Thermal Conductivity Distribution Research Articles

Amino functionalized boron nitride and enhanced thermal conductivity of epoxy composites via combining mixed sizes of fillers

With the emergence of 5G communication and the rapid development of the microelectronics industry, the heat dissipation of high power circuits has become quite an important issue. Along these lines, the thermal conductivity distribution of the electronic packaging materials, which plays a key role in the protecting circuits, requires urgent improvement. In this study, amino-functional boron nitride nanosheets (BNNS) were prepared by employing ball milling boron nitride with urea (aqueous solution) as agents. Then, the epoxy composites filled with large size pristine boron nitride (pBN) and small size functional boron nitride were fabricated by using the wet ball-milling (wBN) technique. The acquired results indicate that the thermal conductivity property of the pBN/wBN/epoxy composites with pBN/wBN ratio of 2.5/7.5 can reach the value of 0.386 W/mK, which is 96% higher than that of pure epoxy. Meanwhile, the measured value is superior from both the pBN/epoxy and wBN/epoxy composites with the same filling amount. This effect can be attributed to the efficient construction of the fillers network and thermal conduction path. Within the epoxy matrix, wBN can fill the pores between pBN and form a denser filler network. In addition, the amino-functional groups grafted with wBN result in their enhanced dispersion within the epoxy matrix that leads to a more stronger interfacial effect. Our approach provides useful insights in understanding the incorporation mechanisms of fillers in polymers, and thereby enhancing their potential applications.

Performance investigation of a two-stage thermoelectric cooler with inhomogeneous materials

A novel model of two-stage thermoelectric cooler with inhomogeneous thermal conductivity in steady-state operating condition is established. The modification of the constant properties model allows controlling the distribution of Joule heat. Considering internal irreversibilities of the thermoelectric cooler, expressions for the cooling capacity, COP, and exergy efficiency are derived. By utilizing numerical methods, the temperature profile along the thermoelectric legs is presented. The optimal operating regions are explored. The COP vs. cooling capacity describing optimal operating regions in inhomogeneity materials are plotted. Meanwhile, the influence of the main parameters such as the variation of thermal conductivity distribution, cold-end temperature and the number of thermoelectric modules on the cooling performance is discussed in detail. Results indicate that the cooling capacity, COP and exergy efficiency are improved compared to those of homo?geneous two-stage thermoelectric coolers when an appropriate inhomogeneous property parameter is applied. The work can provide guidance on design of actual two-stage thermoelectric coolers with inhomogeneous materials.

Tailoring the thermal conductivity of functional cementitious composites with micro core-shell particles: A multiscale homogenization study

Micro core-shell particles have been highlighted in developing energy-efficient functional cementitious composites (FCCs). In this paper, a multiscale model is established to predict the thermal property of cementitious matrices containing micro core-shell particles. Based on the composite material theory, the interfacial thermal conductance and inclusion size distribution are introduced to the Mori-Tanaka homogenization scheme. Following the scale division of FCCs, the effective thermal conductivity is homogenized step by step from the cement paste level to micro-encapsulated cementitious composites level. In what follows, the coupling effects of composition, microstructural and physical aspects are quantified through the model parametrization. As validated by experimental results, accurate numerical predictions can be obtained with the variations of w/c ratio, hydration degree, and mix proportion. Numerical parameter analysis further reveals that the thermal conductivity and volume fractions of composition phases dominate the maximum thermal design range of FCCs, while the size-dependent interfacial thermal conductance matters more when the thermal conductivity of shell material is lower than that of the core material. The findings provide a theoretical basis for the thermal design of multi-phase composites, and contribute to the rational utilization of micro particles to achieve desirable thermal properties of FCCs.

Al2O3 Dispersion-Induced Micropapillae in an Epoxy Composite Coating and Implications in Thermal Conductivity.

