electrical conductivity of ionic and covalent compounds experiment

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Which substances conduct electricity?

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In this class practical, students test the conductivity of covalent and ionic substances in solid and molten states

This experiment enables students to distinguish between electrolytes and non-electrolytes, and to verify that covalent substances never conduct electricity even when liquefied, whereas ionic compounds conduct when molten.

The practical works well as a class experiment, with students working in groups of two to three. There will not be time to investigate all the substances, so each group could be assigned three or four of these, and the results pooled at the end.

• Eye protection
• Carbon (graphite) electrodes, fitted in a holder (see note 1 below)
• Bunsen burner
• Pipeclay triangle
• Heat resistant mat
• Clamp and stand
• Small pieces of emery paper
• Connecting leads and crocodile clips
• DC power pack, 6 V
• Light bulb in holder, 6 V (see note 2 below)

Apparatus notes

• The carbon electrodes need to be fixed in some sort of support – such as a polythene holder or large rubber bung – so that there is no possibility of the electrodes being allowed to short-circuit. The electrodes need to be fixed in such a way as to fit inside the crucible supplied.
• A light bulb has more visual impact, but an ammeter can be used instead.
• Small pieces of lead (TOXIC), copper and perhaps other metals
• Phenylsalicylate (salol) (IRRITANT, DANGEROUS FOR THE ENVIRONMENT)
• Zinc chloride (CORROSIVE, DANGEROUS FOR THE ENVIRONMENT)
• Potassium iodide
• Sulfur (optional)

Health, safety and technical notes

• Read our standard health and safety guidance.
• Wear eye protection throughout.
• Lead, Pb(s), (TOXIC) – see CLEAPSS Hazcard HC056 .
• Copper, Cu(s) – see CLEAPSS Hazcard HC026 . 
• Phenylsalicylate (salol), C 6 H 4 (OH)COOC 6 H 5 (s), (IRRITANT, DANGROUS FOR THE ENVIRONMENT) – see CLEAPSS Hazcard HC052 . 
• Wax – see CLEAPSS Hazcard HC045b . 
• Sugar (sucrose), C 12 H 22 O 11 (s) – see CLEAPSS Hazcard HC040c . 
• Zinc chloride, ZnCl 2 (s) (CORROSIVE, DANGEROUS FOR THE ENVIRONMENT) – see CLEAPSS Hazcard HC108a . 
• Potassium iodide, KI(s) - see CLEAPSS Hazcard HC047b . 
• Sulfur, S 8 (s) – see CLEAPSS Hazcard HC096A . Sulfur is a non-metallic element and is a good substance to have included in the list. But there is a strong likelihood of it catching fire, with sulfur dioxide, SO 2 (g), (TOXIC), given off. Sulfur fires are hard to extinguish. If it happens, cover the vessel with a damp cloth and leave in place until cool. If there is time, sulfur can be done as a teacher demonstration. Heat a small sample of ‘flowers of sulfur’ very, very slowly. Sulfur is a very poor conductor of heat, and localised heating is likely to cause it to start burning! You must use a fume cupboard.
• Set up the circuit as shown in the diagram, at this stage do not include the crucible or bunsen burner flame (these are for later).

Source: Royal Society of Chemistry

The apparatus required for testing the conductivity of different substances when solid and molten

• Select one of the metals, and by holding the electrodes in contact with it, find out whether or not it conducts electricity then switch the current off.
• Note down the results using the student sheet available with this resource (see download links below) and repeat this experiment with each metal available.
• Select one of the solids contained in a crucible. Lower the electrodes so that they are well immersed in the solid, and then clamp the electrodes in position.
• Switch on the current and find out whether the solid conducts electricity or not, then switch the current off again.
• Set the crucible over a Bunsen burner on a pipeclay triangle and tripod, and clamp the electrodes in position over the crucible. Gently heat the sample until it just melts, and then turn off the Bunsen flame. If necessary lower the electrodes into the molten substance, before clamping them again.
• Switch on the current again. Does the molten substance conduct electricity now? Switch the current off again.
• Write up all your observations.
• Raise the electrodes from the crucible, and allow them to cool.
• Clean the electrodes with emery paper.

Repeat steps 4 to 10 with some or all of the other solids.

Pool your results with other groups so that your table is complete.

Teaching notes

The covalent solids only need to be heated for a short time for melting to take place. Under no circumstances should heating be prolonged, otherwise the substances may decompose and/or burn. The students should be warned about what to do if this happens eg cover with a damp cloth. The experiments should be done in a well-ventilated laboratory.

It may be helpful to reserve a crucible for each of the powdered compounds, while having one or two others that can be heated. Once a solid has been liquefied and allowed to cool, the solidified lump is often hard to break up or powder in the crucible.

Zinc chloride melts at about 285 °C, so heating needs to be fairly prolonged in comparison with the covalent solids. It will, however, produce chlorine (TOXIC) so heating should stop as soon as conductivity is detected. Potassium iodide melts at about 675 °C, so very strong and prolonged heating is needed here.

Student questions

• What do you conclude about the electrical conductivity of metals?
• Do all of the solid compounds conduct electricity?
• Do any of the molten compounds conduct electricity. If so, which ones?
• Why do some substances conduct only when they have been liquefied?
• Can you now classify all the compounds as being either ionic or covalent?
• All the metals conduct electricity well. You should explain this conductivity in terms of the ‘free’ electrons within a metallic structure.
• No, none of them.
• Yes, zinc chloride and potassium iodide.
• Some substances are ionic, but electrical conduction is only possible when the ions are free and mobile. This happens once the solid has been melted.
• Phenylsalicylate, polythene, wax and sugar are covalent. Zinc chloride and potassium iodide are ionic.

Which substances conduct electricity? worksheet

Additional information.

This is a resource from the  Practical Chemistry project , developed by the Nuffield Foundation and the Royal Society of Chemistry.

Practical Chemistry activities accompany  Practical Physics and  Practical Biology .

© Nuffield Foundation and the Royal Society of Chemistry

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Specification

• 2.7.2 predict the products of electrolysis of molten salts including lithium chloride and lead(II) bromide using graphite electrodes and state appropriate observations at the electrodes.
• 2.7.3 interpret and write half equations for the reactions occurring at the anode and cathode for the electrolysis processes listed in 2.7.2, for other molten halides and in the extraction of aluminium;
• These substances do not conduct electricity because the molecules do not have an overall electric charge.
• Metals are good conductors of electricity because the delocalised electrons in the metal carry electrical charge through the metal.
• When melted or dissolved in water, ionic compounds conduct electricity because the ions are free to move and so charge can flow.
• Explain how the bulk properties of materials are related to the different types of bonds they contain, their bond strengths in relation to intermolecular forces and the ways in which their bonds are arranged, recognising that the atoms themselves do not…
• Explain how the bulk properties of materials are related to the different types of bonds they contain, their bond strengths and the ways in which their bonds are arranged, recognising that the atoms themselves do not have these properties.
• 1.32 Explain why elements and compounds can be classified as: ionic, simple molecular (covalent), giant covalent, metallic, and how the structure and bonding of these types of substances results in different physical properties, including relative…
• C2.3f explain how the bulk properties of materials (ionic compounds; simple molecules; giant covalent structures; polymers and metals) are related to the different types of bonds they contain, their bond strengths in relation to intermolecular forces and…
• C4.3.1 explain how the bulk properties of materials (including strength, melting point, electrical and thermal conductivity, brittleness, flexibility, hardness and ease of reshaping) are related to the different types of bonds they contain, their bond st…
• C4.2.1 explain how the bulk properties of materials (including strength, melting point, electrical and thermal conductivity, brittleness, flexibility, hardness and ease of reshaping) are related to the different types of bonds they contain, their bond st…
• In general, covalent network substances do not conduct electricity. This is because they do not have charged particles which are free to move.
• Ionic compounds conduct electricity only when molten or in solution as the lattice structure breaks up allowing the ions to be free to move.
• (a) the properties of metals, ionic compounds, simple molecular covalent substances and giant covalent substances

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• Conduction Of Electricity

Electricity and Conduction of Electricity

All substances are made up of atoms, which have charged particles called electrons and protons. These charged particles have a negative and a positive charge respectively. Electricity in all forms is a result of this charge on the fundamental particles. Conduction of electricity is the movement of the charged particles in an organized manner resulting in a net movement of charge through the material. When charged particles move in an orderly fashion, we get an electric current.

