyghambarzadeh, S.M.; Hashemabadi, S.H.; Hoseini, S.M.; Jamnani, M.S. Experimental study of heat transfer enhancement using water/ethylene glycol based nanofluids as a new coolant for car radiators. Int. Commun. Heat Mass Transf. 2011 , 38 , 1283–1290. [ Google Scholar ] [ CrossRef ]
• Hussein, A.M.; Dawood, H.K.; Bakara, R.A.; Kadirgamaa, K. Numerical study on turbulent forced convective heat transfer using nanofluids TiO 2 in an automotive cooling system. Case Stud. Therm. Eng. 2017 , 9 , 72–78. [ Google Scholar ] [ CrossRef ]
• Elsebay, M.; Elbadawy, I.; Shedid, M.H.; Fatouh, M. Numerical resizing study of Al 2 O 3 and CuO nanofluids in the flat tubes of a radiator. Appl. Math. Model. 2016 , 40 , 6437–6450. [ Google Scholar ] [ CrossRef ]
• Akash, A.R.; Pattamatta, A.; Das, S.K. Experimental study of the thermohydraulic performance of water/ethylene glycol-based graphite nano-coolant in vehicle radiators. J. Enhanc. Heat Transf. 2019 , 26 , 345–363. [ Google Scholar ] [ CrossRef ]
• Leong, K.Y.; Saidur, R.; Kazi, S.N.; Mamun, A.H. Performance investigation of an automotive car radiator operated with nanofluid-based coolants (nanofluid as a coolant in a radiator). Appl. Therm. Eng. 2010 , 30 , 2685–2692. [ Google Scholar ] [ CrossRef ]
• Karagoz, Y.; Koten, H.; Tuncer, E.; Pusat, S. Effect of Al 2 O 3 addition to an internal combustion engine coolant on heat transfer performance. Case Stud. Therm. Eng. 2022 , 31 , 101847. [ Google Scholar ] [ CrossRef ]
• Peyghambarzadeh, S.M.; Hashemabadi, S.H.; Jamnani, M.S.; Hoseini, S.M. Improving the cooling performance of automobile radiator with Al 2 O 3 /water nanofluid. Appl. Therm. Eng. 2011 , 31 , 1833–1838. [ Google Scholar ] [ CrossRef ]
• Selvam, C.; Lal, D.M.; Harish, S. Enhanced heat transfer performance of an automobile radiator with graphene-based suspensions. Appl. Therm. Eng. 2017 , 123 , 50–60. [ Google Scholar ] [ CrossRef ]
• Yildiz, C.; Kaptan, C.; Arci, M.; Baynal, K. Taguchi optimization of automotive radiator cooling with nanofluids. Eur. Phys. J.-Spec. Top. 2022 , 231 , 2801–2819. [ Google Scholar ] [ CrossRef ]
• Elias, M.M.; Mahbubul, I.M.; Saidur, R.; Sohel, M.R.; Shahrul, I.M.; Khaleduzzaman, S.S.; Sadeghipour, S. Experimental investigation on the thermo-physical properties of Al 2 O 3 nanoparticles suspended in car radiator coolant. Int. Commun. Heat Mass Transf. 2014 , 54 , 48–53. [ Google Scholar ] [ CrossRef ]
• Hussein, A.M.; Bakar, R.A.; Kadirgama, K.; Sharma, K.V. Heat transfer augmentation of a car radiator using nanofluids. Heat Mass Transf. 2014 , 50 , 1553–1561. [ Google Scholar ] [ CrossRef ]
• Mousavi, H.; Ghomshe, S.M.T.; Rashidi, A.; Mirzaei, M. Hybrids carbon quantum dots as new nanofluids for heat transfer enhancement in wet cooling towers. Heat Mass Transf. 2021 , 58 , 309–320. [ Google Scholar ] [ CrossRef ]
• Shah, T.R.; Ali, H.M.; Janjua, M.M. On aqua-based Silica (SiO 2 –Water) nano-coolant: Convective thermal potential and experimental precision evaluation in Aluminum tube radiator. Nanomaterials 2020 , 10 , 1736. [ Google Scholar ] [ CrossRef ]
• Peyghambarzadeh, S.M.; Hashemabadi, S.H.; Naraki, M.; Vermahmoudi, Y. Experimental study of overall heat transfer coefficient in the application of dilute nanofluids in the car radiator. Appl. Therm. Eng. 2013 , 52 , 8–16. [ Google Scholar ] [ CrossRef ]
• Tafakhori, M.; Kalantari, D.; Biparva, P.; Peyghambarzadeh, S.M. Assessment of Fe 3 O 4 -water nanofluid for enhancing laminar convective heat trans-fer in a car radiator. J. Therm. Anal. Calorim. 2021 , 146 , 841–853. [ Google Scholar ] [ CrossRef ]
• Subhedar, D.G.; Ramani, B.M.; Gupta, A. Experimental investigation of heat transfer potential of Al 2 O 3 /Water-Mono Ethylene Glycol nanofluids as a car radiator coolant. Case Stud. Therm. Eng. 2018 , 11 , 26–34. [ Google Scholar ] [ CrossRef ]
• Contreras, E.M.C.; Filho, E.P.B. Heat transfer performance of an automotive radiator with MWCNT nanofluid cooling in a high operating temperature range. Appl. Therm. Eng. 2022 , 207 , 118149. [ Google Scholar ] [ CrossRef ]
• Khan, M.S.; Dil, T. Heat transfer enhancement of automobile radiator using H 2 O-CuO nanofluid. AIP Adv. 2017 , 7 , 045018. [ Google Scholar ] [ CrossRef ]
• Delavari, V.; Hashemabadi, S.H. CFD simulation of heat transfer enhancement Al 2 O 3 /water and Al 2 O 3 /ethylene glycol nanofluids in a car radiator. Appl. Therm. Eng. 2015 , 73 , 380–390. [ Google Scholar ] [ CrossRef ]
• Sahoo, R.R.; Sarkar, J. Heat transfer performance characteristics of hybrid nanofluids as coolant in louvered fin automotive radiator. Heat Mass Transf. 2017 , 53 , 1923–1931. [ Google Scholar ] [ CrossRef ]
• Li, X.K.; Zou, C.J.; Qi, A. Experimental study on the thermo-physical properties of car engine coolant (water/ethylene glycol mixture type) based SiC nanofluids. Int. Commun. Heat Mass Transf. 2016 , 77 , 159–164. [ Google Scholar ] [ CrossRef ]
• Sivalingam, V.; Kumar, P.G.; Prabakaran, R.; Sun, J.; Velraj, R.; Kim, S.C. An automotive radiator with multi-walled carbon-based nanofluids: A study on heat transfer optimization using MCDM techniques. Case Stud. Therm. Eng. 2022 , 29 , 101724. [ Google Scholar ] [ CrossRef ]
• Mhamed, B.; Sidik, N.A.C.; Akhbar, M.F.A.; Mamat, R.; Najafi, G. Experimental study on thermal performance of MWCNT nano-coolant in Perodua Kelisa 1000cc radiator system. Int. Commun. Heat Mass Transf. 2016 , 76 , 156–161. [ Google Scholar ] [ CrossRef ]
• Khan, A.; Ali, H.M.; Nazir, R.; Ali, R.; Munir, A.; Ahmad, B.; Ahmad, Z. Experimental investigation of enhanced heat transfer of a car radiator using ZnO nanoparticles in H 2 O–ethylene glycol mixture. J. Therm. Anal. Calorim. 2019 , 138 , 3007–3021. [ Google Scholar ] [ CrossRef ]
• Xian, H.W.; Sidik, N.A.C.; Najafi, G. Recent state of nanofluid in automobile cooling systems. J. Therm. Anal. Calorim. 2019 , 135 , 981–1008. [ Google Scholar ] [ CrossRef ]
• Arora, N.; Gupta, M. An updated review on application of nanofluids in flat tubes radiators for improving cooling performance. Renew. Sustain. Energy Rev. 2020 , 134 , 110242. [ Google Scholar ] [ CrossRef ]
• Sidik, N.A.C.; Yazid, M.N.A.W.M.; Mamat, R. A review on the application of nanofluids in vehicle engine cooling system. Int. Commun. Heat Mass Transf. 2015 , 68 , 85–90. [ Google Scholar ] [ CrossRef ]
• Sidik, N.A.C.; Yazid, M.N.A.W.M.; Mamat, R. Recent advancement of nanofluids in engine cooling system. Renew. Sustain. Energy Rev. 2017 , 75 , 137–144. [ Google Scholar ] [ CrossRef ]
• Abbas, F.; Ali, H.M.; Shah, T.R.; Babar, H.; Janjua, M.M.; Sajjad, U.; Amer, M. Nanofluid: Potential evaluation in automotive radiator. J. Mol. Liq. 2020 , 297 , 112014. [ Google Scholar ] [ CrossRef ]
• Zhao, N.B.; Li, S.Y.; Yang, J.L. A review on nanofluids: Data-driven modeling of thermophysical properties and the application in automotive radiator. Renew. Sustain. Energy Rev. 2016 , 66 , 596–616. [ Google Scholar ] [ CrossRef ]
• Bigdeli, M.B.; Fasano, M.; Cardellini, A.; Chiavazzo, E.; Asinari, P. A review on the heat and mass transfer phenomena in nanofluid coolants with special focus on automotive applications. Renew. Sustain. Energy Rev. 2016 , 60 , 1615–1633. [ Google Scholar ] [ CrossRef ]
• Almurtaji, S.; Ali, N.; Teixeira, J.A.; Addali, A. On the role of nanofluids in thermal-hydraulic performance of heat exchangers—A review. Nanomaterials 2020 , 10 , 734. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Sharif, M.Z.; Azmi, W.H.; Redhwan, A.A.M.; Mamat, R.; Yusof, T.M. Performance analysis of SiO 2 /PAG nano lubricant in automotive air conditioning system. Int. J. Refrig. 2017 , 75 , 204–216. [ Google Scholar ] [ CrossRef ]
• Redhwan, A.A.M.; Azmi, W.H.; Sharif, M.Z.; Mamat, R.; Zawawi, N.N.M. Comparative study of thermo-physical properties of SiO 2 and Al 2 O 3 nanoparticles dispersed in PAG lubricant. Appl. Therm. Eng. 2017 , 116 , 823–832. [ Google Scholar ] [ CrossRef ]
• Zawawi, N.N.M.; Azmi, W.H.; Ghazali, M.F. Performance of Al 2 O 3 -SiO 2 /PAG composite nano lubricants in automotive air-conditioning system. Appl. Therm. Eng. 2022 , 204 , 117998. [ Google Scholar ] [ CrossRef ]
• Ali, M.K.A.; Hou, X.J. Improving the heat transfer capability and thermal stability of vehicle engine oils using Al 2 O 3 /TiO 2 nanomaterials. Powder Technol. 2020 , 363 , 48–58. [ Google Scholar ] [ CrossRef ]
• Lue, Y.F.; Hung, Y.H.; Li, F.S.; Teng, T.P.; Chen, S.Y.; Wu, C.H.; Ou, Y.C. Performance assessment and scooter verification of nano-Alumina engine oil. Appl. Sci. 2016 , 6 , 258. [ Google Scholar ] [ CrossRef ]
• Esfe, M.H.; Arani, A.A.A.; Esfandeh, S. Improving engine oil lubrication in light-duty vehicles by using of dispersing MWCNT and ZnO nanoparticles in 5W50 as viscosity index improvers (VII). Appl. Therm. Eng. 2018 , 143 , 493–506. [ Google Scholar ] [ CrossRef ]
• Hilmin, M.N.H.M.; Remeli, M.F.; Singh, B.; Affandi, N.D.N. Thermoelectric power generations from vehicle exhaust gas with TiO 2 nanofluid cooling. Therm. Sci. Eng. Prog. 2021 , 18 , 100558. [ Google Scholar ] [ CrossRef ]
• Karana, D.R.; Sahoo, R.R. Effect on TEG performance for waste heat recovery of automobiles using MgO and ZnO nanofluid coolants. Case Stud. Therm. Eng. 2019 , 12 , 358–364. [ Google Scholar ] [ CrossRef ]
• Chen, M.; Li, J.J. Experimental study on heating performance of pure electric vehicle power battery under low temperature environment. Int. J. Heat Mass Transf. 2021 , 172 , 121191. [ Google Scholar ] [ CrossRef ]
• Wu, F.C.; Rao, Z.H. The lattice Boltzmann investigation of natural convection for nanofluid based battery thermal management. Appl. Therm. Eng. 2017 , 115 , 659–669. [ Google Scholar ] [ CrossRef ]
• Abdelkareem, M.A.; Maghrabie, H.M.; Abo-Khalil, A.G.; Adhari, O.H.K.; Sayed, E.T.; Radwan, A.; Elsaid, K.; Wilberforce, T.; Olabi, A.G. Battery thermal management systems based on nanofluids for electric vehicles. J. Energy Storage 2022 , 50 , 104385. [ Google Scholar ] [ CrossRef ]