Al2O3 particles with different sizes were dispersed into an epoxy precursor to improve the thermal conductivity (TC) of the epoxy coating. Al2O3 particles tend to aggregate in epoxy, and the aggregation becomes more apparent (formation of micropapillae when the particle size is larger than 1 μm) with the increase of particle size. The calculated fast aggregation rates of various-size Al2O3 particles in epoxy showed that the fast aggregation rate increased to a maximum rate of 6.37 × 10–20 m3·s–1 at a particle size of 200 nm and then decreased to a plateau value with the increase of particle size. The high fast aggregation rate caused the aggregation and the formation of nano- and micropapillae, causing the heterogeneous distribution of Al2O3 particles. These micropapillae were separated by epoxy, which made formation of continuous pathways fail, causing the reduction of TC and heterogeneous heat distribution. The highest thermal conductivity of 2.52 W/m·K and uniform heat distribution were observed at the optimum filler size of 30 nm. The research findings provide the knowledge of optimizing particle size on constructing a thermally conductive polymer composite.

Charged 4D Einstein-Gauss-Bonnet-AdS black hole in isobaric process: Thermal conduction, compressibility and Bose Einstein distribution

In this paper, we study Einstein-Gauss-Bonnet (EGB) black hole in 4D anti-de Sitter (AdS) spacetimes. We express all the thermodynamic parameters as a function of the GaussBonnet coupling α. The thermodynamics of black holes can be understood within the framework of the isobaric process, in this case, we show the heat flow and the thermal resistance for the thermal conduction. The physical aspects of this result is that α represents the thermal resistance of the black hole. As an application, we construct statistics of the EGB-AdS black hole undergo the Bose-Einstein statistics.

Toward miniaturizing microelectronics using covalent organic framework dielectric

Toward miniaturizing microelectronics using covalent organic framework dielectric

A reconstruction of Hamilton-Crosser model for effective thermal conductivity of nanofluids based on particle clustering and nanolayer formation

Although many models have been proposed to estimate the effective thermal conductivity (ETC) of nanofluids, the thermal conduction mechanisms need to be further addressed to improve the prediction accuracy of ETC model. In this paper, by fully considering the effects of particle clustering, Brownian motion, Kapitza resistance and nanolayer of particle, Hamilton-Crosser model is reconstructed to establish an improved model for the ETC of nanofluids. To develop this model, the particle clustering is characterized by the particle size distribution analysis, and the thermal conductivity distribution in the nanolayer is represented as a specific function of the distance from the nanoparticle. The influences of temperature, viscosity, particle size and other factors on the ETC of nanofluids are also included in this model. The results show that the accuracy of this model can be improved as compared to those considering only several of these factors, and the maximum error is 3% against the available experimental data. With this model, the inconsistency phenomena in ETC data of nanofluids can be explained in the view of the agglomeration and Brownian motion with the system conditions.

Variabilities and their upper and lower bounds of the equivalent thermal conductivity and resistance defined by the entransy dissipation rate

The prediction of equivalent thermal conductivity (ETC) and resistance (ETR) is an important topic in the composite material field. Many expressions of ETCs and ETRs have been proposed using different homogenization methods in last several decades. Especially, expressions defined by the entransy dissipation rate, keff and Reff, excel for their wide range of application. Usually, it was agreed that keff and Reff were determined by the thermal conductivity distribution inside. However, we find that they are also vary with the boundary temperature gradient distribution (TGD). In this paper, we simulate and mathematically prove the influence of boundary TGD on keff. The results indicate that keff with uniform boundary TGD is higher than that with non-uniform boundary TGD. In addition, the mathematical proof after a little adjustment is applied to confirm the minimum thermal resistance principle based on the uniform TGD inside. The results show that keff is the maximum when TGD are uniform in all regions including boundaries, and keff reaches the minimum when the non-uniformity of TGD extends to the limit. Upper and lower bounds of keff and Reff found in this paper are greatly valuable for optimizing the heat transfer ability and heat insulation ability of materials. And the methodology as well as conclusion in this paper can be reproduced in some generalized irreversible transport systems.