Table of Content

Conduction of Electricity in Liquids Conduction of Electricity in Substances Ionic and Covalent Compounds

Conduction of Electricity in Liquids

Metals conduct electricity by means of mobile electrons. The outermost electrons in metals are loosely held due to which they can move from atom to atom. This is why metals are excellent conductors of electricity. Liquids, on the other hand, conduct electricity by other means. Unlike in metals, the chemical bonding in liquids does not allow for electrons to move freely. This means we have to introduce charges into the water before it can start conducting. Certain compounds (ionic Compounds)dissolve in water, they do so by dissociating or breaking up their bonds. When the bond is broken, the components of the compound break apart to yield multiple constituent atoms with a charge on them. The atom that loses an electron(s) has more protons than electrons and similarly an atom that gains electrons have more electrons than protons. This leads to a charge imbalance leading to a positive or a negative charge on the atom. The atom that becomes charged by losing or gaining one or more electrons is called an Ion.

Conduction of Electricity in Substances

Let’s use an experimental setup to understand the flow of electricity through various liquids. We know that electricity is the movement of charged particles through the body. In solids like metals, the electrons are loosely bound to the atoms due to which electrons can move freely from atom to atom in a metal object. This mobility of electrons allows us to pass an electric current through it. If we can pass an electric current through objects easily, we call them Good conductors of electricity. Materials that do not allow the flow of electricity through it are called insulators. The only liquid elements which conduct electricity are liquid metals and the only metal liquid at room temperature is Mercury. This experiment helps us identify how exactly electricity is conducted through a liquid.

Getting back to the experimental setup. This setup is used to test the conduction of electricity in a substance. This setup consists of an electric circuit connected to a glass lamp attached to a voltage source to power this lamp like a battery. There is a discontinuity in the circuit in the form of an intentional break in it. This breakage is replaced with two electrodes that can be dipped into substances to examine the nature of electrical conduction through the body.

When the electrodes are dipped into a conducting substance like mercury, the current flows from the circuit, from the electrode into the conducting material and from there on to the other electrode and then to the bulb thereby completing the circuit. If the bulb glows it means that the substance is conducting. In a non-conducting substance, the current is unable to flow from the electrode to the substance thereby breaking the circuit. The lamp, in this case, stays off. This experiment is mainly conducted to check the conductivity of solutions. If the lamp lights up, the solution conducts electricity. If the lamp is dim it means that it conducts very little electricity. Let’s see the results of this experiment for various common solutions.

From the experiment, we deduce that there is something in salt that enables the conduction of electricity in a solution. This means that we must dive into what enables it to do so. The answer is Ions. Learn about ionic and covalent compounds and how electricity is conducted in another article. Find out more in the link mentioned below.

One should also bear in mind that normal tap water has many compounds dissolved in it which we term as Hardness. The conductivity depends largely on this and therefore conductivity of tap water may vary from place to place. From this experiment, we found out which solutions conduct electricity and which don’t but what is the mechanism of conduction of electricity in liquids. Learn more about why certain solutions conduct and some don’t. Learn the science behind everything you see around you with BYJU’S. Join us and fall in love with learning.

Ionic and Covalent Compounds

The creation of ions in a solution is largely decided by the nature of chemical bonding between the atoms of the compound. Covalent compounds are usually made from non-metal elements which are bonded by bonds where electrons are shared. Since electrons are shared in covalent bonds they cannot separate into charged ions in a solution. Ionic compounds are compounds made of charged particles (ions). The positive ions are formed by metals having lost one or more electrons. The negative ions are formed by non-metals gaining one or more extra electrons. Positive and negative ions attract each other and combine with each other to yield ionic compounds. Ions carrying opposite charges tend to attract and hold on to each other. This leads to the formation of compounds called ionic compounds. For example, a sodium atom may lose an electron, which is gained by a chlorine atom. Thus, a positively charged sodium ion (Na+) and a negatively charged chloride ion (CI–) are formed. These come together to form the ionic compound NaCl.

Some more examples of ions and their ionic compounds are;

Ionic compounds, unlike covalent compounds, do not share electrons due to which they can dissociate into their component ions. Since Ions form the ionic bonds, they still retain the charge, i.e. the positive and the negative charge on the ions is permanent. Due to this charge separation, water can easily strike at the bonds and separate the positive and the negative ions. This is what we call dissolution of a substance. When an ionic compound is dissolved in water, it splits into its component ions. When common salt (NaCl) is dissolved in water, it splits into Na + and Cl – ions. When an electric potential is applied to this solution with ions, the ions migrate towards oppositely charged electrodes to complete the electric circuit whereas the neutral molecules do not respond to the potential. Thus, solutions that contain ions conduct electricity, while solutions that contain only neutral molecules do not. Electrical current will flow through the circuit shown and the bulb will glow only if ions are present. The lower the concentration of ions in the solution, the weaker the current and the dimmer the glow of the bulb. The movement of ions is essential for the conduction of electricity through liquids. Pure water, for example, contains only very low concentrations of ions, so it is a poor electrical conductor. Saltwater like seawater, on the other hand, contains a lot of dissolved ionic compounds that split into ions in the solution. These ions then help in the conduction of electricity. Therefore, saltwater is a good conductor of electricity due to the presence of ions in the solution.

The below video helps to revise the chapter Electricity Class 10

Frequently Asked Questions – FAQs

What are conductors, what are insulators, define electric current., why is direct current, what is static electricity.

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Properties of Ionic and Covalent Compounds

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If you know the chemical formula of a compound, you can predict whether it contains ionic bonds, covalent bonds, or a mixture of bond types. Nonmetals bond to each other via covalent bonds while oppositely charged ions, such as metals and nonmetals, form ionic bonds . Compounds which contain polyatomic ions may have both ionic and covalent bonds .

Key Takeaways: Properties of Ionic and Covalent Compounds

• One way of classifying chemical compounds is by whether they contain ionic bonds or covalent bonds.
• For the most part, ionic compounds contain a metal bonded to a nonmetal. Ionic compounds form crystals, typically have high melting and boiling points, are usually hard and brittle, and form electrolytes in water.
• Most covalent compounds consist of nonmetals bonded to one another. Covalent compounds usually have lower melting and boiling points than ionic compounds, are softer, and are electrical insulators.

Identifying Bond Types

But, how do you know if a compound is ionic or covalent just by looking at a sample? This is where the properties of ionic and covalent compounds can be useful. Because there are exceptions, you need to look at several properties to determine whether a sample is ionic or covalent, but here are some characteristics to consider:

• Crystals : Most crystals are ionic compounds . This is because the ions in these compounds tend to stack into crystal lattices to balance between the attractive forces between opposite ions and the repulsive forces between like ions. Covalent or molecular compounds can exist as crystals, though. Examples include sugar crystals and diamond.
• Melting and boiling points : Ionic compounds tend to have higher melting and boiling points than covalent compounds.
• Mechanical properties : Ionic compounds tend to be hard and brittle while covalent compounds tend to be softer and more flexible.
• Electrical conductivity and electrolytes : Ionic compounds conduct electricity when melted or dissolved in water while covalent compounds typically don't. This is because covalent compounds dissolve into molecules while ionic compounds dissolve into ions, which can conduct charge. For example, salt (sodium chloride) conducts electricity as molten salt or in salt water. If you melt sugar (a covalent compound) or dissolve it on water, it won't conduct.