• Guo, H.Z.; Li, J.; Zhu, Z.Y.; Lv, P.H. Numerical investigation on thermal performance of battery module with LCP-AFC cooling system applied in electric vehicle. Energy Sci. Eng. 2022 , 10 , 4431–4446. [ Google Scholar ] [ CrossRef ]
• Kiani, M.; Ansari, M.; Arshadi, A.A.; Houshfar, E.; Ashjaee, M. Hybrid thermal management of lithium-ion batteries using nanofluid, metal foam, and phase change material: An integrated numerical–experimental approach. J. Therm. Anal. Calorim. 2020 , 141 , 1703–1715. [ Google Scholar ] [ CrossRef ]
• Liao, G.L.; Wang, W.D.; Zhang, F.; E, J.Q.; Chen, J.W.; Leng, E.W. Thermal performance of lithium-ion battery thermal management system based on nanofluid. Appl. Therm. Eng. 2022 , 216 , 118997. [ Google Scholar ] [ CrossRef ]
• Faizan, M.; Pati, S.; Randive, P. Implications of novel cold plate design with hybrid cooling on thermal management of fast discharging lithium-ion battery. J. Energy Storage 2022 , 53 , 105051. [ Google Scholar ] [ CrossRef ]
• Chen, M.; Li, J.J. Nanofluid-based pulsating heat pipe for thermal management of lithium-ion batteries for electric vehicles. J. Energy Storage 2021 , 32 , 101715. [ Google Scholar ] [ CrossRef ]
• Rahmani, E.; Fattahi, A.; Panahi, E.; Mahmoudi, Y. Thermal management improvement for a pack of cylindrical batteries using nanofluids and topological modifications. J. Power Sources 2023 , 564 , 232876. [ Google Scholar ] [ CrossRef ]
• Sirikasemsuk, S.; Naphon, N.; Eiamsa-ard, S.; Naphon, P. Analysis of nanofluid flow and heat transfer behavior of Li-ion battery modules. Int. J. Heat Mass Transf. 2023 , 208 , 124058. [ Google Scholar ] [ CrossRef ]
• Li, Y.; Xie, H.Q.; Yu, W.; Li, J. Liquid cooling of tractive lithium-ion batteries pack with nanofluids coolant. J. Nanosci. Nanotechnol. 2015 , 15 , 3206–3211. [ Google Scholar ] [ CrossRef ]
• Huo, Y.T.; Rao, Z.H. The numerical investigation of nanofluid based cylinder battery thermal management using lattice Boltzmann method. Int. J. Heat Mass Transf. 2015 , 91 , 374–384. [ Google Scholar ] [ CrossRef ]
• Zhou, Z.C.; Lv, Y.J.; Qu, J.; Sun, Q.; Grachev, D. Performance evaluation of hybrid oscillating heat pipe with carbon nanotube nanofluids for electric vehicle battery cooling. Appl. Therm. Eng. 2021 , 196 , 117300. [ Google Scholar ] [ CrossRef ]
• Deng, Y.W.; Feng, C.L.; E, J.Q.; Zhu, H.; Chen, J.W.; Wen, M.; Yin, H.C. Effects of different coolants and cooling strategies on the cooling performance of the power lithium-ion battery system: A review. Appl. Therm. Eng. 2018 , 142 , 10–29. [ Google Scholar ] [ CrossRef ]
• Lv, W.J.; Li, J.J.; Chen, M. Experimental study on the thermal management performance of a power battery module with a pulsating heat pipe under different thermal management strategies. Appl. Therm. Eng. 2023 , 227 , 120402. [ Google Scholar ] [ CrossRef ]
• Bargal, M.H.S.; Abdelkareem, M.A.A.; Tao, Q.; Li, J.; Shi, J.P.; Wang, Y.P. Liquid cooling techniques in proton exchange membrane fuel cell stacks: A detailed survey. Alex. Eng. J. 2020 , 59 , 635–655. [ Google Scholar ] [ CrossRef ]
• Islam, M.R.; Shabani, B.; Rosengarten, G.; Andrews, J. The potential of using nanofluids in PEM fuel cell cooling systems: A review. Renew. Sustain. Energy Rev. 2015 , 48 , 523–539. [ Google Scholar ] [ CrossRef ]
• Islam, M.R.; Shabani, B.; Andrews, J.; Rosengarten, G. Experimental investigation of using ZnO nanofluids as coolants in a PEM fuel cell. Int. J. Hydrogen Energy 2017 , 42 , 19272–19286. [ Google Scholar ] [ CrossRef ]
• Islam, M.R.; Shabani, B.; Rosengarten, G. Electrical and thermal conductivities of 50/50 water-ethylene glycol based TiO 2 nanofluids to be used as coolants in PEM fuel cells. Energy Procedia 2017 , 110 , 101–108. [ Google Scholar ] [ CrossRef ]
• Zakaria, I.; Mohamed, W.A.N.W.; Mamat, A.M.I.B.; Saidur, R.; Azmi, W.H.; Mamat, R.; Talib, S.F.A. Experimental investigation of Al 2 O 3 -water ethylene glycol mixture nanofluid thermal behaviour in a single cooling plate for PEM fuel cell application. Energy Procedia 2015 , 79 , 252–258. [ Google Scholar ] [ CrossRef ]
• Zakaria, I.; Azmi, W.H.; Mamat, A.M.I.B.; Mamat, R.; Saidur, R.; Talib, S.F.A.; Mohamed, W.A.N.W. Thermal analysis of Al 2 O 3 -water ethylene glycol mixture nanofluid for single PEM fuel cell cooling plate: An experimental study. Int. J. Hydrogen Energy 2016 , 41 , 5096–5112. [ Google Scholar ] [ CrossRef ]
• Zakaria, I.; Azmi, W.H.; Mamat, A.M.I.B.; Saidur, R.; Azmi, W.H.; Mamat, R.; Talib, S.F.A. Experimental investigation of thermal conductivity and electrical conductivity of experimental investigation of thermal conductivity and electrical conductivity of fuel cell application. Int. Commun. Heat Mass Transf. 2015 , 61 , 61–68. [ Google Scholar ] [ CrossRef ]
• Ilhan, B.; Kurt, M.; Ertürk, H. Experimental investigation of heat transfer enhancement and viscosity change of hBN nanofluids. Exp. Therm. Fluid Sci. 2016 , 77 , 272–283. [ Google Scholar ] [ CrossRef ]
• Zhou, S. Modeling and Simulation Technology of Fuel Cell Vehicle ; Beijing Institute of Technology Press: Beijing, China, 2017. [ Google Scholar ]
• Zhang, G.S.; Kandlikar, S.G. A critical review of cooling techniques in proton exchange membrane fuel cell stacks. Int. J. Hydrogen Energy 2012 , 37 , 2412–2429. [ Google Scholar ] [ CrossRef ]
• Ghasemi, M.; Ramiar, A.; Ranjbar, A.A.; Rahgoshay, S.M. A numerical study on thermal analysis and cooling flow fields effect on PEMFC performance. Int. J. Hydrogen Energy 2017 , 42 , 24319–24337. [ Google Scholar ] [ CrossRef ]
• Mahdavi, A.; Ranjbar, A.; Gorji, M.; Rahimi-Esbo, M. Numerical simulation-based design for an innovative PEMFC cooling flow field with metallic bipolar plates. Appl. Energy 2018 , 228 , 656–666. [ Google Scholar ] [ CrossRef ]
• Afshari, E.; Ziaei-Rad, M.; Dehkordi, M.M. Numerical investigation on a novel zigzag-shaped flow channel design for cooling plates of PEM fuel cells. J. Energy Institue 2016 , 90 , 752–763. [ Google Scholar ] [ CrossRef ]
• Hwan, J.J. Thermal control and performance assessment of a proton exchanger membrane fuel cell generator. Appl. Energy 2013 , 108 , 184–193. [ Google Scholar ] [ CrossRef ]
• Han, J.; Park, J.; Yu, S. Control strategy of cooling system for the optimization of parasitic power of automotive fuel cell system. Int. J. Hydrogen Energy 2015 , 40 , 13549–13557. [ Google Scholar ] [ CrossRef ]
• Park, H. A design of air flow configuration for cooling lithium-ion battery in hybrid electric vehicles. J. Power Sources 2013 , 239 , 404–414. [ Google Scholar ] [ CrossRef ]
• Mohammadian, S.K.; Zhang, Y. Thermal management optimization of an air-cooled Li-ion battery module using pin-fin heat sinks for hybrid electric vehicles. J. Power Sources 2015 , 273 , 431–439. [ Google Scholar ] [ CrossRef ]
• Yang, N.; Zhang, X.; Li, G.J.; Hua, D. Assessment of the forced air-cooling performance for cylindrical lithium-ion battery packs: A comparative analysis between aligned and staggered cell arrangements. Appl. Therm. Eng. 2015 , 80 , 55–65. [ Google Scholar ] [ CrossRef ]
• Tong, W.; Somasundaram, K.; Birgersson, E.; Mujumdar, A.S.; Yap, C. Thermo-electrochemical model for forced convection air cooling of a lithium-ion battery module. Appl. Therm. Eng. 2016 , 99 , 672–682. [ Google Scholar ] [ CrossRef ]
• Siruvuri, S.D.V.S.S.; Budarapu, P.R. Studies on thermal management of Lithium-ion battery pack using water as the cooling fluid. J. Energy Storage 2020 , 29 , 354–363. [ Google Scholar ] [ CrossRef ]
• Habibian, S.H.; Abolmaali, A.M.; Afshin, H. Numerical investigation of the effects of fin shape, antifreeze, and nanoparticles on the performance of compact finned-tube heat exchangers automobile Radiator. Appl. Therm. Eng. 2018 , 133 , 248–260. [ Google Scholar ] [ CrossRef ]
• Gonga, C.Y.; Shen, J.; Yu, Y.; Wang, K.A.; Tu, Z.K. A novel radiator structure for enhanced heat transfer in PEM fuel cell vehicle. Int. J. Heat Mass Transf. 2020 , 157 , 119926. [ Google Scholar ] [ CrossRef ]
• Mao, S.L.; Cheng, C.R.; Li, X.C.; Michaelides, E.E. Thermal/structural analysis of radiators for heavy-duty trucks. Appl. Therm. Eng. 2010 , 30 , 1438–1446. [ Google Scholar ] [ CrossRef ]
• Oliet, C.; Oliva, A.; Castro, J.; Pérez-Segarra, C.D. Parametric studies on automotive radiators. Appl. Therm. Eng. 2007 , 27 , 2033–2043. [ Google Scholar ] [ CrossRef ]
• Vaisi, A.; Esmaeilpour, M.; Taherian, H. Experimental investigation of geometry effects on the performance of a compact louvered heat exchanger. Appl. Therm. Eng. 2011 , 31 , 3337–3346. [ Google Scholar ] [ CrossRef ]
• Mahmoudi, J. Modeling of flow field and heat transfer in a copper-base automotive radiator application. Int. J. Green Energy 2016 , 3 , 25–41. [ Google Scholar ] [ CrossRef ]
• Bhattarai, S.; Ghimire, S.K. Computational fluid dynamics-based performance evaluation louvered fin radiator. In Proceedings of the International Conference on Software, Knowledge, Information Management & Applications, Malabe, Sri Lanka, 6–8 December 2017. [ Google Scholar ]
• Plesa, A.; Giurgiu, O.; Banyai, D. Auto radiators-study regarding air flow along the channels. Energy Procedia 2016 , 85 , 390–398. [ Google Scholar ] [ CrossRef ]
• Okbaz, A.; Pnarba, A.; Olcay, A.B.; Aksoy, M.H. An experimental, computational and flow visualization study on the air-side thermal and hydraulic performance of louvered fin and round tube heat exchangers. Int. J. Heat Mass Transf. 2018 , 121 , 153–169. [ Google Scholar ] [ CrossRef ]
• Kim, N.H. An experimental investigation on the airside performance of fin and tube heat exchangers having corrugated louver fins. J. Therm. Sci. Technol. 2020 , 15 , 19–617. [ Google Scholar ]
• Han, H.; He, Y.L.; Li, Y.S.; Wang, Y.; Wu, M. A numerical study on compact enhanced fin and tube heat exchangers with oval and circular tube configurations. Int. J. Heat Mass Transf. 2013 , 65 , 686–695. [ Google Scholar ] [ CrossRef ]
