Thermal Conductivity Of Composite Materials Research Articles

Thermal Performance Simulation of MWNT/NR composites Based on Levenberg-Marquard Algorithm

In this paper, Levenberg-Marquard algorithm was used to simulate thermal performance of aligned carbon nanotubes-filled rubber composite, and the effect of temperature, filling amount, MWNTs orientation and other factors on thermal performance were studied. The research results showed: MWNTs orientation can greatly improve the thermal conductivity of composite materials, the thermal performance improvement of overall orientation was higher than the local orientation. Volume fraction can affect thermal performance, thermal conductivity increased with the increase of volume fraction. Temperature had no significant effect on the thermal conductivity. The simulation results correlated well with experimental results, which showed that the simulation algorithm is effective and feasible.

Micromechanical modeling of the anisotropic thermal conductivity of ellipsoidal inclusion-reinforced composite materials with weakly conducting interfaces

The present paper deals with the micromechanical modeling of the effective thermal conductivity of composite materials containing ellipsoidal inclusions with interfaces thermal resistance. At these interfaces between inclusions and the surrounding medium, the heat flux is assumed continuous while the temperature field undergoes to a discontinuity. The solution of this problem of heterogeneous thermal conductivity is obtained thanks to a micromechanical approach based on the generalized Eshelby's thermal conductivity tensor and the Kapitza’s interface thermal resistance model. Moreover, the present study is conducted in the general case of an anisotropic thermal conductivity of each phase and the inclusions are assumed to have an ellipsoidal shape.Results in terms of the thermal intensity field localization inside each phase are presented and then analyzed in light of the effects of some model parameters. The effective thermal conductivity of the equivalent material has been predicted through classical homogenization schemes such as the Mori-Tanaka, the Self-consistent, the Generalized self-consistent and the Differential scheme. The model predictions have been also compared with results provided by previous investigations.

Prediction of thermal conductivity of composite polymer materials filled with expanded graphite sheet fillers

Adding fillers of high thermal conductivity to the base polymer materials is a solution to make composites of high thermal conductivity. Expanded graphite sheets have been recognized as an economic and efficient filler material to make composite polymers of high conductivity. However, the prediction of the effective thermal conductivity of the composite materials is a difficult task due to the random nature in fillers distribution. The anisotropic properties of the sheet fillers make the heat transfer analysis difficult. In this study, a conjugate heat conduction model considering the random distribution nature of fillers is set up and numerically solved. A validated commercial software FLUENT and finite volume method was used in the analysis. Then an experiment is done to validate the model. The numerical results are used to summarize a correlation for the prediction of the effective thermal conductivity of the composite materials. It is found that the filler height to thickness ratio plays an important role in intensifying the heat conduction in the composite materials. At a given filler content, the graphite sheets should be fabricated thin enough to have higher height to thickness ratios and consequently higher performance in effective conductivity.

Thermal conductivity of energy conversion and storage composite materials packing with short fiber fillers and artificial size cylinder fillers

Enhancement of the thermal conductivity of energy conversion and storage composite materials has become more and more common in energy conversion and storage system by applying high thermally conductive fillers. In this paper, the effect of volume fraction, the thermal conductivity ratio between the fillers and matrix materials and the height to diameter ratio have been considered as three factors that influence the thermal conductivity of composite materials. It is found that the thermal conductivity of composite materials increases with the volume fraction, the thermal conductivity ratio and the height to diameter ratio. The thermal conductivity of composite materials increases in a linear form both with the volume fraction and the height to diameter ratio at a low volume fraction. This trend will both change to a nonlinear form when the volume fraction grows higher. A new generalized correlation is proposed by using the method of nonlinear regression based on the extensive results of numerical study. The new correlation can be used to predict the thermal conductivity of short fiber fillers and artificial size cylinder fillers at a large range of conductivity (1⩽κ⩽900) and volume fraction(0⩽ϕ⩽0.2).

A statistical model for effective thermal conductivity of composite materials

Thermal interface materials composed of polymers and solid particles of high thermal conductivity have been used widely in electronic cooling industries. However, theoretical prediction of effective thermal conductivity of the composites remains as a crucial research topic. Theoretical modelings of the effective thermal conductivity of composites were based mainly on the analog between electric and thermal fields that satisfy Laplace equation under steady condition. Two approaches were employed, either by solving the Laplace equation or by equating the composite to a circuit network of conductors. In this study, the existing models obtained from these two approaches are first briefly reviewed. However, a close examination of the second approach reveals that there exists a paradox in this approach. To resolve this paradox, a statistical approach is then adopted. To this end, a mesoscopic ensemble that contains microscopic states is first constructed. The thermal conductivities of the microstates are identified by the principle of least action. A statistical parameter for each microstate is identified to characterize the effect of interface resistance on heat flow, as well as the connection between microstates. Effective thermal conductivity of the ensemble was then obtained from the variation principle that minimizes the standard deviation with optimal distribution of the parameter. The predictions by the present statistical model fit to experimental data with excellent agreement.