Examples of Ionic Compounds

Most ionic compounds have a metal as the cation or first part of their formula, followed by one or more nonmetals as the anion or second part of their formula. Here are some examples of ionic compounds:

• Table salt or sodium chloride (NaCl)
• Sodium hydroxide (NaOH)
• Chlorine bleach or sodium hypochlorite (NaOCl)

Examples of Covalent Compounds

Covalent compounds consist of nonmetals bonded to each other. These atoms have identical or similar electronegativity values, so the atoms essentially share their electrons. Here are some examples of covalent compounds:

• Water (H 2 O)
• Ammonia (NH 3 )
• Sugar or sucrose (C 12 H 22 O 11 )

Why Do Ionic and Covalent Compounds Have Different Properties?

The key to understanding why ionic and covalent compounds have different properties from each other is understanding what's going on with the electrons in a compound. Ionic bonds form when atoms have different electronegativity values from each other. When the electronegativity values are comparable, covalent bonds form.

But, what does this mean? Electronegativity is a measure of how easily an atom attracts bonding electrons. If two atoms attract electrons more or less equally, they share the electrons. Sharing electrons results in less polarity or inequality of charge distribution. In contrast, if one atom attracts bonding electrons more strongly than the other, the bond is polar.

Ionic compounds dissolve in polar solvents (like water), stack neatly on each other to form crystals, and require a lot of energy for their chemical bonds to break. Covalent compounds can be either polar or nonpolar, but they contain weaker bonds than ionic compounds because they are sharing electrons. So, their melting and boiling points are lower and they are softer.

• Bragg, W. H.; Bragg, W. L. (1913). "The Reflection of X-rays by Crystals". Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences . 88 (605): 428–438. doi:10.1098/rspa.1913.0040
• Langmuir, Irving (1919). "The Arrangement of Electrons in Atoms and Molecules". Journal of the American Chemical Society . 41 (6): 868–934. doi:10.1021/ja02227a002
• McMurry, John (2016). Chemistry (7th ed.). Pearson. ISBN 978-0-321-94317-0.
• Sherman, Jack (August 1932). "Crystal Energies of Ionic Compounds and Thermochemical Applications". Chemical Reviews . 11 (1): 93–170. doi:10.1021/cr60038a002
• Weinhold, F.; Landis, C. (2005). Valency and Bonding . Cambridge. ISBN 0-521-83128-8.
• Covalent or Molecular Compound Properties
• Physical Properties of Matter
• Ionic vs. Covalent Bonds: How Are They Different?
• Examples of Polar and Nonpolar Molecules
• Ionic Compound Properties, Explained
• Chemical Properties and Physical Properties
• Metallic Bond: Definition, Properties, and Examples
• Compounds With Both Ionic and Covalent Bonds
• Examples of Ionic Bonds and Compounds
• What Are Some Examples of Covalent Compounds?
• The 6 Main Types of Solids
• Molecular Solids: Definition and Examples
• Formulas of Ionic Compounds
• General Chemistry Topics
• What Is a Crystal?
• Sodium Chloride: The Molecular Formula of Table Salt

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• Published: 14 August 2024

Anomalous lattice thermal conductivity increase with temperature in cubic GeTe correlated with strengthening of second-nearest neighbor bonds

• Samuel Kielar 1   na1 ,
• Chen Li   ORCID: orcid.org/0000-0003-2336-9524 1 , 2   na1 ,
• Han Huang   ORCID: orcid.org/0000-0001-8070-3731 1 ,
• Renjiu Hu   ORCID: orcid.org/0000-0003-4651-3349 1 ,
• Carla Slebodnick   ORCID: orcid.org/0000-0003-4188-7595 3 ,
• Ahmet Alatas   ORCID: orcid.org/0000-0001-6521-856X 4 &
• Zhiting Tian   ORCID: orcid.org/0000-0002-5098-7507 1  

Nature Communications volume  15 , Article number:  6981 ( 2024 ) Cite this article

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• Atomistic models
• Mechanical engineering
• Phase transitions and critical phenomena
• Semiconductors
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Understanding thermal transport mechanisms in phase change materials is critical to elucidating the microscopic picture of phase transitions and advancing thermal energy conversion and storage. Experiments consistently show that cubic phase germanium telluride (GeTe) has an unexpected increase in lattice thermal conductivity with rising temperature. Despite its ubiquity, resolving its origin has remained elusive. In this work, we carry out temperature-dependent lattice thermal conductivity calculations for cubic GeTe through efficient, high-order machine-learned models and additional corrections for coherence effects. We corroborate the calculated phonon properties with our inelastic X-ray scattering measurements. Our calculated lattice thermal conductivity values agree well with experiments and show a similar increasing trend. Through additional bonding strength calculations, we propose that a major contributor to the increasing lattice thermal conductivity is the strengthening of second-nearest neighbor interactions. The findings herein serve to deepen our understanding of thermal transport in phase-change materials.

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Introduction.

A solid grasp of thermal phonon dynamics in phase change materials is critical to better understanding the phase transition mechanism and engineering materials for thermal energy conversion and storage. Over the past decade, detailed first-principles phonon calculations based on density functional theory (DFT) at 0 K and three-phonon scattering 1 , 2 have become routine. These traditional methods, however, have been proven difficult near phase transitions and at high temperatures due to the structural instabilities at 0 K and increased higher-order anharmonic interactions. Despite further developments of four-phonon scattering 3 , temperature-dependent effective potential (TDEP) 4 , 5 , self-consistent phonon theory 6 , the stochastic self-consistent harmonic approximation (SSCHA) 7 , 8 , and unified theory 9 , phase change materials remain largely unexplored because of the computational constraints in efficiently combining temperature effects with higher-order phonon scattering. This significantly impedes our understanding of phonon dynamics and thermal conductivity in phase change materials.

Germanium telluride (GeTe) provides an excellent yet challenging platform to study thermal transport behavior near temperature-induced phase transitions. The proximity to dynamic instability and the unique bonding characteristics of IV–VI materials further complicate the thermal transport picture. GeTe undergoes a structural phase transition from the rhombohedral to the cubic crystal structure near 650 K depending on the carrier concentration 10 , 11 , 12 , 13 , setting it apart from other IV–VI materials, and is attractive for phase change applications such as phase change memory cells 14 . In addition, GeTe is a prime candidate for thermoelectric applications and is considered a potential replacement for toxic lead telluride (PbTe)-based materials, with a high ZT value of up to \(2.5\) at around 700 K 15 . GeTe has also shown potential for spintronic devices due to its strong spin-orbit coupling and Rashba effect 16 . The lattice thermal conductivity of GeTe plays a crucial role in the aforementioned applications. Therefore, a sophisticated, atomic-scale picture of lattice thermal conductivity of cubic GeTe will not only advance our fundamental understanding of lattice dynamics near crystalline-to-crystalline phase-changes in general but also serve as the solid foundation for optimizing its performance in real applications.