• Li, J.; Wang, S.; Wang, C.; Zhang, W. Numerical study on air-side performance of an integrated fin and micro-channel heat exchanger. Appl. Therm. Eng. 2010 , 30 , 2738–2745. [ Google Scholar ] [ CrossRef ]
• Karthik, P.; Kumaresan, V.; Velraj, R. Experimental and parametric studies of a louvered fin and flat tube compact heat exchanger using computational fluid dynamics. Alex. Eng. J. 2015 , 54 , 905–915. [ Google Scholar ] [ CrossRef ]
• Dogan, S.; Darici, S.; Ozgoren, M. Numerical comparison of thermal and hydraulic Performances for heat exchangers having circular and elliptic cross-section. Int. J. Heat Mass Transf. 2019 , 145 , 118731. [ Google Scholar ] [ CrossRef ]
• Lotfi, B.; Sunden, B.; Wang, Q. An investigation of the thermos-hydraulic performance of smooth wavy fin and elliptical tube heat exchangers utilizing new type vortex generators. Appl. Energy 2015 , 162 , 1282–1302. [ Google Scholar ] [ CrossRef ]
• Wu, X.H.; Zhang, W.; Guo, Q.; Luo, Z.; Lu, Y. Numerical simulation of heat transfer and fluid flow characteristics of composite fin. Int. J. Heat Mass Transf. 2014 , 75 , 414–424. [ Google Scholar ] [ CrossRef ]
• Zhao, L.P.; Gu, X.T.; Gao, L.; Yang, Z.G. Numerical study on airside thermal-hydraulic performance of rectangular finned elliptical tube heat exchanger with large row number in turbulent flow regime. Int. J. Heat Mass Transf. 2017 , 114 , 1314–1330. [ Google Scholar ] [ CrossRef ]
• Liu, J.W.; Long, H.F.; Xi, Z.M.; Xu, J.H.; He, K.X. Simulation analysis of new energy vehicle cooling fans aerodynamic performance based on CFD. Veh. Power Technol. 2020 , 2 , 31–35. [ Google Scholar ]
• Maxwell, J.C. A Treatise on Electricity and Magnetism ; Clarendon Press: Oxford, UK, 1873. [ Google Scholar ]
• Mehta, S.; Chauhan, K.P.; Kanagaraj, S. Modeling of thermal conductivity of nanofluids modifying Maxwell’s equation using model approach. J. Nanoparticle Res. 2011 , 13 , 2791–2798. [ Google Scholar ] [ CrossRef ]
• Hamilton, R.L.; Crosser, O.K. Thermal conductivity of heterogeneous two-component systems. Ind. Eng. Chem. Res. Fundam. 1962 , 1 , 187–191. [ Google Scholar ] [ CrossRef ]
• Yamada, E.; Ota, T. Effective thermal conductivity of dispersed materials. Heat Mass Transf. 1980 , 13 , 27–37. [ Google Scholar ] [ CrossRef ]
• Davis, R. The effective thermal conductivity of composite material spherical inclusions. Int. J. Thermophys. 1986 , 7 , 609–620. [ Google Scholar ] [ CrossRef ]
• Jiang, H.F. Mathematical Model and Medium-High Temperature Experimental Research of Nanofluid Effective Thermal Conductivity ; Tsinghua University: Beijing, China, 2015. [ Google Scholar ]
• Huang, D.; Wu, Z.; Sunden, B. Effects of hybrid nanofluid mixture in plate heat exchangers. Exp. Therm. Fluid Sci. 2016 , 72 , 190–196. [ Google Scholar ] [ CrossRef ]
• Arif, M.; Kuman, P.; Kuman, W.; Mostafa, Z. Heat transfer analysis of radiator using different shaped nanoparticles water-based ternary hybrid nanofluid with applications: A fractional model. Case Stud. Therm. Eng. 2022 , 31 , 101837. [ Google Scholar ] [ CrossRef ]
• Tlili, I. Impact of thermal conductivity on the thermophysical properties and rheological behavior of nanofluid and hybrid nanofluid. Math. Sci. 2021 . Available online: https://link.springer.com/article/10.1007/s40096-021-00377-6 (accessed on 14 October 2023). [ CrossRef ]
• Devi, S.P.A.; Devi, S.S.U. Numerical investigation of hydromagnetic hybrid Cu-Al 2 O 3 /Water nanofluid flow over a permeable stretching sheet with suction. Int. J. Nonlinear Sci. Numer. Simul. 2016 , 17 , 249–257. [ Google Scholar ] [ CrossRef ]
• Johari, M.N.I.; Zakaria, I.A.; Azmi, W.H.; Mohamed, W.A.N.W. Green-bio glycol Al 2 O 3 -SiO 2 hybrid nanofluids for PEMFC: The thermal-electrical-hydraulic perspectives. Int. Commun. Heat Mass Transf. 2022 , 131 , 105870. [ Google Scholar ] [ CrossRef ]
• Khalid, S.; Zakaria, I.A.; Azmi, W.H.; Mohamed, W.A.N.W. Thermal-electrical-hydraulic properties of Al 2 O 3 -SiO 2 hybrid nanofluids for advanced PEM fuel cell thermal management. J. Therm. Anal. Calorim. 2021 , 143 , 1555–1567. [ Google Scholar ] [ CrossRef ]
• Vinoth, R.; Sachuthananthan, B.; Vadivel, A.; Balakrishnan, S.; Raj, A.G.S. Heat transfer enhancement in oblique finned curved microchannel using hybrid nanofluid. Int. J. Therm. Sci. 2022 , 183 , 107848. [ Google Scholar ] [ CrossRef ]
• Siddiqui, F.R.; Tso, C.Y.; Qiu, H.H.; Chao, C.Y.H.; Fu, S.C. Hybrid nanofluid spray cooling performance and its residue surface effects: Toward thermal management of high heat flux devices. Appl. Therm. Eng. 2022 , 211 , 118454. [ Google Scholar ] [ CrossRef ]
• Nasir, S.; Sirisubtawee, S.; Juntharee, P.; Berrouk, A.S.; Mukhtar, S.; Gul, T. Heat transport study of ternary hybrid nanofluid flow under magnetic dipole together with nonlinear thermal radiation. Appl. Nanosci. 2022 , 12 , 2777–2788. [ Google Scholar ] [ CrossRef ]
• Babar, H.; Ali, H.M. Towards hybrid nanofluids: Preparation, thermophysical properties, applications, and challenges. J. Mol. Liq. 2019 , 281 , 598–633. [ Google Scholar ] [ CrossRef ]
• Xian, H.W.; Sidik, N.A.C.; Saidur, R. Hybrid nano coolant for enhanced heat transfer performance in vehicle cooling system. Int. Commun. Heat Mass Transf. 2022 , 133 , 105922. [ Google Scholar ] [ CrossRef ]
• Chakraborty, S.; Panigrahi, P.K. Stability of nanofluid: A review. Appl. Therm. Eng. 2020 , 174 , 115259. [ Google Scholar ] [ CrossRef ]
• Yu, J.; Grossiord, N.; Koning, C.E.; Loos, J. Controlling the dispersion of multi-wall carbon nanotubes in aqueous surfactant solution. Carbon 2007 , 45 , 618–623. [ Google Scholar ] [ CrossRef ]
• Islam, M.F.; Rojas, E.; Bergey, D.M.; Johnson, A.T.; Yodh, A.G. High weight fraction surfactant solubilization of single-wall carbon nanotubes in water. Nano Lett. 2003 , 3 , 269–273. [ Google Scholar ] [ CrossRef ]
• Tang, Q.Y.; Shafiq, I.; Chan, Y.C.; Wong, N.B.; Cheung, R. Study of the dispersion and electrical properties of carbon nanotubes treated by surfactants in dimethylacetamide. Nanotechnology 2010 , 10 , 4967–4974. [ Google Scholar ] [ CrossRef ]
• Li, X.; Zhu, D. Evaluation on dispersion behavior of the aqueous copper nano-suspensions. J. Colloid Interface Sci. 2007 , 310 , 456–463. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Hwang, Y.; Lee, J.K.; Jeong, Y.M.; Cheong, S.I.; Ahn, Y.C.; Kim, S.H. Production and dispersion stability of nanoparticles in nanofluids. Powder Technol. 2008 , 186 , 145–153. [ Google Scholar ] [ CrossRef ]
• Wu, G.S.; Yang, J.K.; Ge, S.L.; Chen, Y.F. Thermal conductivity measurement for carbon nanotube suspensions with 3ω method. Adv. Mater. Res. 2009 , 60 , 394–398. [ Google Scholar ] [ CrossRef ]
• Choudhary, R.; Khurana, D.; Kumar, A.; Subudhi, S. Stability analysis of Al 2 O 3 /water nanofluids. J. Exp. Nanosci. 2017 , 12 , 140–151. [ Google Scholar ] [ CrossRef ]
• Mo, S.; Chen, Y.; Jia, L.; Luo, X.L. Investigation on crystallization of TiO 2 -water nanofluids and deionized water. Appl. Energy 2012 , 93 , 65–70. [ Google Scholar ] [ CrossRef ]
• Witharana, S.; Palabiyik, I.; Musina, Z.; Ding, Y.L. Stability of glycol nanofluids-the theory and experiment. Powder Technol. 2013 , 239 , 72–77. [ Google Scholar ] [ CrossRef ]
• Adil, M.; Zaid, H.M.; Chuan, L.K.; Latiff, N.R.A. Effect of dispersion stability on electrorheology of water-based ZnO nanofluids. Energy Fuels 2016 , 30 , 6169–6177. [ Google Scholar ] [ CrossRef ]
• Han, Y.F. The development trend of new energy vehicle coolant pipeline. New Energy Automob. 2021 , 4 , 80–81. [ Google Scholar ]
• Liu, B. Detection and replacement measures of engine coolant. Technol. Equip. 2022 , 48 , 76–78. [ Google Scholar ]
• Eneren, P.; Aksoy, Y.T.; Vetrano, M.R. Experiments on single-phase nanofluid heat transfer mechanisms in microchannel heat sinks: A review. Energies 2022 , 15 , 2525. [ Google Scholar ] [ CrossRef ]
• Mohammad, K.; Ebrahim, S.; Avara, A. Analysis of entropy generation, pumping power, and tube wall temperature in aqueous suspensions of alumina particles. Heat Transf. Res. 2012 , 43 , 327–341. [ Google Scholar ]
• Ho, C.J.; Wei, L.C.; Li, Z.W. An experimental investigation of forced convective cooling performance of a microchannel heat sink with Al 2 O 3 /water nanofluid. Appl. Therm. Eng. 2010 , 30 , 96–103. [ Google Scholar ] [ CrossRef ]
• Pandey, S.D.; Nema, V.K. Experimental analysis of heat transfer and friction factor of nanofluid as a coolant in a corrugated plate heat exchanger. Exp. Therm. Fluid Sci. 2012 , 38 , 248–256. [ Google Scholar ] [ CrossRef ]
• Lyu, Z.J.; Asadi, A.; Alarifi, L.M. Thermal and fluid dynamics performance of MWCNT-water nanofluid based on thermophysical properties: An experimental and theoretical study. Sci. Rep. 2020 , 10 , 5185. [ Google Scholar ] [ CrossRef ]
• Meisam, A.; Amin, A.; Aberoumand, S. An experimental and theoretical investigation on the effects of adding hybrid nanoparticles on heat transfer efficiency and pumping power of an oil-based nanofluid as a coolant fluid. Int. J. Refrig. 2018 , 89 , 83–92. [ Google Scholar ]
• Khdher, A.M.; Sidik, N.A.C.; Hamzah, W.A.W.; Mamat, R. An experimental determination of thermal conductivity and electrical conductivity of bio glycol based Al 2 O 3 nanofluids and development of new correlation. Int. Commun. Heat Mass Transf. 2016 , 73 , 75–83. [ Google Scholar ] [ CrossRef ]
• Subramaniyan, A.; Sukumaran, L.P.; Ilangovan, R. Investigation of the dielectric properties of TiO 2 nanofluids. J. Taibah Univ. Sci. 2016 , 10 , 403–406. [ Google Scholar ] [ CrossRef ]
• Chilambarasan, L.; Prakash, R.; Shanu, J.P.; Murugasen, P. Investigation on the electrical conductivity of aqueous glycol based ZnO nanofluids. J. Appl. Fluid Mech. 2019 , 12 , 865–870. [ Google Scholar ] [ CrossRef ]

