Macroscopic Thermal Properties Research Articles

The Critical Role of Anharmonic Lattice Dynamics for Macroscopic Properties of the Visible Light Absorbing Nitride Semiconductor CuTaN2

AbstractTernary nitride semiconductors are rapidly emerging as a promising class of materials for energy conversion applications, offering an appealing combination of strong light absorption in the visible range, desirable charge transport characteristics, and good chemical stability. In this work, it is shown that finite‐temperature lattice dynamics in CuTaN2 – a prototypical ternary nitride displaying particularly strong visible light absorption – exhibit a pronounced anharmonic character that plays an essential role in defining its macroscopic optoelectronic and thermal properties. Low‐frequency vibrational modes that are Raman‐inactive from symmetry considerations of the average crystal structure and unstable in harmonic phonon calculations are found to appear as intensive Raman features near room temperature. The atomic contributions to the anharmonic vibrations are characterized by combining Raman measurements with molecular dynamics and density functional theory calculations. This analysis reveals that anharmonic lattice dynamics have large ramifications on the fundamental properties of this compound, resulting in uniaxial negative thermal expansion and the opening of its bandgap to a near‐optimal value for solar energy harvesting. The atomic‐level understanding of anharmonic lattice dynamics, as well as the finding that they strongly influence key properties of this semiconductor at room temperature, have important implications for design of new functional materials, especially within the emerging class of ternary nitride semiconductors.

Thermal Conductivity Analysis of Polymer‐Derived Nanocomposite via Image‐Based Structure Reconstruction, Computational Homogenization, and Machine Learning

Macroscopic thermal properties of engineered or inherent composites depend substantially on the composite structure and the interface characteristics. While it is acknowledged that unveiling such dependency relation is essential for materials design, the complexity involved in, e.g., microstructure representation and limited data impedes the research progress. Herein, this issue is tackled by machine learning techniques on image‐based microstructure and property data predicted from physics simulations, along with experimental validation. The methodology is demonstrated for the model system ultrahigh‐temperature ceramic nanocomposite. The structure is reconstructed from scanning electron microscope images, and is resolved by a diffuse‐interface representation, which is advantageous in handling complicated structure and interface properties. Subsequently, hierarchical finite element homogenization is carried out to evaluate the effective thermal conductivity. A thorough comparison between the computed results and experimentally measured data, conducted across diverse temperatures and varying interface thermal resistances, reveals a high level of agreement. The observed agreement allows for the inverse estimation of the interface thermal resistance, a parameter typically challenging to ascertain directly through experimental means. Utilizing comprehensive data, a machine learning surrogate model has been meticulously trained to accurately predict the effective thermal conductivity of composite structures with exceptional performance.

On the link between mechanics and thermal properties: mechanothermics

We report on the theoretical derivation of macroscopic thermal properties (specific heat, thermal conductivity) of an electrically insulating rod connected to two reservoirs, from the linear superposition of its mechanical mode Brownian motions. The calculation is performed for a weak thermal gradient, in the classical limit (high temperature). The development is kept basic as far as geometry and experimental conditions are concerned, enabling an almost fully analytic treatment. In the modeling, each of the modes is subject to a specific Langevin force, which enables to produce the required temperature profile along the rod. The theory is predictive: the temperature gradient (and therefore energy transport) is linked to motion amplitude cross-correlations between nearby mechanical modes. This arises because energy transport is actually mediated by mixing between the modal waves, and not by the modes themselves. This result can be tested on experiments, and shall extend the concepts underlying equipartition and fluctuation–dissipation theorems. The theory links intimately the macroscopic size of the clamping region where the mixing occurs to the microscopic lengthscale of the problem at hand: the phonon mean-free-path. This clamping region, which is key, has received recently a renewed attention in the field of nanomechanics with topical works on ‘phonon shields’ and ‘soft clamping’. We believe that our work should impact the domain of thermal transport in nanostructures, with future developments of the theory toward the quantum regime.

Direct Visualization of Localized Vibrations at Complex Grain Boundaries.

