Work

Numerical investigation of heat transfer in 2D particulate composites: effects of filler concentration and geometric disorder

Year: 2026

Type: article

Abstract: Predicting the effective thermal conductivity of particulate composites is challenging due to the interplay between filler concentration, geometric disorder, and property contrast. This study utilizes a parametric stochastic framework and a perturbed lattice algorithm to investigate 2D microstructures with controlled spatial perturbation ( s ) and size polydispersity ( dr ). Steady-state heat conduction is solved via finite element analysis, while ensemble averaging ensures statistical reliability. Results reveal that conductivity enhancement saturates at a volume fraction of ϕ ≈ 0.11 without a percolation threshold. Notably, mean conductivity exhibits a non-monotonic dependence on spatial disorder, peaking at s ≈ 0.4, which also corresponds to maximum statistical variability. At high phase contrast, properties converge to the lower Hashin-Shtrikman bound, confirming that performance is governed by matrix-phase constrictions rather than intrinsic filler conductivity. These findings demonstrate that matrix morphology imposes a fundamental limit on heat transport in isolated dispersions, suggesting that significant enhancement requires engineered percolating networks.

Source: International Journal of Thermofluids

DOI: 10.1016/j.ijft.2026.101718

Authors: Alexander Pysarenko, Artem Chystiakov

Institutions: Odessa State Academy of Civil Engineering and Architecture, Slovak University of Technology in Bratislava, Slovak Academy of Sciences, Linnaeus University, Institute of Construction and Architecture of the Slovak Academy of Sciences

Language: English

Topic: Thermal properties of materials

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,520

OpenAlex ID: W7223314975

FWCI:

Cites: 60

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Related to: 10