Click here to enlarge figure

Share and Cite

Tao, Q.; Zhong, F.; Deng, Y.; Wang, Y.; Su, C. A Review of Nanofluids as Coolants for Thermal Management Systems in Fuel Cell Vehicles. Nanomaterials 2023 , 13 , 2861. https://doi.org/10.3390/nano13212861

Tao Q, Zhong F, Deng Y, Wang Y, Su C. A Review of Nanofluids as Coolants for Thermal Management Systems in Fuel Cell Vehicles. Nanomaterials . 2023; 13(21):2861. https://doi.org/10.3390/nano13212861

Tao, Qi, Fei Zhong, Yadong Deng, Yiping Wang, and Chuqi Su. 2023. "A Review of Nanofluids as Coolants for Thermal Management Systems in Fuel Cell Vehicles" Nanomaterials 13, no. 21: 2861. https://doi.org/10.3390/nano13212861

Article Metrics

Article access statistics, further information, mdpi initiatives, follow mdpi.

Subscribe to receive issue release notifications and newsletters from MDPI journals

We apologize for the inconvenience...

To ensure we keep this website safe, please can you confirm you are a human by ticking the box below.

If you are unable to complete the above request please contact us using the below link, providing a screenshot of your experience.

https://ioppublishing.org/contacts/

• Open access
• Published: 20 May 2015

Performance evaluation of nanofluids in solar energy: a review of the recent literature

• Navid Bozorgan 1 &
• Maryam Shafahi 2  

Micro and Nano Systems Letters volume  3 , Article number:  5 ( 2015 ) Cite this article

21k Accesses

66 Citations

1 Altmetric

Metrics details

Utilizing nanofluid as an absorber fluid is an effective approach to enhance heat transfer in solar devices. The purpose of this review is to summarize the research done on the nanofluids’ applications in solar thermal engineering systems in recent years. This review article provides comprehensive information for the design of a solar thermal system working at the optimum conditions. This paper identifies the opportunities for future research as well.

Introduction

Energy is an important entity for the economic development of any country. On the other hand, fossil fuels meeting a great portion of the energy demand are scarce and their availability is decreasing continously. Nowadays, solar systems play an important role in the production of energy from renewable sources by converting solar radiation into useful heat or electricity. Considering the environmental protection and great uncertainty over future energy supplies, solar energy is a better alternative energy form in spite of its its slightly higher operation costs. Heat transfer enhancement in solar devices is one of the significant issues in energy saving and compact designs. One of the effictive methods is to replace the working fluid with nanofluids as a novel strategy to improve heat transfer characteristics of the fluid. More recently reserachers have become interested in the use of nanofluids in collectors, water heaters, solar cooling systems, solar cells, solar stills, solar absorption refrigeration systems, and a combination of different solar devices due to higher thermal conductivity of nanofluids and the radiative properties of nanoparticle. How to select suitable nanofluids in solar applications is a key issue. The effectiveness of nanofluids as absorber fluids in a solar device strongly depends on the type of nanoparticles and base fluid, volume fraction of nanoparticles, radiative properties of nanofluids, temperature of the liquid, size and shape of the nanoparticles, pH values, and stability of the nanofluids [ 1 ]. It was found that only a few review papers have discussed the capability of nanofluids to enhance the performance of solar systems [ 2 - 5 ].This paper compiles recent research in this field and identifies many issues that are open or even not commenced to investigate. It is authors’ hope that this review will be useful to determine the effectiveness of nanofluids in solar applications.

Literature review of recent years

Using nanofluids in solar collectors, role of nanoparticles.

Gan et al. [ 6 ] experimently showed that the radiation absorption of Al 2 O 3 nanofluids is less than Aluminuim nanofluids. For nanofluids with Al 2 O 3 particles, the situation is different because of the different optical properties of Al 2 O 3 . The weak radiation absorption of Al 2 O 3 nanoparticles will not result in significant localized convective heat transfer from the particles to the base fluids. The use of Al 2 O 3 /water nanofluid as coolant was simulated for a silicon solar cell using the finite element method by Elmir et al. [ 7 ]. They considered the solar panel as an inclined cavity with a slope of 30°. Application of nanofluids increased the average Nusselt number and rate of cooling. They reported 27% enhancement in the heat transfer rate for 10% alumina nanofluid at Re = 5.

Luo et al. [ 8 ] simulated the performance of a DAC solar collector with nanofluids using a 2D model by solving the radiative transport equations of particulate media and combining conduction and convection heat transfer equations. The nanofluid flows horizontally from right to left in a steady-state solar collector covered with a glass plate. A solar radiation simulator is used to validate their model. They prepared nanofluids by dispersing and oscillating TiO 2 , Al 2 O 3 , Ag, Cu, SiO 2 , graphite nanoparticles, and carbon nanotubes into Texatherm oil. Their results show that the use of nanofluid in solar collector can improve the outlet temperature and efficiency. They also found that the efficiency of most nanofluids are similar and larger than that of oil, except for TiO 2 .

Rahman et al. [ 9 ] performed a numerical study for a triangular shape solar collector with nanofluids by Galerkin weighted residual finite element method for a wide range of Grashof numbers (Gr). The corrugated bottom is kept at a constant high temperature and the side walls of the triangular enclosure are kept at a low temperature as seen in Figure  1 . It is assumed that both fluid phase and nanoparticles are in thermal equilibrium and there is no slip between them. Nanofluid is Newtonian and incompressible, and flow is laminar and unsteady. Constant thermophysical properties are considered for the nanofluid except for the density variation in the buoyancy forces determined by using the Boussinesq approximation. Nevertheless, they have not mentioned the particle’s diameters. The authors concluded that high value of both Gr and solid volume fraction confirms better heat transfer through convection and conduction. Results showed 24.28% improvement for Gr = 10 6 at 10% volume fraction of copper particles. For lower values of Gr number, conduction is the primary mode of heat transfer for any value of solid volume fractions. The results showed that the convective heat transfer performance is better when the solid volume fraction is kept at 0.05 or 0.08. This study also showed that cu-water nanofluid is the best nanofluid for the augmentation of heat transfer.

(a) Schematic of the triangular shape collector (b) 3D view of a solar thermal collector filled with nanofluid [ 9 ].

Faizal et al. [ 10 ] investigated the thermal performance of nanofluid solar collector and its contribution size reduction to estimate the cost saving. Their findings indicated that efficiency of solar collector with nanofluids is calculated by the function of working fluid density, specific heat and mass flow rates. The results confirmed that higher density and lower specific heat of nanofluids offers higher thermal efficiency than water and can reduce the solar collector area about 25.6%, 21.6%, 22.1% and 21.5% for CuO, SiO 2 , TiO 2 and Al 2 O 3 nanofluids as seen in Figure  2 . Hence, it will reduce the weight, energy and cost to manufacture the collector. The average value of 220 MJ embodied energy can be saved for each collector, 2.4 years payback period can be achieved and around 170 kg less CO 2 emissions will be the result of using nanofluid based solar collector compared to a conventional one. Environmental damage cost is also lower with the nanofluid based solar collector.

Percentage of size reduction for solar collector by applying different nanofluids.

Parvin et al. [ 11 ] numerically investigated the effects of the nanoparticle volume fraction (ϕ = 0%, 1%, 3%, 5% and 7%) and the Reynolds number (Re = 200, 400, 600, 800 and 1000) on the temperature distribution, rate of entropy generation, and collector efficiency. The working fluid was incompressible Cu-water nanofluid under a laminar regime. Their findings were as follows: a) Increasing the particles concentration raises the fluid viscosity and decreases the Reynolds number and consequently decreases heat transfer. b) It is important to find the optimum volume fraction of nanoparticle for each application. c) The collector efficiency can be enhanced nearly 2 times by using Ag-water and Cu-water nanofluids with concentration of 3% as seen in Figure  3 d) The entropy generation is enhanced up to ϕ = 3% as seen in Figure  3 . After this level, adding more nanoparticles makes no changes in mean entropy generation.

Collector efficiency (η), mean entropy generation (S) and Bejan number (Be) at various concentrations.

Ladjevardi et al. [ 12 ] numerically studied the effects of using nanofluid on the performance of a solar collector as seen in Figure  4 considering the different diameter and volume fractions of graphite nanoparticles. They observed that in the infrared domain, the water optical characteristics are dominant while in the UV and visible ranges extinction coefficients are dependent on nanoparticle volume fractions. The extinction coefficient is calculated from the absorption and scattering efficiencies in this research. Their numerical results showed that nanofluid collector thermal efficiency increases about 88% compared with the one in pure water collector with the inlet temperature of 313 K. It also can be increased to 227% with the inlet temperature of 333 K.

Schematic of volumetric solar collector.

Filho et al. [ 13 ] studied silver nanoparticles as direct sunlight absorbers for solar thermal applications. Their results showed that the maximum stored thermal energy increases by 52%, 93% and 144% for silver particle concentration of 1.62, 3.25 and 6.5 ppm respectively due to the good photothermal conversion properties of silver nanoparticles. They also observed that the influence of particle concentration on the specific absorption rate (SAR) is only discernable at the initial heating period. It was concluded that reduction in the SAR at higher particle loadings (65 and 650 ppm) might be the result of: (i) The formation of agglomerates and reduction in the intensity of the sunlight into the fluid due to the deposited particles on the surface, (ii) The difference in the absorption efficiency of each particle at different fluid depth, (iii) The heat leak through radiation may become strengthened as the particle concentration exceeds a certain value as seen in Figures  5 , 6 and 7 .

Experimental system: (a) a schematic illustration and (b) a snapshot of the system under direct sunlight on top of a roof.

Comparison of the ratio of stored thermal energy at different concentrations (where b and u refer to thermocouples located at the bottom and upper positions respectively).

Specific absorption rate of silver nanoparticles (where b and u refer to thermocouples located at the bottom and upper positions respectively).

Karami et al. [ 14 ] experimentally showed that aqueous suspension based alkaline functionalized carbon nanotubes (f-CNT), 10 nm in diameter and 5-10 μm in length, has good stability as an absorber fluid in low-temperature Direct Absorption Solar Collector (DASC). The reason is associated with the hydrophilic nature of carboxylate groups. f-CNT considerably reduces the transmittance and enhances the thermal conductivity as seen in Figure  8 . They recommended the use of this kind of nanofluids to absorb the light directly. In this study, f-CNTs was dispersed into the water by an ultrasonic instrument with the volume fractions less than 150 ppm. Higher concentrations produced a black solution which light was not able to pass through it.

Thermal conductivity of f-CNT/water NFs in ambient temperature and 60°C.

Said et al. [ 15 ] found that nanofluids with single wall carbon nanotubes (SWCNTs) in a flat plate solar collector showed the minimum entropy generation compared to the nanofluids prepared by suspending Al 2 O 3 , TiO 2 and SiO 2 nanoparticles in the same base fluid as seen in Figure  9 . They attributed the decrease of the entropy generation to the increase in heat flux on the absorber plate due to the nanoparticles addition. Ultrasonicator and high pressure homogenizer (capacity of up to 2000 bar) is used to disperse the nanoparticles into the water. It was observed the SWCNTs nanofluids could reduce the entropy generation by 4.34% and enhance the heat transfer coefficient by 15.33%. It also had a small penalty in the pumping power by 1.2%.

Change of entropy generation with volume fraction.

Tang et al. [ 16 ] prepared the carbon nanotube/PEG/SiO 2 composites with high thermal conductivity from multiwall carbon nanotubes (MWCNTs), poly (ethylene glycol) (PEG) and inorganic SiO 2 . These composites had higher thermal conductivity than traditional phase-change materials (PCMs) because of the high thermal conductivity of MWCNTs. Their results clearly showed that PEG/ SiO 2 /MWCNT composites can effectively improve the efficiency of solar energy applications.

Saidur et al. [ 17 ] investigated the effects of different parameters on the efficiency of a low-temperature nanofluid-based direct absorption solar collector (DAC) with water and aluminum nanoparticles. One big advantage of using low-temperature systems is that solar collectors can be relatively simple and inexpensive. Additionally, there are a number of working fluids suitable to low-temperature operation. Commonly used base liquids are water, oil, and ethylene glycol. They accounted for the effects of absorption and scattering within the nanofluid to evaluate the intensity distribution within the nanofluid by the radiative transfer equation (RTE). In order to calculate the spectral extinction coefficient of the nanofluid that is sum of scattering coefficient and absorption coefficient, they investigated the optical properties of the based fluid and nanoparticles separately. Their results revealed that Aluminum/water nanofluid with 1% volume fraction improves the solar absorption considerably. They found that the effect of particle size on the optical properties of nanofluid is minimal, but in order to have Rayleigh scattering the size of nanoparticles should be less than 20 nm. They also found that the extinction coefficient is linearly proportionate to volume fraction.

Sokhansefat et al. [ 18 ] numerically investigated the heat transfer enhancement for Al 2 O 3 /synthetic oil nanofluid with concentrations up to 5% in a parabolic trough collector tube at different operational temperatures as seen in Figure  10 . Nanofluid enhanced convective heat transfer coefficient as seen in Figure  11 .

Schematic diagram of the parabolic trough collector and absorber tube.

Mean convective heat transfer coefficient vs.particle concentration at the operational temperatures of 300,400 and 500 K.

Nasrin et al. [ 19 ] performed a numerical study to investigate the influence of Prandtl number on the flow, temperature fields, convective and radiated heat transfer rates, mean bulk temperature of the fluids and average velocity field in a solar with water- Al 2 O 3 nanofluid collector as seen in Figure  12 . The results showed that with increasing Pr from 1.73 to 6.62, the convective heat transfer enhances about 26% and 18% for nanofluid and base fluid respectively whereas the radiation enhances by 8%.

Schematic diagram of the solar collector.

Role of base fluid

Colangelo et al. [ 20 ] experimently showed that the thermal conductivity improvement of the nanofluids with diathermic oil is greater than that with water in high temperature applications such as solar collectores. They observed that the thermal conductivity reduced with increasing the size of nanoparticles.

Hordy et al. [ 21 ] made four different nanofluids by dispersing plasma functionalized multi-walled carbon nanotubes (MWCNTs) in water, ethylene glycol, propylene glycol and Therminol VP-1 heat transfer fluids with the aid of an ultrasonic bath. They examined both the long-term and high-temperature stability of CNT nanofluids for use in direct solar absorption. In this work plasma treatment applied to modify the surface of the MWCNTs to improve their dispersion property within the base fluid. This study reported a quantitative demonstration of the high temperature and long-term stability of ethylene glycol and propylene glycol-based MWCNT nanofluids for solar thermal collectors.