Three-dimensional patterned distribution of thermal conductivity in the volume for effective thermal concentration

For thermal devices and electronic systems, heat flow manipulation is critical to meet various needs. In this article, based on transformation thermodynamics, three-dimensional (3D) structures in the volume for patterned thermal conductivity were designed and fabricated. The 3D structures in the volume acting as heat flow routes can be achieved as pre-designed, providing a promising method to manipulate heat flow applied to the localized thermal concentration, thermal cloaking, etc. Simulation and experiments show that, by the 3D structures for thermal concentration, the heat flow could be concentrated to the pre-designed region, 7.0 K higher compared to the isotropic sample without any internal structures, and with a temperature gradient of over 1.3 K mm−1 to the surroundings (the heat source is 361 K), indicating an effective heat concentration. It also reveals that the heat flow could be accurately manipulated by carefully designing the geometric and material parameters of the internal structures, providing an alternative method to construct a 3D matrix for heat flow manipulation in the volume.

Three-dimensional numerical simulation of physical field distribution of radio frequency thermal plasma

Radio frequency (RF) thermal plasma involves abundant and complex physics. The understanding of the physical field distributions of the RF thermal plasma is helpful to its applications in industrial field. In this paper, an electro-thermal-magnetic-flow strong coupling mathematical and physical model of three-dimensional RF thermal plasma is established, the actual solenoid structure of the induction coil is considered, and a C++ code is developed for calculating the complex electromagnetic field in a customized version of the computational fluid dynamics commercial code FLUENT. The physical fields of RF thermal plasma, such as temperature field, flow field and electromagnetic field are studied. The electrical conductivity, thermal conductivity and viscosity distribution of the plasma are investigated. The results show that the physical field distribution of RF thermal plasma has an important non-axisymmetric three-dimensional effect due to the actual shape of the non-axisymmetric induction coil structure. The plasma discharge presents an annular distribution with a certain deflection angle. The distribution of plasma flow field shows a non-axisymmetric electromagnetic pump effect which is different from that of the two-dimensional model. The results have great guiding significance for optimizing and controlling the RF thermal plasma in various application areas.

The thermal properties of water-copper nanofluid in the presence of surfactant molecules using molecular dynamics simulation

In this research, using the molecular dynamics simulation, the thermal properties of water-copper nanofluid in a rectangular nanochannel in the presence of surfactant molecules are investigated. Water molecules are considered the base fluid, copper atoms as nanoparticles, and CTAB molecules are considered surfactants. In this paper, some parameters such as thermodynamic stability, thermal conductivity, and radial distribution performance are investigated. The effect of surfactant on thermal conductivity is also studied. The addition of surfactant molecules to the nanofluid improves the thermal behavior of atomic structures. The thermal conductivity of the nanofluid containing the surfactant molecules is higher than the simulated primary nanofluid. Generally, this study investigates the effect of interactions between the base fluid and the surfactant to improve the thermal efficiency of nanofluid. Also The effect of the amount of surfactant added to the base fluid on the thermal properties of the base fluid and nanofluid is investigated. Numerically, the addition of surfactant molecules to the nanofluid increases the thermal conductivity of the structure from 0.741 Wm−1 K−1 to 0.783 Wm−1 K−1.

Road Performance, Thermal Conductivity, and Temperature Distribution of Steel Slag Rubber Asphalt Surface Layer

Road Performance, Thermal Conductivity, and Temperature Distribution of Steel Slag Rubber Asphalt Surface Layer

Hierarchical thermal transport in nanoconfined water.

The structure of nanoconfined fluids is particularly non-uniform owing to the wall interaction, resulting in the distinctive characteristic of thermal transport compared to bulk fluids. We present the molecular simulations on the thermal transport of water confined in nanochannels with a major investigation of its spatial distribution under the effects of wall interaction. The results show that the thermal conductivity of nanoconfined water is inhomogeneous and its layered distribution is very similar to the density profile. The layered thermal conductivity is the coupling result of inhomogeneous density and energy distributions that are generally diametrical, and their contributions to the thermal conductivity compensate with each other. However, the accumulative effect of water molecules is really dominating, resulting in a high thermal conductivity in the high-density layers with the low-energy molecules, and vice versa. Moreover, it is found that the adsorptive and repulsive interactions from solid walls have different roles in the hierarchical thermal transport in nanoconfined water. The adsorptive interaction is only responsible for the layered distribution of thermal conductivity, while the repulsive interaction is responsible for the overall thermal conductivity; accordingly, the thermal conductivity is independent of the strength of water-solid interactions. The identified hierarchical thermal transport in nanoconfined water and its underlying mechanisms have a great significance for the understanding of nanoscale thermal transport and even the mass and energy transport of nanoconfined fluids.