Interestingly, experimental data from multiple independent groups all show an unexpectedly increasing trend for the lattice thermal conductivity of high-temperature phase cubic GeTe 17 , 18 , 19 , 20 , 21 , 22 . This challenges the conventional wisdom that at high temperatures, the lattice thermal conductivity of crystalline materials typically decreases with temperature, attributed to enhanced phonon-phonon scattering. Theoretical and computational studies are, however, scarce, leaving this abnormal trend yet to be explained. Fortunately, ML algorithms in the form of advanced linear regression have been recently applied to thermal transport modeling in crystals, which can account for finite temperature effects while extracting higher-order interatomic force constants (IFCs) with much greater efficiency 23 . However, applications of these algorithms to phase change materials are still in their infancy. To the best of our knowledge, only one study included the quartic IFCs for cubic GeTe at one temperature (800 K) 24 . The scarcity of computational data and the lack of temperature-dependent computational studies compel us to conduct this study to uncover the mystery of the experimental trend.

Herein, we carry out a thorough study of thermal transport in cubic GeTe, combining machine learning (ML)-assisted first-principles calculations and inelastic X-ray measurements (Fig.  1a ). The computational approach in this study integrates considerations of temperature dependence, four-phonon scattering, and the coherence contribution, which is among the highest levels of theory so far 25 , 26 , 27 , 28 . More specifically, we use Bayesian Ridge (BR) regression to train linear models of thermalized force-displacement data generated from first-principles calculations at 693 K and higher. We efficiently extract the IFCs up to the fourth order, allowing us to consider the effects of temperature-dependent IFCs and four-phonon scattering. Additionally, by extending the unified theory 9 to embrace the real-space displacement approach, we provide a first look into coherence effects in a high-temperature phase and with four-phonon scattering included. We corroborate the computational phonon dispersion and lifetimes with the first inelastic X-ray scattering (IXS) measurements of cubic GeTe at 693 K. This work provides a general computational framework to study a wide range of phase change materials.

The schematic of this work is where we ( a ) carried out integrated computational and experimental work to better understand the thermal transport properties of cubic GeTe. Using machine-learned IFCs and developing the real-space displacement approach for the unified theory, we were able to include effects from high temperatures, four-phonon scattering, and coherence ( b ) converted from a plane wave basis to a localized basis composed of pseudo-atomic orbitals (PAOs) to investigate pairwise bonding in cubic GeTe.

Remarkably, our lattice thermal conductivity calculations reproduce the increasing trend in temperature-dependent thermal conductivity that was universally observed across different experiments. This abnormal, strongly increasing trend awaits demystification, which motivated us to perform temperature-dependent interatomic bonding calculations (Fig.  1b ). We correlate this unusual thermal conductivity trend in cubic phase GeTe to its peculiar interatomic bonding behavior, which are known to be unique for IV–VI materials generally. Specifically, we posit that this temperature-dependent bond strengthening between second-nearest neighbors, namely Ge-Ge and Te-Te bonds along the <110> direction, substantially contributes to the increasing thermal conductivity. This study not only offers the first insights into the unusual temperature dependence of thermal conductivity in cubic GeTe but also offers a new perspective of thermal transport near phase transitions in general.

Results and discussions

At 693 K, the X-ray diffraction (XRD) pattern of our GeTe sample shows that it has completed the phase transition from the rhombohedral to the cubic phase (Fig.  2a ). More details can be found in SI. The calculated phonon dispersion at 693 K using renormalized harmonic IFCs fitted via BR regression is shown in Fig.  2b , where the higher order terms were renormalized onto the harmonic IFCs to prevent the imaginary frequencies indicative of an unstable structure. A cutoff of 10.5 Å was applied to include the long-range interactions. Our experimental phonon dispersion from IXS is also plotted in Fig.  2b . The calculated phonon frequencies agree well with those measured by IXS. The phonon dispersion of cubic GeTe is similar to that of IV–VI family, such as PbTe 29 , SnTe 30 , and SnSe 31 , which share the same space group of Fm3m. The phonon lifetimes of the acoustic and optical phonon modes of cubic GeTe at 693 K, extracted by IXS and calculated using both third- and fourth-order IFCs, are shown in Fig.  2c . The lifetimes exhibit an ω −2 dependence in the low-frequency range. Notably, including four-phonon processes significantly improves agreement with the experimental data, especially for the frequency range between 1 and 3.5 THz, the primary heat carriers, as shown in Fig.  2d . This suggests that including four-phonon scattering is essential. The comparison between calculations and experiment validates the accuracy of our ML-trained models from first-principles calculations.

a GeTe undergoes a phase transition from the rhombohedral to cubic crystal structure around 650 K. b Calculated and measured phonon dispersion of GeTe single crystal at 693 K show good agreement. c Calculated and measured phonon lifetimes of GeTe at 693 K. The results follow a rough 1/ω 2 trend, shown by the dark blue dashed line. The shaded region highlights the overestimation of lifetimes if only three-phonon is considered. d Spectral thermal conductivity contribution at 693 K indicates that the main contributors are between 1 and 3.5 THz.

We then calculated the lattice thermal conductivity as a function of temperature by using the IFCs as input to solve the phonon Boltzmann transport equation (BTE). A comparison between our calculated lattice thermal conductivities 32 and experimental data from the literature 17 , 18 , 19 , 20 , 21 , 22 and those from others’ TDEP calculations 33 are shown in Fig.  3a ,  b , respectively. Although TDEP with three-phonon scattering was able to match well with the experimental data of the rhombohedral phase, it drastically overestimated the thermal conductivity in the cubic phase. Our calculations with only three phonon scattering are in the same ballpark as TDEP. A more detailed comparison can be found in SI. However, by including four-phonon scattering, the thermal conductivity dropped by roughly half and fell into the experimental window 33 , and the good agreement holds for all other temperatures we calculated. This is further evidence that four-phonon scattering is vital for modeling thermal transport in cubic GeTe.

a Lattice thermal conductivity of GeTe at various temperatures according to experiment (hollow triangular markers and yellow shaded region) 17 , 18 , 19 , 20 , 21 , 22 and our calculations. The gray area indicates the transition temperature range of GeTe 33 . Temperature-dependent lattice thermal conductivity measurements of PbTe 34 and PbSe 32 from the literature are also shown for comparison. b Lattice thermal conductivity of GeTe previously calculated via TDEP with three-phonon scattering 33 (hollow rectangular markers) along with our calculations using BR-trained third-order IFCs (pink-filled circular markers), our calculations using BR-trained third- and fourth-order IFCs (magenta circular markers), and the latter with added corrections from coherence (dark red circular markers). The inset shows the contribution to thermal conductivity by coherence with both three- and four-phonon scattering included.

We also accounted for the effect of coherence by modifying the unified theory to adopt the finite difference approach and to include four-phonon scattering rates. The coherence contribution is minor compared to the particle-like transport, similar to prior calculations on Tl 3 VSe 4 25 . Specifically, the coherence only increases total thermal conductivity by 1–2% (Fig.  3 inset), although including fourth-order phonon scattering leads to an increased broadening of phonon linewidth. This is because the coherence thermal conductivity, κ C , shows a Breit-Wigner behavior. If the phonon linewidth is close to the Breit-Wigner resonance value (determined by the separation between phonon branches), phonon states can be viewed as “driven” by the scattering, meaning that the quantum coherence between the phonon states can be preserved. Otherwise, κ C is small, which is the case for GeTe.

