Effective thermal conductivity of polymer composites: a review of analytical methods

Kosbe, Pradnya; Patil, Pradeep A.

doi:10.1080/01430750.2018.1557544

Cited by 17 publications

(14 citation statements)

References 63 publications

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“…where 𝑐 𝑘 is the curvilinear abscissa along the k-th edge of ∂Ω, edge having lengths 𝑙 𝑘 . Setting 𝜆 𝑘 = 𝑐 𝑘 /𝑙 𝑘 we can parametrize the edge as follows 𝝆(𝜆 𝑘 ) = 𝝆 𝑘 + 𝜆 𝑘 (𝝆 𝑘+1 − 𝝆 𝑘 ) = 𝝆 𝑘 + 𝜆 𝑘 𝛥𝝆 𝑘 (11) so that…”

Section: The Eshelby Tensor Analytic Expression Of Arbitrarily Shaped...mentioning

confidence: 99%

Thermal Conductivity Prediction of Metal Matrix Particulate Composites: Theoretical Methodology and Application

Chen

Wang

et al. 2023

Preprint

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To make more accurate predictions of the effective thermal conductivity of the composites, a systematic method for predicting the effective thermal conductivity of metal matrix particle composites with arbitrarily shaped particles was proposed, and the geometry of random particles with controlled shape characteristics is reconstructed. In addition, the geometric vertices of the reconstructed particles are used to characterize the morphology of inclusions with complex profile in two-dimensional isotropic elasticity, and its explicit expression for the Eshelby tensor are explored. Moreover, the material mismatch between the particles and the matrix phase is simulate using a continuously distributed source field based on the Eshelby's equivalent inclusion method. The relationship between micro-structure and effective performance is established. Finally, the effective thermal conductivity of CuCr alloys was predicted using the ETC prediction model. Through the comparison of the numerical simulations, experiments, and calculations, the results show that the ETC model has reliable predictive capability.

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Section: The Eshelby Tensor Analytic Expression Of Arbitrarily Shaped...mentioning

confidence: 99%

Thermal Conductivity Prediction of Metal Matrix Particulate Composites: Theoretical Methodology and Application

Chen

Wang

et al. 2023

Preprint

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“…26 The accuracy of analytical models can be improved by including structural characteristics and heat transferrelated phenomena in the model. 27 Analytical thermal conductivity models can study the effective thermal conductivity of bulk, 28 composite, 22,29 and porous 30 structures. In this work, different models available for composite structures were used to develop a modified series-parallel model for porous composites (MSPC model).…”

Section: Theorymentioning

confidence: 99%

Analytical effective thermal conductivity model for colloidal porous composites and nanocomposites based on novolac/graphene oxide aerogels

Nazari

Allahbakhsh

Bahramian

2022

Intl J of Energy Research

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The performance of porous composite materials in thermal energy storage and management applications can be engineered by controlling the relationship between the heat transfer mechanism and the structure of these materials. Analytical thermal conductivity models are essential tools to study and manage such structure/heat transfer relations in porous composite materials. This study develops an analytical thermal conductivity model for porous composites with colloidal matrix morphologies. The model developed here is a modified series-parallel model that considers important structural parameters such as the system's porosity, the colloidal size of the matrix, and the filler's aspect ratio. Moreover, essential effects in the structure of porous composites, including the gas-solid coupling effect and contact length of particles, are also included in the model developed here. In addition, this model can be used in a wide range of porosity and can predict the thermal conductivity of porous composites with appropriate accuracy by changing temperature, pressure, specific surface area, porosity, and other textural properties. Novolac/graphene oxide nanocomposite aerogels with different contents of graphene oxide (GO) nanosheets in the structure were prepared and used to study the validity of the data calculated using the developed model. Our results confirmed that

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“…There has been a growing interest in polymer composites during the last decades. The significantly enhanced mechanical and thermal properties of such polymers caused by the incorporation of a small amount of a reinforcing filler, [ 1,2,11–15,3–10 ] has caught the attention of both the academic and industrial sectors. For this reason, carbon‐based materials of different shapes in nano and micro scale have been proposed as a multifunctional filler to enhance the polymer matrices [ 2,5,21–25,8–10,16–20 ] due to their outstanding mechanical performance, thermal, and electrical conductivity.…”

Section: Introductionmentioning

confidence: 99%

Graphite reinforced silane crosslinked high density polyethylene: The effect of filler loading on the thermal and mechanical properties

et al. 2020

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Crosslinked polyethylene is a promising polymer regarding its mechanical properties and wear resistance, predominantly used in pipework systems. However, it suffers from low thermal conductivity, which limits its application in geothermal heating/cooling systems. In this work, crosslinked high‐density polyethylene (PEX) composites with spherical graphite (SG) as a reinforcing filler are examined in terms of their thermal and mechanical properties. Thermal conductivity measurements showed a significant improvement of the thermal conductivity of PEX with increasing filler content (40.6% augmentation for 5 wt% SG content), while the experimental data are in good agreement with the Chauhan theoretical model for spherical particles. Tensile tests revealed that the elastic modulus of PEX/SG composites presented a considerable improvement (23.6% augmentation for 5 wt% SG content). Various micromechanical models for the prediction of the composites' elastic behavior were applied to the experimental data, which present a satisfactory agreement with the Takayanagi I two‐phase model for low concentrations of SG, and the Takayanagi II two‐phase model for higher filler content.

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Effective thermal conductivity of polymer composites: a review of analytical methods

Cited by 17 publications

References 63 publications

Thermal Conductivity Prediction of Metal Matrix Particulate Composites: Theoretical Methodology and Application

Thermal Conductivity Prediction of Metal Matrix Particulate Composites: Theoretical Methodology and Application

Analytical effective thermal conductivity model for colloidal porous composites and nanocomposites based on novolac/graphene oxide aerogels

Graphite reinforced silane crosslinked high density polyethylene: The effect of filler loading on the thermal and mechanical properties

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