Grain boundaries (GBs) are a prolific microstructural feature that dominates the functionality of a wide class of materials. The functionality at a GB results from the unique atomic arrangements, different from those in the grain, that have driven extensive experimental and theoretical studies correlating atomic-scale GB structures to macroscopic electronic, infrared optical, and thermal properties. In this work, a SrTiO3 GB is examined using atomic-resolution aberration-corrected scanning transmission electron microscopy and ultrahigh-energy-resolution monochromated electron energy-loss spectroscopy, in conjunction with density functional theory. This combination enables the correlation of the GB structure, nonstoichiometry, and chemical bonding with a redistribution of vibrational states within the GB dislocation cores. The new experimental access to localized GB vibrations provides a direct route to quantifying the impact of individual boundaries on macroscopic properties.

Thermal and Mechanical Properties of Plain Woven Ceramic Matrix Composites by the Imaged-Based Mesoscopic Model

The mesoscopic finite element model of ceramic matrix composites is developed by reconstructing computed tomography images. The relationship between microstructure and macroscopic properties and their dispersion are explored. Firstly, a three-dimensional reconstructed computed tomography model was carried out to calculate the orientation of the components. Secondly, the orientation and gray value of images were used to identify the basic structure of composites including fiber tows, matrix, and porosities. Finally, the two-dimensional finite element model was developed to analyze the macroscopic thermal and mechanical properties. The numerical results showed that: (1) the geometries and distributions of pores had a significant effect on the through-thickness modulus and thermal conductivity; (2) the stress and heat flow concentration area on the material surface usually occurred in narrow gaps between closely spaced longitudinal tows; (3) the elastic modulus and thermal conductivity were dispersive, and their distribution followed by two-parameter Weibull distribution.

FEM heat transfer modelling with tomography-based SiCf/SiC unit cell

Modern industry has become increasingly reliant on composite materials for a variety of applications, and the nuclear industry is no exception to this. Among the materials being researched as Enhanced Accident Tolerant Fuels, ceramic matrix composites such as SiC-fiber-reinforced SiC (SiCf/SiC) figure as some prime candidates due to their excellent high temperature performances. SiCf/SiC so far shows adequate nuclear, mechanical and chemical properties; still, the thermal properties need further investigation. The thermal behavior of a material is an important factor for its performance as a nuclear fuel cladding, i.e. the first barrier encapsulating the fuel pellets. Many features determine the resulting properties of composite materials, such as matrix and fiber reinforcement properties and orientation, void fraction, and pore morphology. This study establishes a methodology to study the physical properties of composite materials and applies it to SiCf/SiC. A FEM model is used to characterize the thermal properties of a fundamental SiCf/SiC element, referred to as a �unit cell�, with the objective of accurately predicting the thermal properties of this complex class of materials where experimental data is often difficult to obtain. The unit cell is built based on data acquired with high-resolution tomographic microscopy performed at the TOMCAT beamline of the Swiss Light Source. By using phase-retrieval prior to tomographic reconstruction, the pores, fibers and matrix that compose the material can be distinguished in the data analysis. The separated information is processed to obtain geometrical information about the individual pores and fibers, which is then used to parametrize them as cylindrical objects. This allows constructing a FEM model of a cubic unit cell that is used to extract the effective thermal properties of SiCf/SiC. The analysis scheme includes steady-state and dynamic thermal transport simulations, which yield directional effective thermal conductivity and diffusivity values, respectively. Both modes of analysis show isotropic thermal conductivity values in the range of 71 W/m/K at room temperature, more than three times that of currently employed nuclear cladding materials. Combining these results with the data on the larger structural features of the material will lead to realistic results on the macroscopic thermal properties.

Influences of Crystallinity and Crosslinking Density on the Shape Recovery Force in Poly(ε-Caprolactone)-Based Shape-Memory Polymer Blends.