Coatings utilization to modify the effective properties of high temperature packed bed thermal energy storage

High-temperature thermal energy storage is becoming more and more important as a key component in concentrating solar power systems and as an economically viable large-scale energy storage solution. Ceramics and natural rocks based packed beds are one of the attracting solutions. For application temperatures above 600 °C, radiation heat transfer becomes the dominant heat transfer phenomenon and it greatly influences the performance of thermal storage systems. Coatings with different thermal properties (mainly thermal emissivity and thermal conductivity) could be exploited to modify the effective thermal properties of packed beds. In this work, we present a methodology to account for the thermal effect of a coating layer applied over the pebbles of a packed bed. The influences on the packed bed effective thermal conductivity of several characteristics of the coating material, packed bed arrangement, and filler material are investigated. The results show that low emissivity coatings could reduce the effective thermal conductivity of a rock based packed bed of about 58%, with respect to a similar uncoated solution, already at 800 °C. A low emissivity coating could also limit the increase in the thermal effective conductivity from the cold to the hot zone of the storage. Coatings would have a higher influence when applied in packed beds with large size particles, relatively high thermal conductivity of the substrate and void fraction. The application of different coatings, with various thermo-physical properties, in different parts of the storage could modify the effective thermal conductivity distribution and enable a partial control of the thermocline degradation, increasing the storage thermal efficiency.

A gradient-distributed liquid-metal hydrogel capable of tunable actuation

Although thermoresponsive hydrogels have numerous applications that range from soft robots, biomedical engineering, and actuators to sensors for artificial muscles, the existing hydrogel actuators undergo only unidirectional deformation under a single thermal stimulus and suffer from slow actuation and unstable interfacial adhesion in multiple layers. Herein, hydrogels containing gradient-distributed polydopamine-coated eutectic gallium-indium (PDA-EGaIn) nanodroplets in a poly(N-isopropylacrylamide) (PNIPAM) matrix and thus featuring a gradient distribution of thermal conductivity and an increased barrier towards water loss are shown to be capable of a rapid and tuneable thermoresponse. Notably, whereas hydrogels with a low content of PDA-EGaIn undergo rapid one-way bending under a single thermal (45 °C) stimulus, those with a high content of PDA-EGaIn undergo sequential bidirectional (bending) actuation. The ability of these hydrogels to undergo fast and tuneable actuation under a single thermal stimulus makes them suitable for use in grab-release instruments and soft robots.

Machine-learning-assisted space-transformation accelerates discovery of high thermal conductivity alloys

We study the thermal conductivity distribution of hypothetical graphene-like materials composed of carbon and heavy carbon atoms. These materials are representative of alloys and disordered materials, which are relatively unexplored for thermal properties owing to their large configuration spaces. Since the full thermal conductivity calculations using the Boltzmann transport equation based solutions are computationally prohibitive for each of the 232 considered configurations, we employ regularized autoencoders, a class of generative machine learning models that transform the configuration space to the latent space in which materials are clustered according to the target property. Such conditioning allows selective sampling of high thermal conductivity materials from the latent space. We find that the model is able to learn the underlying thermal transport physics of the system under study and is able to predict superlattice-like configurations with high thermal conductivity despite their higher mass.

Estimation of Thermal Contact Conductances on Irregular Interfaces Using the Generalized Integral Transform Technique and the Reciprocity Functional Method

The reciprocity functional method, associated to the Classic Integral Transform Technique (CITT), has been successfully applied, obtaining analytical solutions for the inverse heat transfer problem that seeks to estimate the thermal contact conductance (TCC) distribution on the interface of a body composed of two materials. Yet, the theoretical development upon which this approach is based is not limited to the need of this interface to have a regular format. This work proposes to extend the method, thus obtaining an analytical development for the estimation of the TCC distribution on interfaces which are not necessarily regular. Several test problems were solved using the techniques described in this work, leading to very good results, with low CPU time usage by the computational implementation.