The most remarkable finding of this work is the increasing trend in the calculated lattice thermal conductivities beginning at 750 K and continuing through 850 K. This is the first computational study to reproduce the experimentally observed anomaly of lattice thermal conductivity vs. temperature. We carefully rule out a few possible explanations for the increasing trend. First, we are aware that the bipolar effect can produce an increasing trend in thermal conductivities at high temperatures. However, the increase in GeTe appears to be much steeper compared to PbSe and PbTe 32 , 34 , 35 (Fig.  3 ). Moreover, the presence of Ge vacancies should make the sample p-type and thus render bipolar effects negligible. Second, since we only considered the lattice thermal conductivity from both our calculation and experiments, the electronic contribution, by definition, has already been subtracted from the total thermal conductivity and is not relevant to this discussion.

We can leverage the detailed calculations to gain insight into the underlying mechanisms for the unusual lattice thermal conductivity increase. Taking a closer look at the temperature dependence of the phonon dispersion shown in Fig.  4a , the most profound change in the frequency occurs in the transverse optical (TO) modes at the Gamma point. The TO mode frequency at the zone center vs. temperature closely aligns with the thermal conductivity trend (Fig.  4b ). Over the past few years, in search of higher-performing thermoelectric materials, studies of phonon dynamics in IV–VI materials have attributed ultralow thermal conductivity to the soft TO modes induced by ferroelectric instability, and the proximity to the ferroelectric instability is typically adjusted via strain and/or alloying 36 , 37 , 38 . While TO mode softening in IV–VI materials is often related to the Peierls distortion, the Peierls distortion disappears in the cubic phase. As the temperature goes above the ferroelectric transition, the hardening of the TO mode over the temperature range we investigated is consistent with the literature 39 and could be related to the increasing stability of the cubic phase. The increasing thermal conductivity is further supported by the temperature dependence of the Gruneisen parameter (Fig.  4c ), which shows a roughly inverse relationship to thermal conductivity as illustrated in Fig.  4d . From 725 K to 850 K, both the increase in the TO mode frequencies and the decrease in the Gruneisen parameter indicate reduced anharmonicity, in contrast to the usual behavior with rising temperature.

Calculated temperature-dependence of ( a ) phonon dispersion, ( b ) TO mode frequency at zone center, ( c ) spectral Gruneisen parameters, ( d ) total Gruneisen parameter.

The decreasing anharmonicity and hardening of the TO mode with temperature are curious. Given that the bonding characteristics of IV–VI chalcogenides are unique, exhibiting properties of both metallic and covalent bonds, or ‘metavalent’ bonding 40 , 41 , we were motivated to dive deeper into the temperature-dependent bonding behaviors of cubic GeTe. To our knowledge, the understanding of the bonding and its temperature dependence in cubic GeTe is quite limited based on the current literature. There is a recent study of pairwise correlated atomic motion in GeTe 42 , but one cannot confidently deduce bonding strengths or thermal conductivity from it.

To go one step deeper than previous studies, we calculated Crystal Orbital Hamilton Population (COHP) curves at 693 K, 775 K, and 850 K to probe the temperature dependence of interatomic bonding in cubic GeTe. It should be emphasized that the COHP calculations are in no way dependent on the force constant calculations, thus providing an independent way to probe atomic pair interactions. Each COHP curve corresponds to one thermalized configuration of the supercell and represents an average of all bonds within the specified cutoff radii and that consist of the specified pair of elements. In these plots, negative values indicate bonding electrons, while positive values indicate anti-bonding electrons. It is difficult to notice any temperature dependent bonding from examining only the COHP vs. energy curves. Rather, to gauge the strength of bonding/anti-bonding interactions, one can integrate the COHP curves with respect to energy, where the value of the integrated COHP (iCOHP) at the Fermi level can be interpreted as an overall bonding/anti-bonding strength.

Examining the iCOHP results, the strongest bonds are between nearest neighbor Ge and Te pairs in the <100> directions, where p-orbital overlap is extensive, as expected. However, these bonds do not show a temperature dependence, and we observe a negligible 0.4% change in bonding strength with temperature from 693 K to 850 K. The covalent interactions of the second-nearest neighbor Ge-Ge and Te-Te bonds are much weaker. However, quite remarkably, the Ge-Ge and Te-Te bonds appear to increase in strength by 8.3% and 103%, respectively. The larger percentage increase of Te-Te bonds can be attributed to the fact that they are weaker since the magnitudes of the COHP increase in both the Ge-Ge and Te-Te bonds are similar. The increasing bonding strengths of Ge-Ge and Te-Te with temperature are peculiar, aligning with the reduced anharmonicity discussed earlier. We posit that while Ge-Te bonds are consolidated closer to the phase transition to stabilize the cubic structure, the second-nearest neighbors of Ge-Ge and Te-Te are not as settled, only reaching peak strength with further temperature increases. It should also be noted that in experimental cubic GeTe samples where Ge vacancies are thought to be common, the Fermi level lies closer to the valance band 43 . Since the difference in the iCOHP curves between 850 K and 693 K (dashed turquoise lines in Fig.  5 ) stays roughly constant right below the Fermi level as shown in Fig.  5 , we do not expect electronic effects from p-doping to alter this bonding picture. Therefore, we believe that this unexpected bond strengthening is a strong contributor to the observed increasing trend.

Comparison of COHP and integrated COHP (iCOHP) bonding curves at 693 K and 850 K for closest ( a ) Ge-Ge bonds (3.6–5.0 Å), and ( b ) Te-Te bonds (3.6–5.0 Å), and ( c ) Ge-Te bonds (0.1–3.5 Å). Values less than zero indicate bonding states, while values greater than zero indicate anti-bonding states. The left subplots show the COHP curves and the difference (labeled as ∆iCOHP 850K, 693K ) between the iCOHP curves for 850 K and 693 K, while the right subplots are the iCOHP curves with respect to energy with a narrow view near the Fermi level. The left subplots also show. The iCOHP curves show a decisive increase in bonding strengths for the Ge-Ge and Te-Te bonds, while hardly any difference exists for the Ge-Te bonds.

Finally, we note that this increasing thermal conductivity at temperatures above that of the phase transition temperature is not just observed in GeTe. SnTe, which also undergoes a rhombohedral-to-rocksalt phase transition at much lower temperatures, exhibits increasing thermal conductivity versus temperature 44 . We note that the authors of the study of SnTe attributed this increasing thermal conductivity to the electronic contribution but that they also expressed doubts over the accuracy of the Lorenz number in their case. Thus, SnTe might behave similarly to GeTe at temperatures near its phase transition if the electronic contribution to thermal conductivity is properly calculated. Even more fascinating, we also find similar properties of phase transitions for SnSe, namely TO mode softening near the phase transition temperature of ~750–800 K 45 and increasing lattice thermal conductivity (along certain crystal axes) just above the phase transition temperature 46 . Given that SnSe transitions from the Pnma to the Cnma crystal structures, differing from GeTe and SnTe, this suggests that the findings herein could have broad implications beyond GeTe, providing a pathway to understanding thermal transport near phase transitions more generally.

In summary, we applied a comprehensive approach combining emerging computational methods and experimental IXS measurements to study thermal transport in the high-temperature cubic phase of GeTe. Our calculations of the lattice thermal conductivity show an abnormally increasing trend starting from ~750 K, which aligns with the experimentally observed trend. We attribute the cause of this abnormal trend to a bond strengthening of second-nearest neighbor Ge-Ge and Te-Te bonds. We also highlight that the calculated phonon lifetimes and thermal conductivity with four-phonon scattering included are in much better agreement with IXS experimental data than calculations that only account for three-phonon processes. The use of a modified version of the unified theory and leveraging BR regression to efficiently train high-order linear models from first-principles data allowed us to properly account for the temperature dependence of thermal transport properties while considering four-phonon scattering and coherence effects simultaneously, which has been previously prohibitive. This work reconciles the significant discrepancies between calculated and experimentally measured thermal conductivity in the literature and provides new insights into the unusually increasing lattice thermal conductivity trend of cubic GeTe. More broadly, this work demonstrates an efficient and thorough pathway toward accurate modeling of highly anharmonic materials near phase transitions and/or at high temperatures that have promise for phase change, thermoelectric, and other energy applications.