Shape-memory polymers (SMPs) show great potential in various emerging applications, such as artificial muscles, soft actuators, and biomedical devices, owing to their unique shape recovery-induced contraction force. However, the factors influencing this force remain unclear. Herein, we designed a simple polymer blending system using a series of tetra-branched poly(ε-caprolactone)-based SMPs with long and short branch-chain lengths that demonstrate decreased crystallinity and increased crosslinking density gradients. The resultant polymer blends possessed mechanical properties manipulable across a wide range in accordance with the crystallinity gradient, such as stretchability (50.5-1419.5%) and toughness (0.62-130.4 MJ m-3), while maintaining excellent shape-memory properties. The experimental results show that crosslinking density affected the shape recovery force, which correlates to the SMPs' energy storage capacity. Such a polymer blending system could provide new insights on how crystallinity and crosslinking density affect macroscopic thermal and mechanical properties as well as the shape recovery force of SMP networks, improving design capability for future applications.

Unveiling the role of filler surface energy in enhancing thermal conductivity and mechanical properties of thermal interface materials

With heat-flux density of electronics drastically increase polymer-based thermal interface materials play a critical role in the performance of electronics. Although surface energy of fillers has been recognized as a crucial parameter, the exploitation of the filler surface energy-dependent properties is still unclear. Herein, we report on unveiling the effect of the surface energy of aluminum on thermal and mechanical properties in thermal interface materials consisted of polydimethylsiloxane and modified aluminum with silane-coupling agents containing varied chain lengths. The results show that reducing the surface energy of aluminum is beneficial to improve the aluminum fillers dispersibility in polydimethylsiloxane, leading to improved macroscopic properties, including rheology, mechanical properties, and thermal properties. Furthermore, based on the thermodynamic prediction, a winding hypothesis was proposed to explain the interaction between the modified aluminum and polydimethylsiloxane. This work provides valuable guidance for rationally designing the surface energy of fillers in thermal interface materials.

Thermo-physical characterization of Hexadecane during the solid/liquid phase change

In this study we provide a multi-physical and multi-scale characterization of an organic Phase Change Material (PCM), i.e. hexadecane, for both its liquid and solid phase and during the phase transition. Macroscopic thermal and physical properties provided are density and viscosity in the liquid phase and thermal conductivity and heat capacity in each phase. Further macroscopic measurements were done by differential scanning calorimetry (DSC), which was used to obtain a first estimation of temperatures at which the solid/liquid phase transition occurs. DSC results present a thermal hysteresis between melting (Tm) and solidification (Ts) temperature. A similar hysteresis was also collected during rotational and oscillatory rheometry at the phase change, where Ts is found to depend on the applied cooling rate. Moreover, near Ts the forming solid structure is continuously affected by conditions imposed by the rheometer (i.e. applied shear rate or stress) and the breakage of crystals takes place even at the weak imposed stress tested (0.001 Pa). Beside the bulk behavior, the local melting and solidification were studied at microscopic scale through Raman spectroscopy. The local melting temperature is very close to what found by DSC and by rheometry. On the other hand, crystallization onset is found at higher temperatures for long waiting times, thus considerably reducing the thermal hysteresis. Finally, we highlight a key influence of interfaces on the phase transition. Variations in boundary conditions (thermal and/or kinematical conditions) are found responsible for the way hexadecane’s solidification occurs.

Structure-Property-Function Relationships of Iron Oxide Multicore Nanoflowers in Magnetic Hyperthermia and Photothermia.

Magnetite and maghemite multicore nanoflowers (NFs) synthesized using the modified polyol-mediated routes are to date among the most effective nanoheaters in magnetic hyperthermia (MHT). Recently, magnetite NFs have also shown high photothermal (PT) performances in the most desired second near-infrared (NIR-II) biological window, making them attractive in the field of nanoparticle-activated thermal therapies. However, what makes magnetic NFs efficient heating agents in both modalities still remains an open question. In this work, we investigate the role of many parameters of the polyol synthesis on the final NFs' size, shape, chemical composition, number of cores, and crystallinity. These nanofeatures are later correlated to the magnetic, optical, and electronic properties of the NFs as well as their collective macroscopic thermal properties in MHT and PT to find relationships between their structure, properties, and function. We evidence the critical role of iron(III) and heating ramps on the elaboration of well-defined NFs with a high number of multicores. While MHT efficiency is found to be proportional to the average number of magnetic cores within the assemblies, the optical responses of the NFs and their collective photothermal properties depend directly on the mean volume of the NFs (as supported by optical cross sections numerical simulations) and strongly on the structural disorder in the NFs, rather than the stoichiometry. The concentration of defects in the nanostructures, evaluated by photoluminescence and Urbach energy (EU), evidence a switch in the optical behavior for a limit value of EU = 0.4 eV where a discontinuous transition from high to poor PT efficiency is also observed.

