Fundamental and estimation of thermal contact resistance between polymer matrix composites: A review

Zhou, Tian; Zhao, Yahui; Rao, Zhenghua

doi:10.1016/j.ijheatmasstransfer.2022.122701

Cited by 58 publications

(7 citation statements)

References 126 publications

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“…Numerous studies have shown that different types, dimensions, and sizes of fillers can affect the thermal performance of polymer composites. [24][25][26] Among thermally conductive fillers, 1-D fiber fillers can form a thermally conductive network more effectively. 27,28 Unfortunately, the common 1-D fillers are all conductive materials, such as silver nanowires, copper nanowires, etc., which are difficult to ensure the insulation performance of composites.…”

Section: Introductionmentioning

confidence: 99%

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Highly thermally conductive electrically insulating composites composed of core–shell structure fiber boron nitride@titanium dioxide filler

Yang,

Feng,

Liang

et al. 2023

Polymer Composites

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With the increasing integration and power density of electronic and electrical equipment, highly thermally conductive insulating materials have a wide range of application scenarios. In this paper, a novel core–shell structure fiber thermal conductive filler hexagonal boron nitride@anatase titanium dioxide (h‐BN@AT) has been prepared by electrospinning technology first. The h‐BN@AT/epoxy resin (EP) thermally conductive and insulating composite was prepared by hot pressing. When the filler content was 30 wt%, the optimal thermal conductivity (λ) of h‐BN@AT/EP composite was 7.62 W/(m·K) (in‐plane) and 0.76 W/(m·K) (out‐of‐plane), which were 3088% and 324% higher than EP. The incorporation of high aspect ratio core–shell structural fibers significantly improves the efficiency of thermal conduction (TC) pathways formation within the composite. Moreover, the utilization of one‐dimensional (1‐D) anatase titanium dioxide fiber (ATO) and two‐dimensional (2‐D) boron nitride (h‐BN) establishes a multi‐level TC channel in EP, significantly increasing the λ of the composite. Notably, the composite retains outstanding insulation properties. The innovative core–shell structural fibers filler developed in this study provides a feasible method for producing thermal conductivity insulating materials.Highlights A new type of core–shell structure h‐BN@AT fiber filler is designed. High thermal conductivity insulating composite h‐BN@AT/EP are prepared by hot pressing. h‐BN@AT can effectively improve the thermal conductivity of composite to ensure good electrical properties. The effect of h‐BN content in h‐BN@AT filler on the properties of the composite was obtained. The superiority of h‐BN@AT in heat conduction is verified by the classical heat conduction model and simulation.

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Section: Introductionmentioning

confidence: 99%

“…Numerous studies have shown that different types, dimensions, and sizes of fillers can affect the thermal performance of polymer composites 24–26 . Among thermally conductive fillers, 1‐D fiber fillers can form a thermally conductive network more effectively 27,28 .…”

Section: Introductionmentioning

confidence: 99%

Highly thermally conductive electrically insulating composites composed of core–shell structure fiber boron nitride@titanium dioxide filler

Yang,

Feng,

Liang

et al. 2023

Polymer Composites

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“…31 Materials' thermal characteristics are required to monitor the reaction equilibria, estimate the products' energy content, and obtain the adiabatic temperature at the gasification unit. 13,32 The biomass heat capacity is a fundamental thermophysical property required to calculate the standard molar thermodynamic functions and reaction equilibria to design a highly efficient reactor for plant biomass processing. 33 Moreover, precise knowledge of the working capacity and thermodynamic properties of biomass samples are required for effective plant processing, while lack of enough information on the thermodynamic properties of cellulose and lignin is one of the main challenges in developing the biomass industry.…”

Section: Introductionmentioning

confidence: 99%

“…Materials' thermal characteristics are required to monitor the reaction equilibria, estimate the products' energy content, and obtain the adiabatic temperature at the gasification unit 13,32 . The biomass heat capacity is a fundamental thermophysical property required to calculate the standard molar thermodynamic functions and reaction equilibria to design a highly efficient reactor for plant biomass processing 33 .…”