Experiments

We purchased GeTe crystals from 2D Semiconductors. The samples were grown using the state-of-art flux zone technique. Before the IXS measurements, we performed XRD at room temperature to screen the samples. Details can be found in SI. We carefully selected a single crystal with a size of \(107\,\mu m\times 485\,\mu m\times 550\,\mu m\) for IXS measurements. To ensure a complete phase transition from the rhombohedral to the cubic phase, we heated the GeTe crystal to 693 K. The XRD reflection pattern of GeTe at 693 K confirmed the cubic phase and indicated good single crystallinity. The IXS measurements were conducted using beamline 30-ID at the Advanced Photon Source (APS), Argonne National Laboratory. IXS is a photon-in, photon-out spectroscopy technique used to probe the dynamics of phonons. This method involves directing a highly focused X-ray beam at a sample and analyzing the energy and momentum transfer that occurs when the X-rays scatter inelastically off the phonons. The high-energy-resolution inelastic X-ray spectrometer (HERIX) at APS 30-ID is a state-of-the-art spectrometer that provides high resolving power, micro-focused beam, nine analyzers, and large momentum transfer 47 and we have performed IXS using it on semiconductors 29 , 48 and hybrid materials 49 , 50 , 51 . The instrument operates at 23.7 keV, and the instrument energy resolution was determined prior to measurement to be 1.5 meV. Measured energy spectra were fitted with Lorentzian peaks convoluted with a pseudo-Voigt function to simulate instrument resolution. We performed three to five repeated energy scans and averaged the data for every q point to reduce statistical noise. After fitting the elastic and phonon peaks at each q point, we obtained the mode-dependent phonon frequencies and line widths. The inverse of phonon line width gives the phonon lifetime. An example of the raw data and the fitting curve is shown in Fig.  6 .

Energy spectra from IXS measurement (blue circles) of the TA mode at q  = 0.6 along [100] for cubic GeTe single crystal at 693 K characterized by an elastic peak centered at zero energy and inelastic peaks associated with the creation and annihilation of phonons. Cyan and red curves represent the instrumental resolution function and fitting core based on the Lorentzian function, respectively. The solid blue curve denotes the convolution between the resolution function and the fitting core.

Computation

Four-phonon scattering of high-temperature phase.

To efficiently extract effective higher-order IFCs at finite temperatures, we adopted the BR regression algorithm to train linear models of force-displacement data generated from DFT calculations, with each set of force-displacement data corresponding to a specific temperature. The efficiency of this process stems from the ability to construct linear models based on sparse solutions for underdetermined systems. We trained the linear models using the hiPhive package 23 , which interfaces with the scikit-learn ML library and its BR regression algorithm implementation. All reference data was split such that 80% was used for training and 20% was saved to validate the model. More specific details about BR regression and its advantages, as well as the training of the IFCs, can be found in SI. All of the force-displacement data were from configurations based on a 5 × 5 × 5 cubic GeTe supercell consisting of 250 atoms. More details regarding the DFT calculations can be found in SI. The optimized lattice constant using DFT calculations corresponding to 0 K was found to be 6.02 Å, which is within the experimental range of 6.016–6.022 Å for temperatures between 693 K and 800 K 52 .

To generate the temperature-specific sets of displacements, we used a self-consistent phonon method, also implemented in the hiPhive package. In this iterative process, harmonic force constants were calculated and used to generate new configurations by randomly populating the normal modes with a distribution corresponding to the desired temperature 53 . This idea is similar to that employed in SSCHA 8 , but with the equilibrium positions frozen. More details about the self-consistent phonon method, including a flowchart, can be found in the SI.

Once these temperature-specific sets of displacements were generated, we performed DFT calculations for each configuration to accurately obtain the corresponding forces. We used the resulting force-displacement data to obtain second, third, and fourth-order effective IFCs for each temperature using linear models trained with BR regression. In this way, thermal averaging effects are baked into the trained linear models and, thus, the predicted force constants. We used cutoffs of 10.5 Å, 8.0 Å, and 5.0 Å for the second, third, and fourth-order IFCs, respectively, to construct the linear models. We are aware of the long-range interactions typical of IV–VI rock salt structures, 54 and a more detailed discussion on long-range interactions is included in SI. To best account for these long-range interactions, we used the cutoff of 10.5 Å, which is the maximum allowed for our 250-atom supercell, to train the second-order model. More discussions on long-range interactions can be found in SI. For our calculated phonon dispersion, we used calculated Born effective charges and dielectric constants from DFPT to apply non-analytical term corrections (see SI for more details on the DFPT calculations). Further increasing the third-order cutoff made little difference regarding the calculated thermal conductivity. Our fourth-order cutoff of 5.0 Å includes second-nearest neighbors, typically sufficient to converge fourth-order effects 55 . Notably, the fitting of the fourth-order IFCs, typically prohibitive, only took a few minutes using BR regression.

Using the IFCs as input, we solved the BTE iteratively for three-phonon processes and used the relaxation time approximation (RTA) for four-phonon processes. It is prohibitively expensive to solve the BTE iteratively for four-phonon processes. Fortunately, the Umklapp processes contribute significantly more to the overall scattering rates in cubic GeTe (see Fig. S2 in Supplementary information), justifying the treatment of four-phonon calculations using the RTA 55 . More details regarding the BTE calculations can be found in SI.

Coherence contribution

We applied a correction to the thermal conductivity by including the quantum coherence effect. This was motivated by the unified theory 9 , which shows that broadening the phonon branches can lead to quantum coherence and contribute to lattice thermal conductivity. The original unified theory was only shown to be compatible with the DFPT framework, and only included the coherence contribution from the third-order IFCs. We extended it to incorporate IFCs generated by the real-space displacement approach and include the coherence thermal conductivity from both the third and fourth-order IFCs (Fig.  7 ). This new implementation allows for (1) applying the unified theory to more complex materials in general because of the use of input from the real-space displacement approach instead of DFPT in reciprocal space; (2) including the four-phonon scattering contribution in the coherence term because the BR regression method drastically accelerated the fitting process and made the fourth-order IFCs accessible. We confirm the consistency of our approach with the original unified theory by calculating the thermal conductivity of \({CsPbB}{r}_{3}\) , as shown in the Supplementary information.

Incorporating real-space displacement method enables computation for more complicated structures with larger unit cells.

The coherence contribution to lattice thermal conductivity is denoted by

where \(\omega ({{\bf{q}}})_{s}\) and \(\Gamma ({{\bf{q}}})_{s}\) are the phonon frequency and linewidth, respectively, with the latter calculated using both the third and fourth order IFC, and \(\bar{N}({{\bf{q}}})_{s}={\left(\exp \left(\hslash \omega ({{\bf{q}}})_{s}/\left({k}_{{{\rm{B}}}}T\right)\right)-1\right)}^{-1}\) is the Bose-Einstein distribution. The generalized group velocity matrix is given by

where the unitary transformation \({{{\mathcal{E}}}}^{\star }({{\bf{q}}})_{s,b\alpha }D({{\bf{q}}})_{b\alpha,{b}^{{\prime} }{\alpha }^{{\prime} }}{{\mathcal{E}}}({{\bf{q}}})_{{s}^{{\prime} },{b}^{{\prime} }{\alpha }^{{\prime} }}={\omega }^{2}({{\bf{q}}})_{s}{\delta }_{s,{s}^{{\prime} }}\) diagonalizes the dynamical matrix \(D({{\bf{q}}})\) . Conventional phonon packages based on the real-space displacement approach, such as Phonopy, can provide the dynamical matrix \(D({{\bf{q}}})\) and its gradient \({\nabla }_{{{\bf{q}}}}D\left({{\bf{q}}}\right),\, {{\rm{but}}}\) do not directly support the calculation of \({\nabla }_{{{\bf{q}}}}\sqrt{D\left({{\bf{q}}}\right)}\) . Our solution is to obtain the matrix elements of \({\nabla }_{{{\bf{q}}}}\sqrt{D\left({{\bf{q}}}\right)}\) by numerically solving the matrix equation

so that the complicated symbolic manipulation simplifies to a numerical equation, which significantly reduces the computational complexity even when the unit cell is large.