Said et al. [ 22 ] experimentlly investigated the thermal conductivity, viscosity and pressure drop of water, ethylene glycol (EG) and EG + H2O (60:40)-based Al2O3 (13 nm) nanofluids prepared by using ultrasonic dispersion method in the operating temperature range of 25°C to 80°C at low range concentrations of 0.05% to 0.1% for. They observed that deviation of experimental values from estimated values of thermal conductivity of Al 2 O 3 /water nanofluids is considerably high but the experimental values of Al 2 O 3 /EG nanofluids are nearly similar to those of the model calculation as seen in Figure  13 . Their results showd that nanofluids pressure drop at a low concentration flowing in a solar collector is slightly higher than the base fluid.

Thermal conductivity of Al2O3/EG (a) and Al2O3/water (b) nanofluids at different volume fractions and at 25°C.

Liu et al. [ 23 ] experimentally investigated the feasibility of using the graphene (GE)-dispersed nanofluids based on the ionic liquid 1-hexyl-3-methylimidazolium tetrafluoroborate ([HMIM] BF 4 ) in high-temperature heat transfer systems (such as solar collectors). Ionic liquids (ILs) are a group of molten salts with a melting below 100°C as well as a wide liquid temperature range from room temperature to a maximum temperature of 459°C. ILs have excellent thermophysical properties such as good thermal and chemical stability, high density and heat capacity and negligible vapor pressure. In this work, authors showed how to improve the performance of ILs for solar thermal systems. They observed 15.2%-22.9% enhancement in thermal conductivity using 0.06% graphene in the temperature range from 25 to 200°C as seen in Figure  14 . Their results showed that GE is a better nanoadditive for nanofluids than other carbon materials and metal nanoparticles.

Thermal conductivity of [HMIM]BF4 and the GE-dispersed Ionanofluids as a function of temperature.

Variation of specific heat capacity with temperature for the pure and the different nanoparticle concentration of Hitec nanofluid.

The authors attributed this reduction to the self-lubrication characteristic of GE. In addition, the results obtained from the thermogravimetric analysis showed the high thermal stability of GE/BF 4 nanofluids. Their measurements showed that this novel class of nanofluids is very suitable for high temperature applications such as solar collectors.

Ho et al. [ 24 ] found the optimal concentration of alumina nanoparticles in doped molten Hitec (a nitrate salt) by maximizing its specific heat capacity. High-temperature molten salt typically has a high heat capacity and is effective as a working fluid for concentrating solar power (CSP) systems. Their findings are as follows: 1- The addition of less than 2% Al 2 O 3 nanoparticles significantly increases the specific heat of Hitec metal at low temperatures as seen in Figure  15 , 2- For the volume fractions less than or equal to 0.5%, adding Al 2 O 3 nanoparticles has a negative effect on the specific heat in temperature of 335°C, 3- At all temperatures, a concentration of 0.063 wt.% provides the maximum enhancement of specific heat about 19.9%, 4- The scanning electron microscopic (SEM) images show that, even at a relatively low concentration, nanoparticles aggregate as clusters with the size of 0.2 to 0.6 μm in the grain boundaries of Hitec, 5- The findings of this study suggest that the concentration that yields favorable uniform dispersion and optimal pattern of particles or clusters may maximize the specific heat. The simplified model of the solid-fluid interfacial area demonstrates that interfacial area is maximal at a concentration of 0.023 wt.%. As the nanoparticle concentration increases above 0.023 wt. %, the formed clusters become larger and the interfacial area density between the solid clusters and the base fluid decreases which may reduce the increase in specific heat capacity. According to the results obtained from this study, the maximum enhancement of the specific heat capacity occurs at concentration of 0.063 wt.% instead of 0.023 wt.%. Indeed, some agglomeration of nanoparticles forming submicrometer clusters may be the best for the enhancement of specific heat capacity. However, the total interfacial area at concentration of 0.063 wt. % was slightly less than its value at concentration of 0.023 wt. %.

Role of surfactants

Singh et al. [ 25 ] added Cu to commercial solar heat transfer fluids (Therminol 59 (TH59) and Therminol 66 (TH66)) by the combination of temperature and ultrasonic ripening processes. They stated that surfactant selection has an important role in preparing stable nanofluids. Choosing the right surfactant is mainly dependent on the properties of the base fluids and particles. For example, silicon oxide nanoparticles were successfully dispersed in TH66 using benzalkonium chloride (BAC, Acros Organics) as a surfactant but the use of BAC surfactant with Cu nanoparticles did not provide sufficient stability of suspension due to the lack of specific interaction between the nanoparticles and the surfactant molecules. The bi-layer arrangement of surfactant molecules should provide good adhesion to the nanoparticle surface and miscibility with the aromatic solvent. In this work, authors used a combination of oleic acid and BAC and a mixture of octadecyl thiol (ODT) and BAC surfactants to disperse Cu nanoparticles in TH66 and TH59, respectively. They observed that 3D Cu nanoparticle agglomerates do not break by conventional sonication with ultrasound gun without temperature ripening. They showed that a sonication time of about 4 h leads to the effective breakup of Cu agglomerates into individual grains at a 120°C. They also concluded that Cu/TH66 nanofluids appear to be more stable than the Cu/TH59 nanofluids because of the higher dynamic viscosity.

Yousefi et al. [ 26 , 27 ] studied the effect of Al 2 O 3 (15 nm) and MWCNT (10-30 nm) water nanofluid on the efficiency of a flat plate solar collector experimentally. The weight fractions of the nanoparticles were 0.2% and 0.4%, and the experiments were performed with and without Triton X-100 as surfactant. Their findings showed that the surfactant presence in the nanofluid extremely affects solar collector’s efficiency.

Lenert et al. [ 28 ] presented a combined modeling and experimental study to optimize the performance of a cylindrical nano-fluid volumetric receiver. They concluded that the efficiency is more than 35% when nanofluid volumetric receivers are coupled to a power cycle and optimized with respect to the optical thickness and solar exposure time. This study provides an important perspective in the use of nanofluids as volumetric receivers in concentrated solar applications. In this work, 28 nm carbon-coated cobalt (C-Co) nanoparticles dispersed and suspended in Therminol VP-1 after 30 min in a sonication bath without any surfactant.

Role of the pH

Yousefi et al. [ 29 ] investigated the effect of pH of MWCNT-H2O nanofluid on the efficiency of a flat-plate solar collector as seen in Figure  16 . The experiments were carried out using 0.2 wt% MWCNT (10-30 nm) with various pH values (3.5, 6.5 and 9.5) and with Triton X-100 as an additive. They found that increasing or decreasing the pH with respect to the pH of the isoelectric point (IEP) would enhance the positive effect of nanofluids on the efficiency of the solar collector. The collector efficiency enhanced while the differences between the pH of nanofluids and that of isoelectric increased. As the nanofluids become more acidic (lower pH value), more charges are accumulated on the particle surface, leading to lower agglomeration of nanoparticles in the suspension. Consequently, the effective thermal conductivity of the nanofluid increases. In addition, with the increase in pH of the nanofluid, the surface charge of the CNT increases leading to the increase in thermal conductivity and stability of nanofluid.

The efficiency of the flat-plate solar collector with MWCNT nanofluid as base fluid at three pH values as compared with water in0.0333 kg/s mass flow rate.

Using nanofluids in photovoltaic/thermal (PV/T) system

Sardarabadi et al. [ 30 ] performed experiments to study the effects of using SiO2/water nanofluid as a coolant on the thermal and electrical efficiencies of a photovoltaic thermal (PV/T) system. A flat plate solar collector was attached to a PV panel. The tilt angle of the collector was set at a constant value of 32° to maximize the solar collecting area. It was observed that by adding a thermal collector to a PV system, the total exergy for the three cases with pure water, 1% silica/water nanofluid and 3% silica/water nanofluid increased by 19.36%, 22.61% and 24.31%, respectively as seen in Figure  17 . Thermal efficiency of the PV/T collector for the two cases of 1 and 3 wt% of silica/water nanofluid increased 7.6% and 12.8%, respectively.

Exergetic efficiency of the system for the three cases with pure water (a), 1% silica/water nanofluid (b) and 3% silica/water nanofluid (c) during the daily experiment.

Karami et al. [ 31 ] experimentlly investigated the cooling performance of water based Boehmite (AlOOH. xH 2 O) nanofluid in a hybrid photovoltaic (PV) cell. The PV cell is mono-crystalline silicon. Results showed that the nanofluid performed better than water and the average PV surface temperature decreased from 62.29°C to 32.5°C as seen in Figure  18 . They reported that the electrical efficiency falls as the concentration of the nanofluid rises beyond a certain level. The authors attributed this reduction to the high surface activity of nanoparticles and their tendency to agglomeration/clustering at high particle loadings. Table 1 summarizes the results of nanofluids influence on different solar thermal applications

Variation of the average temperatures of the PV surface at various flow rates for water and three different concentrations of nanofluid.

Using nanofluids in solar stills

Kabeel et al. [ 32 ] investigated a small unit for water desalination coupled with nano-fluid-based (Cu/water) solar collector as a heat source as seen in Figure  19 . The system consists of a solar water heater (flat plate solar collector), a mixing tank and a flashing chamber plus a helical heat exchanger and a condenser. The desalination process is based on the evaporation of sea water under a very low pressure (vacuum). The evaporated water is then condensed to obtain fresh water. The simulation results showed that the nanoparticle concentration is an important factor on increasing the fresh water production and decreasing cost. Authors reported that the water cost can be decreased from 16.43 to 11.68 $/m 3 at ϕ = 5% as seen in Figure  20 .

Schematic diagram of single stage flash (SSF) system.

Variations in system productivity and water cost as a function of nano-particle volume fraction.

Kabeel et al. [ 33 ] used Al 2 O 3 nanoparticles with water inside a single basin solar still. Their results showed that using nanofluids improves the solar still water productivity by about 116% and 76% with and without operating the vacuum fan. The authors attributed this increment to the increase of evaporation rate inside the still. Utilizing nanofluid increases the rate of evaporation. In addition, due to this vacuum inside the still the evaporation rate increases further and the productivity increases compared with the still working at atmospheric conditions.

Using nanofluids in solar pond

Al-Nimr et al. [ 34 ] presented a mathematical model to describe the effects of using silver-water nanofluid on the thermal performance of a shallow solar pond (SSP) and showed that the energy stored in the nanofluid pond is about 216% more than the energy stored in the brine pond. The upper layer of the pond is made of mineral oil and the lower layer is made of silver (Ag) water-based nanofluid. Their results showed that for solar radiation of 1000 W/m 2 , the nanofluid pond required a depth less than 25 cm in order to absorb the light, while the brine pond depth must be more than 25 m to absorb the same amount of light. They attributed the increase of stored energy to the increase in thermal conductivity of the base fluid due to the nanoparticles addition that leads to uniform temperature distribution within the layer with reduction in heat losses.

Using nanofluids in the solar collector integrated with open thermosyphon

Liu et al. [ 35 ] experimentally showed that the solar collector integrated with open thermosyphon has a much better collecting performance compared to the collector with concentric tube and its efficiency could be improved by using CuO/water nanofluid as the working fluid as well. Their results showed that the maximum and mean values of the collecting efficiency of the collector with open thermosyphon using nanofluids increased 6.6% and 12.4%, respectively.

Conclusions

Nanofluids have been utilized to improve the efficiency of several solar thermal applications. Theoretical and experimental studies on solar systems proved that the system performance enhances noticeably by using nanofluids. A number of investigations presented the existence of an optimum concentration for nanoparticles in the base fluid. Adding nanoparticles beyond the optimum level no longer enhances the efficiency of the solar system.

Optimal conditions are a function of nanoparticles size and concentration, base fluid, surfactant and pH as discussed throughout this article. Nanofluid utilization in the solar thermal systems is accompanied by important challenges including high cost of production, instability, agglomeration and erosion. This review article is an attempt to elucidate the advantages and disadvantages of nanofluids application in the solar system.