Section: Introductionmentioning

confidence: 99%

Determination of the heat capacity of cellulosic biosamples employing diverse machine learning approaches

Karimi

Khosravi

Fathollahi

et al. 2022

Energy Science & Engineering

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Heat capacity is among the most well‐known thermal properties of cellulosic biomass samples. This study assembles a general machine learning model to estimate the heat capacity of the cellulosic biomass samples with different origins. Combining the uncertainty and ranking analyses over 819 artificial intelligence models from seven different categories confirmed that the least‐squares support vector regression (LSSVR) with the Gaussian kernel function is the best estimator. This model is validated using 700 laboratory heat capacities of four cellulosic biomass samples in wide temperature ranges (absolute average relative deviation = 0.32%, mean square errors = 1.88 × 10−3, and R2 = 0.999991). The data validity investigation approved that only one out of 700 experimental data is an outlier. The LSSVR model considers the effect of the cellulosic samples' crystallinity, temperature, and sulfur and ash content on their heat capacity. The overall prediction accuracy of the LSSVR is more than 62% better than the achieved accuracy using the empirical correlation.

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“…A condutância térmica de contato em si é um tema de pesquisa em transferência de calor por condução que vem sendo estudado ao longo de muitos anos e que permanece sendo um tema desafiador. Muitos trabalhos, especialmente nesta última década, se dedicaram na proposta de metodologias experimentais de condutância térmica de contato [11][12][13][14], em aplicações e na sua identificação envolvendo a solução de problemas inversos, que tipicamente são resolvidos por meio de abordagens analíticas e Bayesianas. Os primeiros, tem sua solução obtida por meio de métodos que não envolvem uma análise sob incerteza das estimativas e dos demais parâmetros presentes nos modelos utilizados, como métodos envolvendo gradiente conjugado ou funcionais de reciprocidade [2,[15][16][17][18][19][20][21][22][23][24].…”

Section: Introductionunclassified

Estimativa da Variação Temporal de Condutância Térmica de Contato em Placas Termicamente Finas via Método MCMC

Watanabe¹,

Abreu²,

Knupp³

et al. 2022

VETOR

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Este trabalho trata da solução de um problema inverso de condução de calor visando estimar a variação temporal de condutância térmica de contato, num problema unidimensional em um material de duas camadas termicamente finas, aquecidas por meio de um fluxo de calor aplicado na superfície superior e exposto a convecção térmica na superfície inferior. Para a formulação do problema direto, considerando placas termicamente finas, foi utilizado o método Classic Lumped. Esta formulação reduz o problema original em duas equações diferenciais ordinárias acopladas, desta forma, possibilita diminuir o custo computacional necessário para solucionar o problema direto associado, que foi resolvido utilizando a função NDSolve, intrínseca do software Mathematica. Para a solução do problema inverso foi utilizado o método Monte Carlo via Cadeias de Markov, dentro de uma abordagem Bayesiana, aplicando o algoritmo de Metropolis-Hastings. O método foi analisado a partir de medidas simuladas de temperatura e se mostrou capaz para estimar uma função temporal da condutância térmica de contato. Esta metodologia permite levar em conta as incertezas associadas aos parâmetros presentes nos modelos, bem como, àquelas associadas com a estimativa da condutância térmica variando com o tempo, o que não é observado nos métodos voltados para estimativa temporal da condutância térmica de contato encontrados atualmente na literatura.

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Fundamental and estimation of thermal contact resistance between polymer matrix composites: A review

Cited by 58 publications

References 126 publications

Highly thermally conductive electrically insulating composites composed of core–shell structure fiber boron nitride@titanium dioxide filler

Highly thermally conductive electrically insulating composites composed of core–shell structure fiber boron nitride@titanium dioxide filler

Determination of the heat capacity of cellulosic biosamples employing diverse machine learning approaches

Estimativa da Variação Temporal de Condutância Térmica de Contato em Placas Termicamente Finas via Método MCMC

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