The coherence thermal conductivity scales as \({\kappa }_{C} \sim \frac{\Gamma }{4\triangle {\omega }^{2}+{\Gamma }^{2}}\) , where \(\triangle \omega\) represents the scale of separation between phonon branches. When the phonon branch separations are much smaller than the broadening \(\Gamma\) , the coherence contribution scales as \({\kappa }_{C}\, \sim \frac{1}{\Gamma }\) , while when the broadening \(\Gamma\) is negligible compared to the phonon branch separation, \({\kappa }_{C} \sim \Gamma\) . Specifically, for each \({{\boldsymbol{q}}}\) and every two phonon branches, the resonance occurs at \(\delta \omega \left({{\boldsymbol{q}}}\right)=2{\Gamma }_{{\!\!Total}}({{\boldsymbol{q}}})\) , where \(\delta \omega \left({{\boldsymbol{q}}}\right)\) is the line separation between the two phonon branches, and \({\Gamma }_{{\!\!Total}}({{\boldsymbol{q}}})\) is the total linewidth by including broadening from both third and fourth-order interactions. It is worth mentioning that the quantum coherence of phonons is analogous to electronic Zener tunneling, in which electrons undergo quantum-mechanical inter-band transitions 56 and exhibit resonance behavior.

Interatomic bonding

To obtain the COHP bonding curves, we projected the delocalized planewave basis set used within VASP onto a suitable localized basis set consisting of pseudo-atomic orbitals. The projections were quite computationally demanding for our large 250-atom supercells, so we provide calculations for three temperatures and one chosen configuration for each temperature. Each configuration was chosen such that the average force, maximum force, and average displacement all increased with temperature to ensure that the results reflected the intended change in temperature. We used the LOBSTER code 57 , 58 to perform the basis set projection. We found the default localized basis set provided with LOBSTER to work well in this application, with a calculated charge splashing of only 1%, a low value indicative of a high-quality local basis set projection.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Acknowledgements

This work was funded by Z.T.’s NSF CAREER Award (CBET1839384). This research used resources of the Advanced Photon Source, a U.S. DOE Office of Science User Facility operated for the D.O.E. Office of Science by Argonne National Laboratory under Contract No. DE-AC02-06CH11357. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation Grant ACI-1053575. This work used Expanse at San Diego Supercomputer Center (SDSC) through allocation CTS150063 from the Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS) program, which is supported by National Science Foundation grants #2138259, #2138286, #2138307, #2137603, and #2138296.

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These authors contributed equally: Samuel Kielar, Chen Li.

Authors and Affiliations

Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, NY, USA

Samuel Kielar, Chen Li, Han Huang, Renjiu Hu & Zhiting Tian

MOE Key Laboratory of Low-grade Energy Utilization Technologies and Systems, School of Energy & Power Engineering, Chongqing University, Chongqing, China

Department of Chemistry, Virginia Tech, Blacksburg, VA, USA

Carla Slebodnick

Advanced Photon Source, Argonne National Laboratory, Argonne, IL, USA

Ahmet Alatas

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S.K. and C.L. contributed equally to this work. S.K., C.L., and Z.T. conceived the study. S.K. conducted the thermal transport calculations. C.L. conducted the IXS measurements. H.H. applied coherence corrections to the calculations. R.H. assisted with the IXS measurements. C.S. conducted XRD for sample screening. A.A. assisted with the IXS measurements. The manuscript was prepared by S.K., C.L., H.H., and Z.T.

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Kielar, S., Li, C., Huang, H. et al. Anomalous lattice thermal conductivity increase with temperature in cubic GeTe correlated with strengthening of second-nearest neighbor bonds. Nat Commun 15 , 6981 (2024). https://doi.org/10.1038/s41467-024-51377-8

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DOI : https://doi.org/10.1038/s41467-024-51377-8

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Free-standing, water-resistant, and conductivity-enhanced pedot:pss films from in situ polymerization of 3-hydroxymethyl-3-methyl-oxetane.

Graphical Abstract

1. Introduction

2. materials and methods, 2.1. materials, 2.2. preparation of pedot:pss:hmo free-standing films, 2.3. material characterization, 2.3.1. 1 h and 13 c nuclear magnetic resonance (nmr), 2.3.2. fourier-transform infrared spectroscopy, 2.3.3. electrical conductivity measurements, 2.3.4. differential scanning calorimetry (dsc), 2.3.5. atomic force microscopy (afm), 2.3.6. mechanical properties, 2.3.7. electrocardiogram (egc) recording, 3. results and discussion, 3.1. electrical conductivity of pedot:pss:hmo free-standing films, 3.2. reactivity of hmo in pedot:pss medium, 3.3. ftir spectroscopy analysis, 3.4. thermal behavior, 3.5. surface morphology analysis, 3.6. mechanical properties.

3.7. Application as Electrodes in ECG Biosensors

4. conclusions, supplementary materials, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Jorge, S.M.; Santos, L.F.; Ferreira, M.J.; Marto-Costa, C.; Serro, A.P.; Galvão, A.M.; Morgado, J.; Charas, A. Free-Standing, Water-Resistant, and Conductivity-Enhanced PEDOT:PSS Films from In Situ Polymerization of 3-Hydroxymethyl-3-Methyl-Oxetane. Polymers 2024 , 16 , 2292. https://doi.org/10.3390/polym16162292

Jorge SM, Santos LF, Ferreira MJ, Marto-Costa C, Serro AP, Galvão AM, Morgado J, Charas A. Free-Standing, Water-Resistant, and Conductivity-Enhanced PEDOT:PSS Films from In Situ Polymerization of 3-Hydroxymethyl-3-Methyl-Oxetane. Polymers . 2024; 16(16):2292. https://doi.org/10.3390/polym16162292

Jorge, Sara M., Luís F. Santos, Maria João Ferreira, Carolina Marto-Costa, Ana Paula Serro, Adelino M. Galvão, Jorge Morgado, and Ana Charas. 2024. "Free-Standing, Water-Resistant, and Conductivity-Enhanced PEDOT:PSS Films from In Situ Polymerization of 3-Hydroxymethyl-3-Methyl-Oxetane" Polymers 16, no. 16: 2292. https://doi.org/10.3390/polym16162292

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Ag/Cu doped polyaniline hybrid nanocomposite-based novel gas sensor for enhanced ammonia gas sensing performance at room temperature

First published on 12th August 2024

Hybrid nanocomposites, which comprise organic and inorganic materials, have gained increasing attention in applications for enhanced sensing response to both reducing and oxidation gases. In this study, a novel nanocomposite is synthesized using chemical polymerization by reinforcing Ag/Cu nanoparticles with different concentrations doped into the polyaniline matrix. This hybrid nanocomposite is used as a sensing platform for ammonia detection with different concentrations (ppm). The homogeneous distribution of Ag/Cu nanoparticles onto the PANI matrix provides a smooth and dense surface area, further accelerating the transmission of electrons. The synergistic effect of the PANI@Ag/Cu matrix is responsible for the outstanding conductivity, compatibility, and catalytic ability of the proposed gas sensor. The structure, morphology, and surface composition of as-synthesized samples were examined using X-ray diffraction, field emission scanning electron microscopy, ultraviolet-visible spectroscopy, energy dispersive spectroscopy, thermogravimetric analysis, and Fourier transform infrared spectroscopy. The results indicated that the resistive sensor based on the PANI@Ag/Cu 3 hybrid nanocomposite exhibited the highest response toward ammonia at room temperature, with a response value of 86% to a concentration of 300 ppm. We also investigated the sensing properties of volatile organic compounds, including carbon dioxide, carbon monoxide, ethanol and hydrogen sulphide. Characterization and gas sensing measurements exhibited protonation and deprotonation of the PANI@Ag/Cu heterojunction, which contributes to the ammonia sensing mechanism. Overall, the obtained findings demonstrated that the PANI@Ag/Cu hybrid nanocomposite is a promising material for gas sensing applications in environmental monitoring.