Taylori R, Coulombe S, Otanicar T, Phelan P, Gunawan A, Lv W, Rosengarten G, Prasher R, Tyagi H (2013) Small particles, big impacts: a review of the diverse applications of nanofluids. J Appl Phys 113:011301–011301-19

Article   Google Scholar  

Mahian O, Kianifar A, Kalogirou SA, Pop I, Wongwises S (2013) A review of the applications of nanofluids in solar energy. Int J Heat Mass Transf 57:582–594

Said Z, Sajid MH, Saidur R, Kamalisarvestani M, Rahim NA (2013) Radiative properties of nanofluids. Int Commun Heat Mass Transfer 46:74–84

Al-Shamani AN, Yazdi MH, Alghoul MA, Abed AM, Ruslan MH, Mat S, Sopian K (2014) Nanofluids for improved efficiency in cooling solar collectors – a review. Renew Sustain Energy Rev 38:348–367

Khullar V, Tyagi H, Phelan PE, Otanicar TP, Singh H, Taylor RA (2013) Solar energy harvesting using nanofluids-based concentrating solar collector. J Nanotechnol Eng Med 3:031003-1-9

Google Scholar  

Gan Y, Qiao L (2012) Radiation-enhanced evaporation of ethanol fuel containing suspended metal nanoparticles. Int J Heat Mass Transfer 55:5777–5782

Elmir M, Mehdaoui R, Mojtabi A (2012) Numerical simulation of cooling a solar cell by forced convection in the presence of a nanofluid. Energy Procedia 18:594–603

Luo Z, Wang C, Wei W, Xiao G, Ni M (2014) Performance improvement of a nanofluid solar collector based on direct absorption collection (DAC) concepts. Int J Heat Mass Transfer 75:262–271

Rahman MM, Mojumder S, Saha S, Mekhilef S, Saidur R (2014) Augmentation of natural convection heat transfer in triangular shape solar collector by utilizing water based nanofluids having a corrugated bottom wall. Int Commun Heat Mass Transfer 50:117–127

Faizal M, Saidur R, Mekhilef S, Alim MA (2013) Energy, economic and environmental analysis of metal oxides nanofluid for flat-plate solar collector. Energy Convers Manag 76:162–168

Parvin S, Nasrin R, Alim MA (2014) Heat transfer and entropy generation through nanofluid filled direct absorption solar collector. Int J Heat Mass Transfer 71:386–395

Ladjevardi SM, Asnaghi A, Izadkhast PS, Kashani AH (2013) Applicability of graphite nanofluids in direct solar energy absorption. Sol Energy 94:327–334

Filho EPB, Mendoza OSH, Beicker CLL, Menezes A, Wen D (2014) Experimental investigation of a silver nanoparticle-based direct absorption solar thermal system. Energy Convers Manag 84:261–267

Karami M, AkhavanBahabadi MA, Delfani S, Ghozatloo A (2014) A new application of carbon nanotubes nanofluid as working fluid of low-temperature direct absorption solar collector. Sol Energy Mater Sol Cells 121:114–118

Said Z, Saidur R, Rahim NA, Alim MA (2014) Analyses of exergy efficiency and pumping power for a conventionalflat plate solar collector using SWCNTs based nanofluid. Energy Build 78:1–9

Tang B, Wang Y, Qiu M, Zhang S (2014) A full-band sunlight-driven carbon nanotube/PEG/SiO2 composites for solar energy storage. Sol Energy Mater Sol Cells 123:7–12

Saidur R, Meng TC, Said Z, Hasanuzzaman M, Kamyar A (2012) Evaluation of the effect of nanofluid-based absorbers on direct solar collector. Int J Heat Mass Transfer 55:5899–5907

Sokhansefat T, Kasaeian AB, Kowsary F (2014) Heat transfer enhancement in parabolic trough collector tube using Al2O3/synthetic oilnanofluid. Renew Sustain Energy Rev 33:636–644

Nasrin R, Parvin S, Alim MA (2013) Effect of Prandtl number on free convection in a solar collector filled with nanofluid. Procedia Engineering 56:54–62

Colangelo G, Favale E, de-Risi A, Laforgia D (2012) Results of experimental investigations on the heat conductivity of nanofluids based on diathermic oil for high temperature applications. Appl Energy 97:828–833

Hordy N, Rabilloud D, Meunier JL, Coulombe S (2014) High temperature and long-term stability of carbon nanotube nanofluids for direct absorption solar thermal collectors. Sol Energy 105:82–90

Said Z, Sajid MH, Alim MA, Saidur R, Rahim NA (2013) Experimental investigation of the thermophysical properties of AL2O3-nanofluid and its effect on a flat plate solar collector. Int Commun Heat Mass Transfer 48:99–107

Liu J, Wang F, Zhang L, Fang X, Zhang Z (2014) Thermodynamic properties and thermal stability of ionic liquid-based nanofluids containing graphene as advanced heat transfer fluids for medium-to-high-temperature applications. Renew Energy 63:519–523

Ho MX, Pan C (2014) Optimal concentration of alumina nanoparticles in molten Hitec salt to maximize its specific heat capacity. Int J Heat Mass Transfer 70:174–184

Singh D, Timofeeva EV, Moravek MR, Cingarapu S, Yu W, Fischer T, Mathur S (2014) Use of metallic nanoparticles to improve the thermophysical properties of organic heat transfer fluids used in concentrated solar power. Sol Energy 105:468–478

Yousefi T, Veysi F, Shojaeizadeh E, Zinadini S (2012) An experimental investigation on the effect of Al2O3-H2O nanofluid on the efficiency of flat-plate solar collectors. Renew Energy 39:293–298

Yousefi, F. Veysy, E. Shojaeizadeh, S. Zinadini (2012). An experimental investigation on the effect of MWCNT-H2O nanofluid on the efficiency of flat-plate solar collectors. Experimental Thermal and Fluid Science 207-212

Lenert A, Wang EN (2012) Optimization of nanofluid volumetric receivers for solar thermal energy conversion. Sol Energy 86:253–265

Yousefi T, Shojaeizadeh E, Veysi F, Zinadini S (2012) An experimental investigation on the effect of pH variation of MWCNT–H2O nanofluid on the efficiency of a flat-plate solar collector. Sol Energy 86:771–779

Sardarabadi M, Passandideh-Fard M, Zeinali Heris S (2014) Experimental investigation of the effects of silica/water nanofluid on PV/T (photovoltaic thermal units). Energy 66:264–272

Karami N, Rahimi M (2014) Heat transfer enhancement in a hybrid microchannel-photovoltaic cell using Boehmite nanofluid. Int Commun Heat Mass Transfer 55:45–52

Kabeel AE, El-Said EMS (2014) Applicability of flashing desalination technique for small scale needs using a novel integrated system coupled with nanofluid-based solar collector. Desalination 333:10–22

Kabeel AE, Omara ZM, Essa FA (2014) Enhancement of modified solar still integrated with external condenser using nanofluids: An experimental approach. Energy Convers Manag 78:493–498

Al-Nimr MA, Al-Dafaie AMA (2014) Using nanofluids in enhancing the performance of a novel two-layer solar pond. Energy 68:318–326

Liu ZH, Hu RL, Lu L, Zhao F, Xiao HS (2013) Thermal performance of an open thermosyphon using nanofluid for evacuated tubular high temperature air solar collector. Energy Convers Manag 73:135–143

Download references

Acknowledgements

The authors would like to express their appreciation to the Islamic Azad University of Abadan Branch for providing financial support.

Author information

Authors and affiliations.

Mechanical Engineering Department, Abadan Branch, Islamic Azad University, P.O.B. 666, Abadan, Iran

Navid Bozorgan

Mechanical Engineering Department, California State Polytechnic University, Pomona, California, USA

Maryam Shafahi

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Navid Bozorgan .

Additional information

Competing interests.

The authors declare that they have no competing interests.

Authors’ contributions

MS conducted the extensive literature review and NB wrote the article. Both authors read and approved the final manuscript.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0 ), which permits use, duplication, adaptation, distribution, and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Reprints and permissions

About this article

Cite this article.

Bozorgan, N., Shafahi, M. Performance evaluation of nanofluids in solar energy: a review of the recent literature. Micro and Nano Syst Lett 3 , 5 (2015). https://doi.org/10.1186/s40486-015-0014-2

Download citation

Received : 04 September 2014

Accepted : 26 January 2015

Published : 20 May 2015

DOI : https://doi.org/10.1186/s40486-015-0014-2

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Solar energy
• Solar systems
• Heat transfer enhancement

Application of nanofluids as cutting fluids in machining operations: a brief review

• Review Article
• Published: 03 February 2022
• Volume 13 , pages 4247–4278, ( 2023 )

Cite this article

• Lotfi Ben Said 1 , 2 ,
• Lioua Kolsi   ORCID: orcid.org/0000-0003-4368-7458 1 , 3 ,
• Kaouther Ghachem 4 ,
• Mohammed Almeshaal 5 &
• Chemseddine Maatki 5  

729 Accesses

16 Citations

Explore all metrics

The evolution of materials of cutting tools and their geometry, is currently leading to a technological development of many other sectors linked to machining. It is, therefore, a progress in the construction of machine tools, the machining of new materials, improvement of cutting fluids (lower toxicity and costs related to the maintenance and treatment of used cutting fluids, chemical formulation). Regarding the cutting fluids, international regulations are moving towards eco-elimination or limiting the use of certain molecules for ecological reasons. In addition, the formulation must be adapted as best as possible to the industrial demand, both in terms of performance and costs. The characteristics of nanofluids meet all these requirements and seem to be a promising solution for major problems encountered when using conventional cutting fluids. The present paper reports a literature review emphasizing essentially the investigations performed during the last 2 years. This literature focuses on the use of nano-lubricant in machining processes such as turning, milling and grinding processes. Analyzing the current review, it has been found that the use of nanofluids especially hybrid ones reduces the tool wear, the surface roughness, cutting forces, and heat generation. However, the optimal choice of nanoparticles and their concentrations that suites more the most severe cutting conditions, needs more attention in future works.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save.

• Get 10 units per month
• Download Article/Chapter or eBook
• 1 Unit = 1 Article or 1 Chapter
• Cancel anytime

Price includes VAT (Russian Federation)

Instant access to the full article PDF.

Rent this article via DeepDyve

Institutional subscriptions

Similar content being viewed by others

Nanofluid: A Sustainable Alternative Coolant for Metalworking and Machining Operations

A comprehensive review on the application of nanofluids in the machining process

Emerging application of nanoparticle-enriched cutting fluid in metal removal processes: a review.

Alberts M, Kalaitzidou K, Melkote S (2009) An investigation of graphite nanoplatelets as lubricant in grinding. Int J Mach Tools Manuf 49:966–970

Article   Google Scholar  

Ali N, Bahman AM, Aljuwayhel NF, Ebrahim SA, Mukherjee S, Alsayegh A (2021) Carbon-based nanofluids and their advances towards heat transfer applications—a review. Nanomaterials 11(6):1628. https://doi.org/10.3390/nano11061628

Article   CAS   Google Scholar  

Ali MAM, Azmi AI, Murad MN, Zain MZM, Khalil ANM, Shuaib NA (2020) Roles of new bio-based nanolubricants towards eco-friendly and improved machinability of Inconel 718 alloys. Tribol Int 144:106106

Anand N, Kumar AS, Paul S (2019) Effect of cutting fluids applied in MQCL mode on machinability of Ti-6Al-4V. J Manuf Process 43:154–163

Anshuman D, Omprakash P, Kumar PS, Sudhansu RD, Bibhuti BB (2019) Performance appraisal of various nanofluids during hard machining of AISI 4340 steel. J Manuf Process 46:248–270

Bakalova T, Svobodová L (2019) Quality assessment of milling technology and the biocidal effects of SiO2 or TiO2 nanoadditives in cooling lubricant emulsions. J Manuf Process 45:509–519

Braga DU, Diniz AE, Miranda GWA, Coppini NL (2003) Minimum lubrication in Al-Si drilling. J Braz Soc Mech Sci Eng 25(1):63–68

Chatha SS, Pal A, Singh T (2016) Performance evaluation of aluminium 6063 drilling under the influence of nanofluid minimum quantity lubrication. J Clean Prod 137:537–545

Che Sidik NA, Samion S, Ghaderian J, Witri Muhammad Yazid MNA (2017) Recent progress on the application of nanofluids in minimum quantity lubrication machining: a review. Int J Heat Mass Transfer 108:79–89

Chetan BC, Behera S, Ghosh PVR (2016) Application of nanofluids during minimum quantity lubrication: a case study in turning process. Tribol Int 101:234–246

Choudhary A, Naskar A, Paul S (2018) An investigation on application of nano-fluids in high speed grinding of sintered alumina. J Manuf Process 35:624–633

Cui X, Li C, Zhang Y, Jia D, Zhao Y, Li R, Cao H (2019) Tribological properties under the grinding wheel and workpiece interface by using graphene nanofluid lubricant. Int J Adv Manuf Technol 104:3943–3958

Dambatta YS, Sayuti M, Sarhan AAD, Hamdi M, Manladan SM, Reddy M (2019) Tribological performance of SiO 2 -based nanofluids in minimum quantity lubrication grinding of Si 3 N 4 ceramic. J Manuf Process 41:135–147

Davim JP, Sreejith PS, Gomes R, Peixoto C (2006) Experimental studies on drilling of aluminium (AA1050) under dry, minimum quantity of lubricant, and floodlubricated conditions. Proc Inst Mech Eng B J Eng Manuf 220(10):1605–1611

De Chiffre L (2002) Surface integrity and part accuracy in reaming and tapping stainless steel with new vegetable based cutting oils. Tribol Int 58(10):865–870

Google Scholar  

De Oliveira D, Da Silva RB, Gelamo RV (2019) Influence of multilayer graphene platelet concentration dispersed in semisynthetic oil on the grinding performance of Inconel 718 alloy under various machining conditions. Wear 426–427:1371–1383