A reconstruction of Maxwell model for effective thermal conductivity of composite materials

Composite materials consisting of high thermal conductive fillers and polymer matrix are often used as thermal interface materials to dissipate heat generated from mechanical and electronic devices. The prediction of effective thermal conductivity of composites remains as a critical issue due to its dependence on considerably factors. Most models for prediction are based on the analog between electric potential and temperature that satisfy the Laplace equation under steady condition. Maxwell was the first to derive the effective electric resistivity of composites by examining the far-field spherical harmonic solution of Laplace equation perturbed by a sphere of different resistivity, and his model was considered as classical. However, a close review of Maxwell’s derivation reveals that there exist several controversial issues (deficiencies) inherent in his model. In this study, we reconstruct the Maxwell model based on a potential mean-field theory to resolve these issues. For composites made of continuum matrix and particle fillers, the contact resistance among particles was introduced in the reconstruction of Maxwell model. The newly reconstructed Maxwell model with contact resistivity as a fitting parameter is shown to fit excellently to experimental data over wide ranges of particle concentration and mean particle diameter. The scope of applicability of the reconstructed Maxwell model is also discussed using the contact resistivity as a parameter.

High Thermal Conductive Insulation Composite Materials

Compact design and smart device has becoming a popular trend for electric and electronic application. With the increase of power and function, the heat accumulation is a new challenge. High thermal conductive insulation material becomes a hot research area in recent years. The current paper reviews the recent progress of high thermal conductive insulation material; and the influence of the composition, structure regularity of resin, functional filler, manufacture process on the thermal conductivity of composite material is discussed. The open topics and future trend are also summarized.

Investigation of nanoparticle agglomeration on the effective thermal conductivity of a composite material

The viability of organic phase change materials (PCMs), such as paraffin wax, for passive thermal management of portable electronics improves if the PCM overall bulk thermal conductivity is increased through the addition of highly conducting nanoparticles. Previous work has suggested the possibility of increasing the bulk thermal conductivity of composite materials through the controlled agglomeration of nanoparticles, yet no theoretical study has been performed to investigate the conditions under which the bulk thermal conductivity enhancement is achieved. Therefore, this study examines the influence of both spherical clustering and linear percolation network formation on the resultant bulk conductivity. This approach uses effective medium and percolation theories for unpercolated and percolated areas, respectively. Theoretical approaches are shown for spherical clustering and a 1-d conduction model of linear percolation networks, and finite element analysis (FEA) is used for a 2-d conduction model of linear percolation networks. The results for herringbone graphite nanofibers (HGNFs) in a paraffin matrix suggest that spherical clustering and linear agglomeration tend to reduce the bulk thermal conductivity, which agrees with experimental observations. However, linear percolation networks may enhance the effective thermal conductivity when large inclusion–matrix to inclusion–inclusion Kapitza resistance ratios are used.

Extraordinary synergy in the thermal and electric properties of polymer matrix reinforced with hybrid fillers

The effect of the incorporation of different combinations of electric conducting and non‐conducting nanofillers into epoxy resin on the thermal and electric conductivity was studied. Graphite nanoplatelets (GNPs), multi‐wall carbon nanotubes (MWCNTs) and carbon fibers (CFs) were used as the conductive fillers. The non‐conductive ones were boron nitride (BN) or barium hexaferrite (BaFe12O19). The content of nanocarbon in composite materials (CMs) was varied from 1.0 to 6.0 vol%, the content of dielectric filler in composite materials was equal to 15.0 vol% boron nitride and 8.0 vol% BaFe12O19, respectively. The combination of electroconductive nanocarbon and non‐conductive boron nitride particles showed an increase of the thermal conductivity (by a factor of 2 for hybrid composite materials boron nitride/graphite nanoplatelet/epoxy (4.5 vol% of nanocarbon) compared to the thermal conductivity of composite materials with single graphite nanoplatelets filler) and the electric conductivity, whereas the hybrid conductive fillers of various morphology (graphite nanoplatelets/carbon nanotubes or graphite nanoplatelets/carbon fibers) did not show an improvement. On the other hand, the use of graphite nanoplatelets/carbon nanotubes and graphite nanoplatelets/carbon fibers hybrid fillers lead to the anisotropy of the electric conductivity and a reversible change of the electric resistance after a compression up to 50 MPa due to improved elastic properties.