1. Introduction

Research into ternary hybrid systems has been growing in popularity as a means to improve sensing performance. Metal particle–metal oxide–conducting polymers, metal particle–carbon nanotubes–conducting polymers, metal particle–graphene–conducting polymers, metal oxide–graphene conducting polymers and metal oxide–metal oxide–conducting polymers 23,24 are among the gas sensors based on ternary nanocomposite that have been synthesised for gas-sensing research. The carboxylated polypyrrole (CPPy)/CNTs/Pd nanocomposites produced by Park et al. 23 for NH 3 detection are simple and novel. By in situ polymerization, Zhang et al. 25 synthesised ZnO, graphene quantum dots (GQDs), and PANI nanocomposites. At room temperature, ZnO, GQDs, and PANI nanocomposite sensors showed high sensitivity (from 2% to 500 ppb acetone), selectivity, response/recovery time of 15/27 s, reproducibility, and long-term stability. Additionally, the conductive polymer-based ternary material mixture system is not random. Process compatibility, morphology, composition ratio and function distribution are the only ways to achieve synergistic reinforcement of many materials. Utilising Ag/Cu and PANI characteristics, this research aims to create a unique ammonia detection device. Reasons to assume Ag/Cu can improve conducting polymer sensing include the following: polymer conductivity is altered by Ag/Cu nanoparticles. Secondly, Ag/Cu nanoparticles may improve sensor selectivity as chemical receptors and various metal nanoparticles exhibit chemical affinity for gas molecules. Metal-containing conductive polymers improve nanocomposite–gas interaction. These aspects inspired the development of a hybrid conducting polymer nanocomposite ammonia gas sensor based on in situ Ag/Cu synthesis in a PANI matrix for room-temperature performance. PANI@Ag/Cu hybrid nanocomposite can be prepared with a range of five different concentrations of silver nitrate and copper acetate. Analysis of the conducting polymer and its nanocomposites was carried out using XRD, UV, FESEM, EDS, TGA and FT-IR methods. To create PANI and PANI@Ag/Cu hybrid nanocomposite films, the spin-coating technique was applied to a silicon substrate. The gas-sensing capabilities of the samples were examined by subjecting them to different concentrations of NH 3 at room temperature. In addition, the mechanisms and impacts of Ag/Cu on sensor behaviour for ammonia detection were thoroughly examined. Among the many practical benefits of environmental monitoring, the study emphasizes the fact that the PANI@Ag/Cu hybrid nanocomposite can achieve its increased sensing capabilities at room temperature. To the best of our knowledge, no research has been carried out thus far on gas sensors based on PANI@Ag/Cu hybrid nanocomposite films, which could improve the room temperature detection performance of ammonia gas.

2. Experimental procedure

2.1 materials required, 2.2 synthesis of polyaniline (pani).

2.3 Synthesis of PANI@Ag/Cu hybrid nanocomposite

Nitrogen atoms in PANI amine and imine groups can coordinate with metal ions. A coordination link can be formed between these nitrogen atoms and either silver or copper, stabilising the metal nanoparticles within the PANI matrix. Synthesis of the hybrid nanocomposite can involve redox reactions in which PANI can reduce Ag + and Cu 2+ ions to their corresponding metallic forms, Cu 0 and Ag 0 , respectively. As a consequence of this procedure, metal nanoparticles are created without external sources within the PANI matrix. The inclusion of Ag and Cu nanoparticles into the PANI matrix can improve its electrical conductivity because these metals are very conductive. All things considered, the nanocomposite performance in gas sensing and similar applications is enhanced by this synergistic effect. As shown in Scheme 3 , the amine groups included in PANI inhibit the aggregation of Ag/Cu nanoparticles. 28

3. Results and discussion

3.1 x-ray diffraction.

3.2 FT-IR study

3.3 Optical analysis and band gap values

As per Tauc's eqn (2) , the direct allowed transition type can be used to approximatively determine the optical band gap of the powder sample. 32 Eqn (2) α = 2.303 × 10 1 A / L c represents the absorption coefficient, where A is the sample absorbance, E g is the optical band gap, h is the Planck constant, and v is the reciprocal of the wavelength. L represents the path length, while A stands for absorption. 33 Based on the plot of ( αhν ) 2 vs. hν , the E g values of both the pure PANI and the produced hybrid nanocomposites have been calculated. In order to estimate the band gap, the straight line was extrapolated to the point where ( αhν ) 2 = 0. As shown in Fig. 3c and d , the spectral analysis produced transition bandgaps ( E g ) of around 2.21 eV for pure PANI, 2.4 eV for PANI@Ag/Cu 1 , 2.6 eV for PANI@Ag/Cu 2 , 2.9 eV for PANI@Ag/Cu 3 , 3.5 eV for PANI@Ag/Cu 4 , and 4.1 eV for PANI@Ag/Cu 5 . Increases in the band gap allow the hybrid nanocomposite to potentially display optical features that can be varied, as shown in Fig. 3d . In a hybrid nanocomposite of PANI@Ag/Cu, the band gap is increased due to the specific interactions between the three materials. The incorporation of these metal nanoparticles into the PANI matrix causes alterations to the electrical structure of the polymer. Incorporating Ag and Cu nanoparticles into a nanocomposite can change its electrical characteristics by creating new energy levels in the band structure. The quantum confinement effect and changes in charge transfer dynamics between the PANI and the metal nanoparticles can cause this modification to lead to an expanded band gap. These nanoparticles can also affect the PANI crystallinity and morphological properties, which in turn raises the band gap. The capacity to modify the emission and absorption spectra of the material by adjusting the band gap is a crucial characteristic of gas sensors. The energy levels at which electrons can be stimulated and then relax can be changed by changing the band gap of the sensor material. The material absorption and emission wavelengths may alter as a result of this change in energy levels. This allows for the possibility of tailoring the sensor to respond more strongly to certain gases by altering the energy levels at which they interact with the material. The ability to detect target gases at low concentrations with great precision is made possible by this characteristic, which enables the creation of highly selective gas sensors. It is possible to increase the adaptability and application of sensing technology by tuning the band gap, which in turn allows the development of sensors that work successfully for different types of gas molecules and in varied environmental situations.

3.4 Morphological analysis

3.5 Dispersive X-ray spectroscopy (EDX)

3.6 Thermogravimetric (TG) and differential thermal analysis (DTA)

3.7 Gas sensing studies

3.8 Sensing mechanism of PANI@Ag/Cu hybrid nanocomposite

4. Conclusion

Data availability, conflicts of interest.

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