Nonlinear transport of rarefied Couette flows from low speed to high speed

The nonlinear transport properties and macroscopic flow features of rarefied plane Couette flows from low speed to high speed for a monatomic gas are investigated in detail using the direct simulation Monte Carlo (DSMC) method. The effective viscosity and thermal conductivity are directly computed from the DSMC results according to the linear constitutive relations. The detailed structure of the Knudsen layer (KL) and the functional dependence of the effective transport coefficients on local Knudsen numbers in the whole system are presented and compared with existing theoretical models. The results show that the effective viscosity and thermal conductivity distributions in the KL for different Mach number flows can be recast into the same profile (i.e., isothermal scaling function) in terms of a scaled wall distance η=∫0y1/λ(y)dy, though the local flow is nonisothermal. For all cases, the shear-stress Knudsen number distributions across the channel show a well opposite trend to the effective transport coefficient profiles. The functional dependence between them in the bulk region always coincides with the normal solution that is derived from the Boltzmann model equations for unbounded shear flows, while that in the KL for low-speed cases shows a large difference with the normal solution. As the Mach number increases, the DSMC data in the KL can also agree approximately with the normal solution at a large shear-stress Knudsen number. These results can be very useful for developing phenomenological models to describe a wall-bounded rarefied shear flow, showing a good prospect in both microflow and high-altitude applications.

Pulsed thermal imaging for non-destructive evaluation of hot gas path coatings in gas turbines

ABSTRACT To address global research in energy technologies, a UK–US collaboration was setup to look at implications in the use of alternative gas turbine liquid/gaseous fuels and first-generation IGCC-derived syngas. The development of predictive models for deposition, corrosion and component living in gas turbines operating on such novel fuel gases is now being developed. Linked to this, the non-destructive inspection of hot gas path components needs to be refined and the life prediction models utilising thermal barrier coatings need to be validated to enable the on-going assessment of the remnant lives of components during their use. Thermal barrier coatings (TBCs) have been critical to the operation of gas turbines in aircraft and land-based applications. As the engine demands increase with respect to operational temperature and efficiency, so has the requirement for TBCs, both from the perspective of their performance (thermal conductivity, durability) as well as their reliability. Because TBCs play critical role in protecting the underlying super alloy, their failure (spallation) cause accelerated component damage leading to unplanned outage. Therefore, it is important to inspect and monitor the TBC condition to assure its quality and reliability. Non-destructive evaluation (NDE) methods would allow for direct determination of TBC thermal conductivity on coated components and, therefore, they can be used to inspect the quality of as processed components and monitor TBC degradation during service. This paper presents a new method, the pulsed thermal imaging–multilayer analysis (PTI–MLA) method, which can measure the coating thermal conductivity and heat capacity distributions for coatings on different substrates and thickness. NDE methods were also evaluated based on preliminary experimental results for TBC samples that were thermal cycled to various lifetimes to monitor TBC degradation and predict TBC life. Initial insight into the TBC response with painted and unpainted surfaces is also discussed to demonstrate next steps.

Ballistic-Diffusive Heat Conduction in Thin Films by Phonon Monte Carlo Method: Gray Medium Approximation Versus Phonon Dispersion

Abstract The gray medium approximation treating all phonons with an averaged and representative mean-free-path (MFP) is an often used method in analyzing ballistic-diffusive heat conduction at nanoscale. However, whether there exists a reasonable value of the average MFP which effectively represents the entire spectrum of modal MFPs remains unclear. In this paper, phonon Monte Carlo (MC) method is employed to study the effects of the gray medium approximation on ballistic-diffusive heat conduction in silicon films by comparing with dispersion MC simulations. Four typical ways for calculating the average MFP with gray medium approximation are investigated. Three of them are based on the weighted average of the modal MFPs, and the remaining one is based on the weighted average of the reciprocals of the modal MFPs. The first three methods are found to be good at predicting effective thermal conductivity and heat flux distribution, but have difficulties in temperature profile, while the last one performs better for temperature profile than effective thermal conductivity and heat flux distribution. Therefore, none of the average MFPs can accurately characterize all the features of ballistic-diffusive heat conduction for the gray medium approximation. Phonon dispersion has to be considered for the accurate thermal analyses and modeling of ballistic-diffusive heat transport. Our work could be helpful for further understanding of phonon dispersion and more careful use of the gray medium approximation.