Computational Determination of Macroscopic Mechanical and Thermal Material Properties for Different Morphological Variants of Cast Iron

The sensitivity of macroscopic mechanical and thermal properties of grey cast iron is computationally investigated for a variety of graphite morphologies over a wide temperature range. In order to represent common graphite morphologies according to EN ISO 945-1, a synthetic approach is used to algorithmically generate simulation domains. The developed mechanical and thermal model is applied in a large simulation study. The study includes statistical volume elements of the graphite morphology classes GJL-150 and IA2 to IA5, with 10, 11 and 12 v.−% of graphite precipitations, respectively, for a temperature range from 20 to 750 °C. Homogenised macroscopic quantities, such as the Young’s moduli, Poisson’s ratios, yield strengths and thermal conductivities, are predicted for different morphology classes by applying simulation and data analysis tools of the research data infrastructure Kadi4Mat. This is the first work to determine the mechanical and thermal properties of the morphology classes defined in EN ISO 945-1.

Recent progress in tuning polymer oriented microstructures for enhanced thermoelectric performance

In recent years, the research of conjugated polymer-based thermoelectric (TE) materials has experienced exponential growth due to their diverse advantages and promising application potentials in internet-of-things, medical/health monitoring, and flexible and wearable electronics, etc. Oriented microstructure is undoubtedly vital governing polymer macroscopic performances, including mechanical, thermal and TE properties. Regretfully, the corresponding review or summary of the relation between oriented microstructure and TE performance is scarce for conjugated polymers. Here, the recent progress of orienting conjugated polymers in TE applications is reviewed. First, typical methods to achieve the oriented microstructure, including both long-range in-plane orientation and local ordered structure, are introduced. Then, to deepen a fundamental understanding of the relationship between oriented structure and TE performance, the underlying mechanism are discussed by taking insights from charge and phonon transports. Finally, the main challenges and the future prospects are outlooked. • Recent progress of oriented microstructures of conjugated polymers in thermoelectric applications is reviewed. • Typical methods to achieve the oriented microstructures are summarized. • Underlying mechanism are discussed by means of charge and phonon transports. • Main challenges and the future prospects are outlooked.

Iterative multi-scale approach for heat conduction with free convection problem in periodic hollow structures

This paper describes a thermal homogenization approach to the application of a multi-scale formulation for steady state heat conduction with free convection problems in a hollow structure. The presented formulation evaluates the effective macroscopic thermal properties of a hollow structure containing fluid within microstructures. This is done by scaling up and down between the microscopic and macroscopic models. The uniqueness of this approach is that it permits the solution of a heat conduction problem on a macroscopic scale, instead of solving heat conduction with free convection problem. The proposed methodology involves an iterative upscaling procedure which solves a coupled convection conduction CFD unit cell problem in each iteration. This reduces the required computational time while maintaining the required level of accuracy. Our method of multi-scale formulation has been verified using two examples of hollow structures containing air within the hollow spaces. The results are in excellent agreement with the reference solutions.