Dongzhou J, Changhe L, Yanbin Z, Min Y, Yaogang W, Shuming G, Huajun C (2017) Specific energy and surface roughness of minimum quantity lubrication grinding Ni-based alloy with mixed vegetable oil-based nanofluids. Precis Eng 50:248–262

Elhami S, Razfar MR (2020) Application of nano electrolyte in the electrochemical discharge machining process. Precis Eng 64:34–44

Gajrani KK, Suvin PS, Kailas SV, Sankar MR (2019) Thermal, rheological, wettability and hard machining performance of MoS2 and CaF2 based minimum quantity hybrid nano-green cutting fluids. J Mater Process Technol 266:125–139

Gao T, Zhang X, Li C, Zhang Y, Yang M, Jia D, Ji H, Zhao Y, Li R, Yao P, Zhu L (2020) Surface morphology evaluation of multi-angle 2D ultrasonic vibration integrated with nanofluid minimum quantity lubrication grinding. J Manuf Process 51:44–61

Garg A, Sarma S, Panda BN, Zhang J, Gao L (2016) Study of effect of nanofluid concentration on response characteristics of machining process for cleaner production. J Clean Prod 135:476–489

Ghosh CS, Rao PV (2019) Comparison between sustainable cryogenic techniques and nano-MQL cooling mode in turning of nickel-based alloy. J Clean Prod 231:1036–1049

Guan J, Ding Y, Gao C et al (2021) Experimental study on turning performance of a novel nanofluid prepared by composites of MWCNTs. Int J Adv Manuf Technol 116:2373–2385

Guangxian L, Shuang Y, Nan L, Wencheng P, Cuie W, Songlin D (2019) Quantitative analysis of cooling and lubricating effects of graphene oxide nanofluids in machining titanium alloy Ti6Al4V. J Mater Proces Tech 271:584–598

Gupta MK, Sood PK, Sharma VS (2016) Optimization of machining parameters and cutting fluids during nano-fluid based minimum quantity lubrication turning of titanium alloy by using evolutionary techniques. J Clean Prod 135(1):1276–1288

Hosseini SF, Emami M, Sadeghi MH (2018) An experimental investigation on the effects of minimum quantity nano lubricant application in grinding process of Tungsten carbide. J Manuf Process 35:244–253

Huang WT, Liu WS, Wu DH (2016) Investigations into lubrication in grinding processes using MWCNTs nanofluids with ultrasonic-assisted dispersion. J Clean Prod 137:1553–1559

Huang S, Li X, Yu B, Jiang Z, Huang H (2020) Machining characteristics and mechanism of GO/SiO 2 nanoslurries in fixed abrasive lapping. J Mater Process Tech 277:116444

Joshi KK, Behera RK, Anurag (2018) Effect of minimum quantity lubrication with Al 2 O 3 Nanofluid on Surface Roughness and its prediction using hybrid fuzzy controller in turning operation of Inconel 600. Mater Today: Proc 5:20660–20668

Junankar AA, Yashpal Y, Purohit JK (2021a) Experimental investigation to study the effect of synthesized and characterized monotype and hybrid nanofluids in minimum quantity lubrication assisted turning of bearing steel. Proc Inst Mech Eng J. https://doi.org/10.1177/13506501211038113

Junankar AA, Parate SR, Dethe PK, Dhote NR, Gadkar DG, Gadkar DD, Gajbhiye SA (2021b) Optimization of bearing steel turning parameters under CuO and ZnO nanofluid-MQL using MCDM hybrid approach. Mater Today Proceedings. https://doi.org/10.1016/j.matpr.2021.04.589

Junankar AA, Yashpal JKP et al (2021c) Performance evaluation of Cu nanofluid in bearing steel MQL based turning operation. Mater Today: Proc 44–6:4309–4314

Kakac S, Pramuanjaroenkij A (2009) Review of convective heat transfer enhancement with nanofluids. Int J Heat Mass Transfer 52:3187–3196

Khalilpourazary S, Salehi J (2019) How alumina nanoparticles impact surface characteristics of Al7175 in roller burnishing process. J Manuf Process 39:1–11

Khan AM, Gupta MK, Hegab H, Jamil M, Mia M, He N, Song Q, Liu Z, Pruncu CI (2020a) Energy based cost integrated modelling and sustainability assessment of Al-GnP hybrid nanofluid assisted turning of AISI52100 steel. J Clean Prod 257:120502

Khan AM, Jamil M, Mia M, He N, Zhao W, Gong L (2020b) Sustainability-based performance evaluation of hybrid nanofluid assisted machining. J Clean Prod 257:120541

Kim W-Y, Senguttuvan S, Kim SH, Lee SW, Kim S-M (2021) Numerical study of flow and thermal characteristics in titanium alloy milling with hybrid nanofluid minimum quantity lubrication and cryogenic nitrogen cooling. Int J Heat Mass Transfer 170:121005

Kishawy HA, Hegab H, Deiab I, Eltaggaz A (2019) Sustainability assessment during machining Ti-6Al-4V with nano-additives-based minimum quantity lubrication. J Manuf Mater Process 3:61. https://doi.org/10.3390/jmmp3030061

Kıvak T, Sarıkaya M, Yıldırım ÇV, Şirin Ş (2020) Study on turning performance of PVD TiN coated Al2O3+TiCN ceramic tool under cutting fluid reinforced by nano-sized solid particles. J Manuf Process 56:522–539

Kulkarni HB, Nadakatti MM, Kulkarni SC, Kulkarni RM (2020) Investigations on effect of nanofluid based minimum quantity lubrication technique for surface milling of Al7075-T6 aerospace alloy. Mater Today: Proc 27(1):251–256

CAS   Google Scholar  

Kumar MS, Krishna VM (2020) An investigation on turning AISI 1018 steel with hybrid biodegradeable nanofluid/MQL incorporated with combinations of CuO-Al 2 O 3 nanoparticles. Mater Today: Proc 24:1577–1584

Kumar A, Ghosh S, Aravindan S (2017) Grinding performance improvement of silicon nitride ceramics by utilizing nanofluids. Ceram Int 43–16:13411–13421

Kumar A, Ghosh S, Aravindan S (2019) Experimental investigations on surface grinding of silicon nitride subjected to mono and hybrid nanofluids. Ceram Int 45(14):17447–17466

Kumar AS, Deb S, Paul S (2020) Tribological characteristics and micro-milling performance of nanoparticle-enhanced water based cutting fluids in minimum quantity lubrication. J Manuf Process 56:766–776

Lee P-H, Kim JW, Lee SW (2018) Experimental characterization on eco-friendly micro-grinding process of titanium alloy using air flow assisted electrospray lubrication with nanofluid. J Clean Prod 201:452–462

Leep HR (1990) Influence of cutting fluids on surface finish of holes drilled into aluminum 390. J Synth Lubr 6(4):325–338

Li B, Li C, Zhang Y, Wang Y, Jia D, Yang M, Zhang N, Wu Q, Han Z, Sun K (2017) Heat transfer performance of MQL grinding with different nanofluids for Ni-based alloys using vegetable oil. J Clean Prod 154:1–11

Li M, Yu T, Zhang R, Yang L, Ma Z, Li B, Wang XZ, Wang W, Zhao J (2020) Experimental evaluation of an eco-friendly grinding process combining minimum quantity lubrication and graphene-enhanced plant-oil-based cutting fluid. J Clean Prod 244:118747

Machado AR, Wallbank J (1997) The effect of extremely low lubricant volumes in machining. Wear 210(1):76–82

Ming L, Tianbiao Y, Lin Y, Hongyu L, Rongchuang Z, Wanshan W (2019) Parameter optimization during minimum quantity lubrication milling of TC4 alloy with graphene-dispersed vegetable-oil-based cutting fluid. J Clean Prod 209:1508–1522

Mohana RG, Dilkush S, Sudhakar I, Anil Babu P (2021) Effect of cutting parameters with dry and MQL nano fluids in turning of EN-36 STEEL. Mater Today Proc 41:1182–1187

Mohd Khalil AN, Azmib AI, Murad MN, Mahboob Ali MA (2018) The effect of cutting parameters on cutting force and tool wear in machining Nickel Titanium Shape Memory Alloy ASTM F2063 under Minimum Quantity Nanolubricant. Procedia CIRP 77:227–230

Mosleh M, Ghaderi M, Shirvani KA, Belk J, Grzina DJ (2017) Performance of cutting nanofluids in tribological testing and conventional drilling. J Manuf Process 25:70–76

Musavi SH, Davoodib B, Niknam SA (2019a) Effects of reinforced nanoparticles with surfactant on surface quality and chip formation morphology in MQL-turning of superalloys. J Manuf Process 40:128–139

Musavi SH, Davoodi B, Niknam SA (2019b) Effects of reinforced nanofluid with nanoparticles on cutting tool wear morphology. J Central South Univ 26(5):1050–1064

Muthusamy Y, Kadirgama K, Rahman MM, Ramasamy D, Sharma KV (2016) Wear analysis when machining AISI 304 with ethylene glycol/TIO 2 nanoparticle-based coolant. Int J Adv Manuf Technol 82:327–340

Najiha MS, Rahman MM, Kadirgama K (2016) Performance of water-based TiO2 nanofluid during the minimum quantity lubrication machining of aluminium alloy, AA6061-T6. J Clean Prod 135:1623–1636

Najman MN, Kasrai M, Bancroft GM (2003) X-ray absorption spectroscopy and atomic force microscopy of films generated from organosulfur extreme-pressure (EP) oil additives. Tribol Lett 14(4):225–235

Nam JS, Lee PH, Lee SW (2011) Experimental characterization of micro-drilling process using nanofluid minimum quantity lubrication. Int J Mach Tools Manuf 51:649–652

Nam J, Kim JW, Kim JS, Lee J, Lee SW (2018) Parametric analysis and optimization of nanofluid minimum quantity lubrication micro-drilling process for titanium alloy (Ti-6Al-4V) using response surface methodology and desirability function. Procedia Manuf 26:403–414

Okokpujie IP, Ohunakin OS, Adelekan DS, Bolu CA, Gill J, Atiba OE, Aghedo OA (2019) Experimental investigation of nano-lubricants effects on temperature distribution of mild steel machining. Procedia Manuf 35:1061–1066

Öndin O, Kıvak T, Sarıkaya M, Yıldırım ÇV (2020) Investigation of the influence of MWCNTs mixed nanofluid on the machinability characteristics of PH 13–8 Mo stainless steel. Tribol Int 148:106323

Padmini R, Vamsi Krishna P, Krishna Mohana Rao G (2016) Effectiveness of vegetable oil based nanofluids as potential cutting fluids in turning AISI 1040 steel. Tribol Int 94:490–501

Padmini R, Krishna PV, Mohana Rao GK (2015) Performance assessment of micro and nano solid lubricant suspensions in vegetable oils during machining. Proc IMechE Part b: J Eng Manuf 229(12):1–9

Padmini R, Krishna PV, Sai M, Satish K (2019) Influence of green nanocutting fluids on machining performance using minimum quantity lubrication technique. Mater Today: Proc 18:1435–1449

Pasam VK, Revuru RS, Gugulothu S (2018) Comparing the performance & viability of nano and microfluids in minimum quantity lubrication for machining AISI1040 steel. Mater Today: Proc 5:8016–8024

Pashmforoush F, Bagherinia RD (2018) Influence of water-based copper nanofluid on wheel loading and surface roughness during grinding of Inconel 738 superalloy. J Clean Prod 178:363–372

Peña-Parás L, Maldonado-Cortésa D, Rodríguez-Villalobos M, Romero-Cantú AG, Montemayor OE, Herreraa M, Trousselle G, González J, Hugler W (2019) Optimization of milling parameters of 1018 steel and nanoparticle additive concentration in cutting fluids for enhancing multi-response characteristics. Wear 426–427:877–886

Peña-Parás L, Maldonado-Cortés D, Villalobos MR, Romero-Cantú AG, Montemayor OE (2020) Enhancing tool life, and reducing power consumption and surface roughness in milling processes by nanolubricants and laser surface texturing. J Clean Prod 253:119836

Peña-Parás L, Rodríguez-Villalobos M, Maldonado-Cortés D, Guajardo M, Rico-Medina CS, Elizondo G, Quintanilla DI (2021) Study of hybrid nanofluids of TiO2 and montmorillonite clay nanoparticles for milling of AISI 4340 steel. Wear 477:203805

Peng R, Tong J, Zhao L, Tang X, Peng X, He X (2021) Molecular dynamics study on the adsorption synergy of MWCNTs/MoS2 nanofluids and its influence of internal-cooling grinding surface integrity. Appl Surface Sci 563:150312

Prashantha Kumar ST, Thirtha Prasada HP, Nagamadhu M, Siddaraju C (2021) Investigate the effect of Al 2 O 3 & CuO nano cutting fluids under MQL technique in turning of DSS-2205. Adv Mater Process Technol. https://doi.org/10.1080/2374068X.2021.1948701

