Machine learning-driven molecular dynamics decodes thermal tuning in graphene foam composites

Machine learning-driven molecular dynamics decodes thermal tuning in graphene foam composites

Abstract Graphene foam (GF), synthesized via Chemical Vapor Deposition (CVD), has been proven to be the ideal bulk porous material. The addition of poly(dimethylsiloxane) (PDMS) within the porous structure enables enhancement of mechanical strength and alteration of heat transfer behavior. This stud...

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Bibliographic Details
Main Authors: Pingyang Zhang, Shaodong Zhang, Yihan Qin, Tingting Du, Lei Wei, Xiangyu Li
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:npj Computational Materials
Online Access:https://doi.org/10.1038/s41524-025-01710-6
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