Smart Honeycomb “Mechanical Metamaterials” with Tunable Poisson's Ratios

Mechanical metamaterials represent a class of deformable systems, which exhibit macroscopic deformations, mechanical, and/or thermal properties. These emerge due to the structure of their subunits rather than their materials composition and typically exhibit anomalous (normally negative) macroscopic structural, mechanical, or thermal property/properties caused by a change in shape/size of the system. Herein, a class of honeycombs is discussed, which push to the extreme the classical definition of “mechanical metamaterials,” exhibiting temperature‐tunable Poisson's ratio properties. More specifically, centrosymmetric honeycombs with T‐shaped joints constructed from different materials are shown to exhibit temperature‐dependent Poisson's ratio values, which can be either positive or negative (auxetic) depending on the external stimulus the system is subjected to. The sign and magnitudes of the Poisson's ratio values are explained in terms of particular geometries that these composite honeycomb systems attain at different temperature conditions. In particular, auxeticity is attributed to the transformation of the T‐shaped units to re‐entrant units. Practical aspects on how these properties may be achieved are discussed, including the possibility that the changes in shape, and hence Poisson's ratios, are inducedviadifferent extents of dryness on opposite surfaces of ligaments made from absorbent materials.

Thermal properties of graphene-based polymer composite materials: A molecular dynamics study

Interfaces between graphene play a crucial yet poorly understood role in the transport of heat in graphene-based composite materials. The primary focus of this study was on developing a quantitative understanding of the mechanism underlying the heat flow through the structure of a graphene-based polymer matrix composite material. The macroscopic thermal properties of the composite material were studied to provide an effective way to improve thermal conductivity for polymers. Molecular dynamics simulations were performed to understand the thermal resistance of interfaces between graphene and to optimize the condition of the interface for nanoscale thermal reinforcement. A modified Maxwell Garnett effective medium theory was used to predict the thermal conductivity of the composite material. The results indicated that the thermal properties of a graphene-based polymer matrix composite material depends upon the details of the microscopic structure and atomic interactions within the composite material. Interfaces between graphene contribute significantly to the thermal conductivity of the composite material. This is even more critical for composite materials where the lateral size of graphene can affect the thermal performance of the composite material significantly. Low thermal boundary resistance and high thermal conductivity can be achieved by introducing the structure of a carbon cross-link network between graphene. The proper combination of graphene with large size and carbon cross-links with high density can lead to a fifty-fold improvement in overall thermal performance for the polymer matrix composite material. The relative position between graphene can be adjusted for the further optimization of interfacial conditions, but with little success in nanoscale thermal reinforcement. The bulk thermal conductivity of graphene nanoribbons has been found to be about 2570 W/m·K at room temperature. The results can provide a theoretical basis for understanding the applied physics of thermal transport at the nanoscale in graphene-based polymer matrix composite materials.

The correlation between porosity characteristics and the crystallographic texture in extruded stabilized aluminium titanate for diesel particulate filter applications

Porous ceramic diesel particulate filters (DPFs) are extruded products that possess macroscopic anisotropic mechanical and thermal properties. This anisotropy is caused by both morphological features (mostly the orientation of porosity) and crystallographic texture. We systematically studied those two aspects in two aluminum titanate ceramic materials of different porosity using mercury porosimetry, gas adsorption, electron microscopy, X-ray diffraction, and X-ray refraction radiography. We found that a lower porosity content implies a larger isotropy of both the crystal texture and the porosity orientation. We also found that, analogous to cordierite, crystallites do align with their axis of negative thermal expansion along the extrusion direction. However, unlike what found for cordierite, the aluminium titanate crystallite form is such that a more pronounced (0 0 2) texture along the extrusion direction implies porosity aligned perpendicular to it.

A Mechanics Based Surface Image Interpretation Method for Multifunctional Nanocomposites.

Graphene nanosheets and thicker graphite nanoplatelets are being used as reinforcement in polymeric materials to improve the material properties or induce new functional properties. By improving dispersion, de-agglomerating the particles, and ensuring the desired orientation of the nano-structures in the matrix, the microstructure can be tailored to obtain specific material properties. A novel surface image assisted modeling framework is proposed to understand functional properties of the graphene enhanced polymer. The effective thermal and mechanical responses are assessed based on computational homogenization. For the mechanical response, the 2-D nanoplatelets are modeled as internal interfaces that store energy for membrane actions. The effective thermal response is obtained similarly, where 2-D nanoplatelets are represented using regions of high conductivity. Using the homogenization simulation, macroscopic stiffness properties and thermal conductivity properties are modeled and then compared to the experimental data. The proposed surface image assisted modeling yields reasonable effective mechanical and thermal properties, where the Kapitza effect plays an important part in effective thermal properties.