Qu S, Gong Y, Yang Y, Wang W, Liang C, Han B (2020) An investigation of carbon nanofluid minimum quantity lubrication for grinding unidirectional carbon fibre-reinforced ceramic matrix composites. J Clean Prod 249:119353

Rahman SS, Ibne Ashraf MZ, Nurul Amin AKM, Bashar MS, Kabir Ashik MF, Kamruzzaman M (2019) Tuning nanofluids for improved lubrication performance in turning biomedical grade titanium alloy. J Clean Prod 206:180–196

Rao DN, Srikant RR (2006) Influence of emulsifier content on cutting fluid properties. Proc Inst Mech Eng B 220:1803–1806

Rapeti P, Pasam VK, Rao Gurram KM, Revuru RS (2018) Performance evaluation of vegetable oil based nano cutting fluids in machining using Grey Relational Analysis-A step towards sustainable manufacturing. J Clean Prod 172:2862–2875

Reverberi AP, D’Addona DM, Bruzzone AAG, Teti R, Fabiano B (2019) Nanotechnology in machining processes: recent advances. Procedia CIRP 79:3–8

Revuru RS, Pasam VK, Syed I, Paliwal UK (2018) Development of finite element based model for performance evaluation of nano cutting fluids in minimum quantity lubrication. CIRP J Manuf Sci Technol 21:75–85

Sai Geetha CHT, Dash AK, Kavya B, Amrita M (2021) Analysis of hybrid nanofluids in machining AISI 4340 using minimum quantity lubrication. Mater Today: Proc 43:579–586

Salimi-Yasar H, Heris SZ, Shanbedi M, Amiri A, Kameli A (2017a) Experimental investigation of thermal properties of cutting fluid using soluble oil-based TiO2 nanofluid. Powder Technol 310:213–220

Salimi-Yasar H, Heris SZ, Shanbedi M (2017b) Influence of soluble oil-based TiO2 nanofluid on heat transfer performance of cutting fluid. Tribol Int 112:147–154

Sani ASA, Rahim EA, Sharif S, Sasahara H (2019) Machining performance of vegetable oil with phosphonium- and ammonium-based ionic liquids via MQL technique. J Clean Prod 209:947–964

Sarhan AAD, Sayuti M, Hamdi M (2012) Reduction of power and lubricant oil consumption in milling process using a new SiO2 nanolubrication system. Int J Adv Manuf Technol 63:505–512

Satheesh Kumar B, Padmanabhan G, Vamsi Krishna P (2016) Performance assessment of vegetable oil based cutting fluids with extreme pressure additive in machining. J Adv Res Mater Sci 19:1–13

Sen B, Gupta MK, Mia M, Mandal UK, Mondal SP (2020) Wear behaviour of TiAlN coated solid carbide end-mill under alumina enriched minimum quantity palm oil-based lubricating condition. Tribol Int 148:106310

Setti D, Sinha MK, Ghosh S, Rao PV (2015) Performance evaluation of Ti–6Al–4V grinding using chip formation and coefficient of friction under the influence of nanofluids. Int J Mach Tools Manuf 88:237–248

Sharma AK, Tiwar AK, Singha RK, Dixit AR (2016) Tribological investigation of TiO2 nanoparticle based cutting fluid in machining under minimum quantity lubrication (MQL). Mater Today: Proc 3(6):2155–2162

Sharma AK, Tiwari AK, Dixit AR, Singh RK (2017a) Investigation into performance of SiO 2 nanoparticle based cutting fluid in machining process. Mater Today: Proc 4:133–141

Sharma AK, Singh RK, Dixit AR, Tiwari AK (2017b) Novel uses of alumina-MoS2 hybrid nanoparticle enriched cutting fluid in hard turning of AISI 304 steel. J Manuf Process 30:467–482

Sharma AK, Tiwari AK, Dixit AR, Singh RK (2020) Measurement of machining forces and surface roughness in turning of AISI 304 steel using Alumina-MWCNT hybrid nanoparticles enriched cutting fluid. Measurement 150:107078

Shen B, Shih A, Tung S (2008a) Application of nanofluids in minimum quantity lubrication grinding. Tribol Trans 130(51):730–737

Shen B, Malshe AP, Kalita P, Shih AJ (2008b) Performance of novel MoS2 nanoparticles based grinding fluids in minimum quantity lubrication grinding. Trans NAMRI/SME 36:357–364

Shuang Y, John M, Songlin D (2019) Experimental investigation on the performance and mechanism of graphene oxide nanofluids in turning Ti-6Al-4V. J Manuf Process 43:164–174

Shuang Y, Jinjin L, Jiahua Z, Xiangzhi W, John M, Songlin D (2020) Investigation of machining Ti-6Al-4V with graphene oxide nanofluids: tool wear, cutting forces and cutting vibration. J Manuf Process 49:35–49

Singh H, Sharma VS, Singha S, Dogra M (2019) Nanofluids assisted environmental friendly lubricating strategies for the surface grinding of titanium alloy: Ti6Al4V-ELI. J Manuf Process 39:241–249

Singh RK, Sharma AK, Bishwajeet VM, Gaurav K, Nag A, Kumar A, Rai Dixit A, Mandal A, Das AK (2018) Influence of graphene-based nanofluid with minimum quantity lubrication on surface roughness and cutting temperature in turning operation. Mater Today: Proc 5:24578–24586

Singh RK, Sharma AK, Dixit AR, Tiwari AK, Pramanik A, Mandal A (2017) Performance evaluation of alumina-graphene hybrid nano-cutting fluid in hard turning. J Clean Prod 162:830–845

Singh H, Sharma VS, Dogra M (2020) Exploration of graphene assisted vegetables oil based minimum quantity lubrication for surface grinding of TI-6AL-4V-ELI. Tribol Int 144:106113

Sinha MK, Madarkar R, Ghosh S, Venkateswara Rao P (2017) Application of eco- friendly nanofluids during grinding of Inconel 718 through small quantity lubrication. J Clean Prod 141:1359–1375

Sirin E, Kıvak T, Yıldırım ÇV (2021a) Effects of mono/hybrid nanofluid strategies and surfactants on machining performance in the drilling of Hastelloy X. Tribol Int 157:106894

Sirin S, Sarıkaya M, Vakkas Yıldırım Ç, Kıvak T (2021b) Machinability performance of nickel alloy X-750 with SiAlON ceramic cutting tool under dry, MQL and hBN mixed nanofluid-MQL. Tribol Int 153:106673

Şirin Ş, Kıvak T (2019) Performances of different eco-friendly nanofluid lubricants in the milling of Inconel X-750 superalloy. Tribol Int 137:180–192

Sirin S, Kıvak T (2021) Effects of hybrid nanofluids on machining performance in MQL-milling of Inconel X-750 superalloy. J Manuf Process 70:163–176

Surendra DB, Aman K, Sandesh SC, Deepak RU (2021) Investigating a novel Ag/ZnO based hybrid nanofluid for sustainable machining of inconel 718 under nanofluid based minimum quantity lubrication. J Manuf Process 66:313–324

Tiwari A, Agarwal D, Singh A (2021) Computational analysis of machining characteristics of surface using varying concentration of nanofluids (Al 2 O 3 , CuO and TiO 2 ) with MQL. Mater Today: Proc 42:1262–1269

Vamsi Krishna P, Srikant RR, Nageswara Rao D (2010) Experimental investigation on the performance of nanoboric acid suspensions in SAE-40 and coconut oil during turning of AISI 1040 steel. Int J Mach Tools Manuf 50:911–916

Venkatesan K, Devendiran S, Ghazaly NM, Nishanth (2019a) Application of Taguchi-Response surface analysis to optimize the cutting parameters on turning of Inconel X-750 using Nanofluids suspended Al 2 O 3 in coconut oil. Procedia Manuf 30:90–97

Venkatesan K, Mathew AT, Devendiran S, Ghazaly NM, Sanjith S, Raghul R (2019b) Machinability study and multi-response optimization of cutting force, Surface roughness and tool wear on CNC turned Inconel 617 superalloy using Al 2 O 3  Nanofluids in Coconut oil. Procedia Manuf 30:396–403

Venkatesan K, Devendiran S, Ghazaly NM, Rahul R, Mughilan T (2019c) Optimization of cutting parameters on turning of incoloy 800H using Al2O3 nanofluid in coconut oil. Procedia Manuf 30:268–275

Venkatesan K, Devendiran S, Ghazaly NM, Nishanth (2019d) Application of Taguchi-Response surface analysis to optimize the cutting parameters on turning of Inconel X-750 using Nanofluids suspended Al 2 O 3 in coconut oil. Procedia Manufacturing 30:90–97

Venkatesan K, Devendiran S, Sachin D, Swaraj J (2020) Investigation of machinability characteristics and comparative analysis under different machining conditions for sustainable manufacturing. Measurement 154:107425

Virdi RL, Chatha SS, Singh H (2020) Performance evaluation of Inconel 718 under vegetable oils based nanofluids using minimum quantity lubrication grinding. Mater Today: Proc. https://doi.org/10.1016/j.matpr.2020.03.802

Wang Y, Li C, Zhang Y, Yang M, Zhang X, Zhang N, Dai J (2017a) Experimental evaluation on tribological performance of the wheel/workpiece interface in minimum quantity lubrication grinding with different concentrations of Al 2 O 3 nanofluids. J Clean Prod 142–4:3571–3583

Wang Y, Li C, Zhang Y, Li B, Yang M, Zhang X, Guo S, Liu G, Zhai M (2017b) Comparative evaluation of the lubricating properties of vegetable-oil-based nanofluids between frictional test and grinding experiment. J Manuf Process 26:94–104

Yıldırım ÇV (2019) Experimental comparison of the performance of nanofluids, cryogenic and hybrid cooling in turning of Inconel 625. Tribol Int 137:366–378

Yıldırım ÇV, Sarıkaya M, Kıvak T, Şirin Ş (2019) The effect of addition of hBN nanoparticles to nanofluid-MQL on tool wear patterns, tool life, roughness and temperature in turning of Ni-based Inconel 625. Tribol Int 134:443–456

Zhang X, Li C, Zhang Y, Wang Y, Li B, Yang M, Guo S, Liu G, Zhang N (2017) Lubricating property of MQL grinding of Al2O3/SiC mixed nanofluid with different particle sizes and microtopography analysis by cross-correlation. Precis Eng 47:532–545

Zhang J, Li C, Zhang Y, Yang M, Jia D, Liu G, Hou Y, Li R, Zhang N, Wu Q, Cao H (2018) Experimental assessment of an environmentally friendly grinding process using nanofluid minimum quantity lubrication with cryogenic air. J Clean Prod 193:236–248

Zhang Y, Li C, Jia D, Li B, Wang Y, Yang M, Hou Y, Zhang X (2016) Experimental study on the effect of nanoparticle concentration on the lubricating property of nanofluids for MQL grinding of Ni-based Alloy. J Mater Process Technol 232:100–115

Zhang L, Guo X, Zhang K, Wu Y, Huang Q (2020) Enhancing cutting performance of uncoated cemented carbide tools by jointuse of magnetic nanofluids and micro-texture under magnetic field. J Mater Process Tech 284:116764

Zhou C, Guo X, Zhang K, Cheng L, Wu Y (2019a) The coupling effect of micro-groove textures and nanofluids on cutting performance of uncoated cemented carbide tools in milling Ti-6Al-4V. J Mater Process Tech 271:36–45

Zhou R, Fu S, Li H, Yuan D, Tang B, Zhou G (2019b) Experimental study on thermal performance of copper nanofluids in a miniature heat pipe fabricated by wire electrical discharge machining. Appl Thermal Eng 160:113989

Download references

Acknowledgements

This research was funded by the Deanship of Scientific Research at Princess Nourah bint Abdulrahman University through the Fast-track Research Funding Program.

Author information

Authors and affiliations.

Mechanical Engineering Department, College of Engineering, Ha’il University, Ha’il City, Saudi Arabia

Lotfi Ben Said & Lioua Kolsi

Laboratory of Electro-Mechanical Systems (LASEM), National Engineering School of Sfax, University of Sfax, 3038, Sfax, Tunisia

Lotfi Ben Said

Laboratory of Metrology and Energy Systems, National Engineering School, University of Monastir, Monastir, Tunisia

Lioua Kolsi

Department of Industrial Engineering and Systems, College of Engineering, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia

Kaouther Ghachem

Department of Mechanical Engineering, College of Engineering, Imam Mohammad Ibn Saud Islamic University, Riyadh, 11432, Saudi Arabia

Mohammed Almeshaal & Chemseddine Maatki

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Lioua Kolsi .

Ethics declarations

Conflict of interest.

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Ben Said, L., Kolsi, L., Ghachem, K. et al. Application of nanofluids as cutting fluids in machining operations: a brief review. Appl Nanosci 13 , 4247–4278 (2023). https://doi.org/10.1007/s13204-021-02140-8

Download citation

Received : 03 February 2021

Accepted : 03 October 2021

Published : 03 February 2022

Issue Date : June 2023

DOI : https://doi.org/10.1007/s13204-021-02140-8

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Nano-lubricant
• Nanoparticle
• Find a journal
• Publish with us
• Track your research