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Unlocking enhanced thermal conductivity in polymer blends through active learning

Engineering and Technology

Unlocking enhanced thermal conductivity in polymer blends through active learning

J. Xu and T. Luo

Discover how Jiaxin Xu and Tengfei Luo leveraged high-throughput molecular dynamics simulations and active learning to unveil polymer blends with remarkable thermal conductivity. Their groundbreaking research analyzed the interplay of various factors, paving the way for innovative materials with superior performance.

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Playback language: English
Abstract
This study uses high-throughput molecular dynamics (MD) simulations and active learning (AL) to identify polymer blends with enhanced thermal conductivity (TC). MD simulations determined the TC of single-component polymers and blends. An AL framework efficiently explored the TC of 550,000 polymer blends, accelerating the discovery of high-performance blends. The relationship between TC, radius of gyration (Rg), and hydrogen bonding was analyzed, revealing the importance of inter- and intra-chain interactions.
Publisher
npj Computational Materials
Published On
Apr 10, 2024
Authors
Jiaxin Xu, Tengfei Luo
Tags
thermal conductivity
polymer blends
molecular dynamics
active learning
inter-chain interactions
hydrogen bonding
single-component polymers

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