Heat conduction model based on percolation theory for thermal conductivity of composites with high volume fraction of filler in base matrix

Chatterjee, Aritra; Verma, Ravi; Umashankar, H.P.; Kasthurirengan, S.; Shivaprakash, N. C.; Behera, Upendra

doi:10.1016/j.ijthermalsci.2018.09.015

Cited by 23 publications

(8 citation statements)

References 23 publications

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“…The most popular theory among them is the thermal conductive path theory, where the addition of fillers to an extent will form a thermal conductive network that facilitates thermal conductivity improvement [ 5 ]. Heat transfer paths are formed when the fillers are added beyond a certain volume fraction, and this phenomenon is known as percolation, whereby a sudden increment in the composite thermal conductivity is observed [ 46 ]. The thermoelastic coefficient theory is based on the heat conduction due to the phonons, with the thermal conductivity of the composites depending on the efficiency of phonon transfer.…”

Section: Composite Systemsmentioning

confidence: 99%

A Review of Multiple Scale Fibrous and Composite Systems for Heating Applications

et al. 2021

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Different types of heating systems have been developed lately, representing a growing interest in both the academic and industrial sectors. Based on the Joule effect, fibrous structures can produce heat once an electrical current is passed, whereby different approaches have been followed. For that purpose, materials with electrical and thermal conductivity have been explored, such as carbon-based nanomaterials, metallic nanostructures, intrinsically conducting polymers, fibers or hybrids. We review the usage of these emerging nanomaterials at the nanoscale and processed up to the macroscale to create heaters. In addition to fibrous systems, the creation of composite systems for electrical and thermal conductivity enhancement has also been highly studied. Different techniques can be used to create thin film heaters or heating textiles, as opposed to the conventional textile technologies. The combination of nanoscale and microscale materials gives the best heating performances, and some applications have already been proven, even though some effort is still needed to reach the industry level.

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Section: Composite Systemsmentioning

confidence: 99%

A Review of Multiple Scale Fibrous and Composite Systems for Heating Applications

et al. 2021

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“…It was found that when the ratio of inclusion-matrix to inclusion-inclusion Kapitza resistance increases then the relative thermal resistance reduces through the percolation network compared to the unpercolated regions of the domain, which in turn leads to an increase in the ETC of a composite. Recently, Chatterjee et al [33] proposed a computational heat conduction model based on percolation theory for thermal 5 1 conductivity of composites with a high volume fraction of filler in the matrix. They considered 2 cubical particle percolation effect to compute the ETC of the composite.…”

Section: Etcmentioning

confidence: 99%

“…Recently, Chatterjee et al. 33 proposed a computational heat conduction model based on percolation theory for thermal conductivity of composites with a high volume fraction of filler in the matrix. They considered cubical particle percolation effect to compute the ETC of the composite.…”

Section: Introductionmentioning

confidence: 99%

Analytical and numerical assessment of the effect of highly conductive inclusions distribution on the thermal conductivity of particulate composites

Khan

Hajeri

Khan

2019

Journal of Composite Materials

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Highly conductive composites have found applications in thermal management, and the effective thermal conductivity plays a vital role in understanding the thermo-mechanical behavior of advanced composites. Experimental studies show that when highly conductive inclusions embedded in a polymeric matrix the particle forms conductive chain that drastically increase the effective thermal conductivity of two-phase particulate composites. In this study, we introduce a random network three dimensional (3D) percolation model which closely represent the experimentally observed scenario of the formation of the conductive chain by spherical particles. The prediction of the effective thermal conductivity obtained from percolation models is compared with the conventional micromechanical models of particulate composites having the cubical arrangement, the hexagonal arrangement and the random distribution of the spheres. In addition to that, the capabilities of predicting the effective thermal conductivity of a composite by different analytical models, micromechanical models, and, numerical models are also discussed and compared with the experimental data available in the literature. The results showed that random network percolation models give reasonable estimates of the effective thermal conductivity of the highly conductive particulate composites only in some cases. It is found that the developed percolation models perfectly represent the case of conduction through a composite containing randomly suspended interacting spheres and yield effective thermal conductivity results close to Jeffery's model. It is concluded that a more refined random network percolation model with the directional conductive chain of spheres should be developed to predict the effective thermal conductivity of advanced composites containing highly conductive inclusions.

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“…Classically, the upscaling process can be related to percolation theory [10], which describes connectivity of objects within for example, a porous structure. We can also determine effects of this connectivity on macroscale properties such as thermal conductivity [11]. In particular, the fundamental contributions of Torquato who proposed strategies via rigorous microstructure-property relations [1,12].…”

Section: Introductionmentioning

confidence: 99%

Thermal conductivity model function of porosity: review and fitting using experimental data

Preux

Malinouskaya

2021

Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles

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Heat conduction model based on percolation theory for thermal conductivity of composites with high volume fraction of filler in base matrix

Cited by 23 publications

References 23 publications

A Review of Multiple Scale Fibrous and Composite Systems for Heating Applications

A Review of Multiple Scale Fibrous and Composite Systems for Heating Applications

Analytical and numerical assessment of the effect of highly conductive inclusions distribution on the thermal conductivity of particulate composites

Thermal conductivity model function of porosity: review and fitting using experimental data

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