Nanoscale thermal transport in epoxy matrix composite materials reinforced with carbon nanotubes and graphene nanoplatelets

The technology related to hybrid filler-reinforced polymer matrix composite materials is growing at a high rate with increasing interest and usage. This study presents a way of increasing the thermal conductivity of polymer matrix composites by the use of a hybrid filler consisting of carbon nanotubes and graphene nanoplatelets and preliminarily clarifies the mechanisms that lead to the synergistic reinforcement of composite thermal conductivity at the nanoscale. The focus of this study was upon the fundamental relationships between nanometer-scale reinforcement structures and macroscopic composite thermal properties. The benefits and limitations associated with the incorporation of the hybrid filler into an epoxy matrix were evaluated. The results indicated that there exists an evident synergistic reinforcing effect between carbon nanotubes and graphene nanoplatelets on composite thermal conductivity. A significant increase has been gained in composite thermal conductivity, but low loading is required in order to exploit the benefits derived from the unique structure of the hybrid filler. Filler loading must be controlled very accurately in order to ensure that a critical threshold is not reached, beyond which there is a decrease in thermal conductivity, compared to that of graphene nanoplatelet-reinforced composites. The synergistic reinforcing benefits to composite thermal conductivity and is derived from effective conducting pathways formed between carbon nanotubes and graphene nanoplatelets within polymer matrices. The results can offer practical guidance on how to improve thermal transport properties for polymer matrix composite materials.

Development and Validation of Multiscale Thermo-Elasto-Viscoplastic Analysis Method for Plain-Woven Composites

In this study, the analysis method for thermomechanical properties of plain-woven composites is developed, and applied to thermoelastoviscoplastic analysis of plain-woven glass fiber-reinforced plastic (GFRP) composites. For this, a time-dependent constitutive equation depending on temperature for matrix materials is incorporated into the micro/meso/macro-scale thermo-elastic homogenization method for plain-woven composites developed by our research group. This method enables us to analyze thermoelastoviscoplastic properties in not only fiber bundles but also fibers and matrix materials in fiber bundles, as well as macroscopic thermal properties. This method is then applied to the thermal expansion analysis of a plain-woven GFRP composite subjected to a macroscopic temperature change from 25°C to 80°C before it is cooled to 25°C. Comparing the analysis results with experimental data, we validate the present method. It is also shown that the present method can evaluate themal residual stress and strain in the composite.

Size effect on the thermal conductivity of octadecanoic acid: A molecular dynamics study

Octadecanoic acid (OA) is well-known as an excellent phase change material (PCM) for heat storage due to its high energy density and narrow phase change temperature. In the practical application of PCMs, OA is often filled into the porous or microencapsulated matrix in micro/nanoscale forms. Generally, the thermal transport properties of OA are greatly subject to its size effect, and unfortunately only its macroscopic thermal transport properties are well studied in the composite field. To meet the demands of efficient OA-filled composite PCMs, OA’s nanoscale thermal transport properties are undoubtedly significant. In this study, an atomic simulation was conducted through a top-down approach based on equilibrium molecular dynamics to calculate the size-dependent thermal conductivity (κ) of OA in bulk, nanowire, and nanochain forms. The vibrational density of states and phonon overlap energy for the three forms of OA were compared to extract the size effect of κ. The largest κ value occurred for the bulk form while the smallest value occurred for the nanochain form. The limited sizes of nanowire forms reduce the atom vibration and weaken the phonon matching level, thus resulting in a lower κ than the bulk form. The curled structures of the nanochain forms exhibit higher molecular distances and more phonon scattering probabilities under weak van der Waals forces, leading to the lowest thermal transport. This study’s findings provide a clear understanding of the size dependence of thermal transport in OA for constructing OA-filled PCMs.