A Study on Nanocomposites Behavior at Heating

Published literature is rich with investigations of mechanical properties of composites, but fewer publications are focused on thermal properties. Several publications addressing different theoretical approaches for predicting thermal conductivity of composite materials have been noted. However, one of the publications has discussed both transverse and axial thermal conductivity of a carbon fiber composite. A non-linear increase in the thermal conductivity was reported with the increase of fiber volume fraction of plain weaves and no theoretical models are able to predict this non-linearity. The result of literature search even further identified the necessity and importance of carrying out further investigations on thermal behavior of composites materials. Thermal conductivity of composites is anisotropic in nature and data about thermal conductivity of resin is known to reduce stresses related to shrinkage of composites during cure and mismatch in thermal expansion coefficients. Before conducting experiments to determine thermal conductivity of various composites, knowledge about effect of different parameters influencing thermal conductivity is essential. This paper deals with an analytical study on few nanocomposites behavior at heating.

Theoretical Considerations on Fibre Reinforced Composites Thermal Conductivity Uncertainties

Thermal conductivity of composites is anisotropic in nature and data about thermal conductivity of resin facilitates to reduce stresses related to shrinkage of composites during cure and mismatch in thermal expansion coefficients. Before conducting experiments to determine thermal conductivity of various composites, knowledge about effect of different parameters influencing thermal conductivity is essential. The increasing use of composites, for various applications, emphasizes its importance/significance in the thermal property analysis of an engineering system. Published literature is rich with investigations of mechanical properties of composites, but fewer publications are focused on thermal properties. Several publications addressing different theoretical approaches for predicting thermal conductivity of composite materials have been noted. Various theoretical approaches are used to yield the thermal conductivity of a composite material so that the heat flow in anisotropic composite material in any direction can be estimated. In this paper few models will be considered and a theoretical study on thermal conductivity uncertainties will be conducted and discussed. The results identified the need and importance of carrying out further investigations on thermal behavior of composites materials.

Influence of Carbon Nanotubes Dispersion on Thermal Properties of Copper-Carbon Nanotubes (CNTs) Composite Materials

In this present work, two methods for dispersing carbon nanotubes into the copper matrix were tested: a Solid Route process where CNTs are simply mixed with the copper powder and a Liquid Route process where CNTs are dispersed in a copper salt solution and then mixed with the metallic copper powder. Powders are sintered by uni-axial hot pressing process under vacuum atmosphere at 650°C and thermal conductivities of composite materials were measured using the laser flash method. Results are compared with a theoretical model of Nan et al. which enables to predict the thermal conductivity of materials containing CNTs. Comparison of experimental and theoretical results tends to prove that CNTs are 2D-randomly dispersed in a plane perpendicular to the pressing direction during uni-axial hot pressing process. Moreover, an increase of +7% of the thermal conductivity is shown for the composite material containing 1 vol. % of CNTs into the copper matrix.

Mesoscale model for thermal conductivity of concrete

Thermal conductivity of coarse aggregate, cement mortar as well as concrete were measured by means of a guarded hot plate apparatus and/or a transient plane source. Influences of sand ratio, type and volume fraction of aggregate, water–cement ratio, saturation degree and load level on thermal conductivity of concrete were investigated. By using the theoretical model for thermal conductivity of composite materials, interfacial thermal resistance between cement mortar and coarse aggregate were studied further. The results show that thermal conductivity of concrete increases with the increasing saturation degree, volume fraction and thermal conductivity of aggregate, but decreases with the increasing water–cement ratio and load level. And interfacial thermal resistance coefficient decreases with the increasing saturation degree; therefore, interfacial thermal resistance must be considered when calculating thermal conductivity of concrete. Finally, mesoscale models were established for thermal conductivity of undamaged concrete in dry and unsaturated states based on the Maxwell’s model. In addition, a mesoscale model was proposed for thermal conductivity of damaged concrete; this model is based on the assumption that damaged concrete was isotropic and damaged phase was served as an insulator. Mesoscale models can be used to predict the effective thermal conductivity of concrete under different states and the predicted values were all in acceptable agreement with the experimental values.

Cross-property connections for copper–graphite composites

Copper–graphite composite materials in the range of 0–10 vol% of carbon phase were prepared from the mixture of copper and graphite powders by hot isostatic pressing. The microstructure, mechanical (tensile strength, elongation to fracture) and physical (electrical and thermal conductivity) properties of composite samples were investigated, and the cross-property connections were calculated. It was shown that electrical and thermal conductivity cross-property (Lorenz number) is almost constant and increases only slightly (no more than 10 % increase was observed). This implies that in the investigated composition range the Lorenz number of a copper–graphite composite system behaves according to Franz–Wiedemann law for pure metals at constant temperature. On the contrary, the conductivity to tensile strength cross-property connections showed significant linear increase (over 200 % in the investigated composition range) for both electrical conductivity and thermal conductivity of composite materials. The cross-property connections of conductivity to the elongation to fracture exhibit a nonlinear dependence on the volume fraction of graphite.

Synergistic improvement of thermal conductivity in polymer composites filled with pitch based carbon fiber and graphene nanoplatelets

We found that the thermal conductivity of composite materials was synergistically enhanced by the simultaneous incorporation of well-dispersed pitch-based carbon fibers (PCFs) and graphene nanoplatelets (GNPs) into the matrix. Accordingly, this study investigated the causes of such enhancement and attempted to optimize the thermal conductivity. The solvent-free composites fabrication method based on powder mixing and in-situ polymerization proposed recently was employed to achieve a uniform dispersion of fillers of different sizes and shapes. The isotropic and in-plane thermal conductivity of the composite containing both uniformly dispersed 5 wt% of PCF and 15wt% of GNP achieved improvements of 82% and 183% when compared to those containing 20 wt% of GNP, and improvements of 65% and 74% when compared to those containing 20 wt% of PCF, respectively. The synergistic improvement of the thermal conductivity was maximized at the optimized composition due to the most efficient formation of thermally-conductive pathways and internal structures favorable for phonon transport.

Experimental and theoretical studies of effective thermal conductivity of composites made of silicone rubber and Al2O3 particles

In this study, effective thermal conductivities of composite materials were investigated both experimentally and theoretically. The composites made of silicone rubber and spherical Al2O3 particles of four mean diameters were prepared with various volume fractions. Experimental results indicate that the effective thermal conductivity increases nonlinearly with increasing particle volume fraction and is higher for larger particles, indicating its dependence not only on conductivities and volume fraction, but also on the materials' interfacial geometry. The experimental results were used to evaluate the performance of theoretical models. It was found that the models by Deissler and Boegli and by Maxwell that contain no parameter for interfacial effects were unable to predict the experimental results. On the other hand, the models by Hsu et al. and by Agari and Uno that provide interfacial contact parameters fit very well with the data over the whole ranges of the present experiment.

How to enhance the effective thermal conductivity of composite material based on optimization method?

Filling a finite amount of high thermal conductivity materials into the base material to enhance the ETC (effective thermal conductivity) of the composite has attracted intensive interests, but how to disperse the fillers apparently poses a question. In the present study, we investigate the enhancement of ETC through altering the distribution of the fillers with an optimization method which is inspired by the volume-to-point heat conduction problem. The theoretical model is first validated by the theoretical results of the Parallel and Series models. Then it is used to investigate the way how to fill the high thermal conductivity materials. It is found that the distribution of fillers changes gradually from parallel type to series type as the relative location of temperature gradient of filling location is away from the highest temperature gradient. The closer to the highest temperature gradient, the larger ETC of the composite is. The optimized ETCs are compared with those of the random distributions, which indicate that the distribution obtained by the optimization method can achieve better ETC enhancement than the corresponding random distribution in the range of relative locations between 0.04 and 0.3. The information provided here can be useful for fabricating the composite material.

Lattice Boltzmann Modeling of Thermal Conduction in Composites with Thermal Contact Resistance

AbstractThe effective thermal conductivity of composite materials with thermal contact resistance at interfaces is studied by lattice Boltzmann modeling in this work. We modified the non-dimensional partial bounce-back scheme, proposed by Han et al. [Int. J. Thermal Sci., 2008. 47: 1276-1283], to introduce a real thermal contact resistance at interfaces into the thermal lattice Boltzmann framework by re-deriving the redistribution function of heat at the phase interfaces for a corrected dimensional formulation. The modified scheme was validated in several cases with good agreement between the simulation results and the corresponding theoretical solutions. Furthermore, we predicted the effective thermal conductivities of composite materials using this method where the contact thermal resistance was not negligible, and revealed the effects of particle volume fraction, thermal contact resistance and particle size. The results in this study may provide a useful support for materials design and structure optimization.

Effect of the Carbon Nanotube Distribution on the Thermal Conductivity of Composite Materials

Finite element analysis has been employed to investigate the effect of carbon nanotubes (CNTs) distribution on the thermal conductivity of composite materials. Several kinds of representative volume elements (RVEs) employed in this study are made by assuming that unidirectional CNTs are randomly distributed in a polymer matrix. It is also assumed that each set of RVEs contains a constant fiber volume fraction and aspect ratio. Results show that randomness—the way in which fibers are distributed inside the matrix—has a significant effect on the thermal conductivity of CNT composites. Results of this study were compared using the analytical Xue and Nan model and good agreement was observed.

The Dependence of the Thermophysical Properties of Filled Fluoroplastics on the Temperature and Concentration of Fillers

The results of measuring the specific heat and thermal conductivity of composite materials based on a polytetrafluoroethylene matrix with different volume fractions of disperse fillers – powders of coke, molybdenum disulphide, and finely disperse diamonds – in the temperature range 200–550 K are presented.