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Updated: Jan 17, 2026

Rapid in-silico Battery Electrolyte Electrochemical Reaction Generation using 3T-VASP Multi-Scale Energy Minimization
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在MXenes中加速格子导热计算:一种机器学习的力场方法

Thanasee Thanasarnsurapong1, Sourav Kanti Jana1, Panyalak Detrattanawichai2

  • 1Department of Physics, Faculty of Science, Kasetsart University, Bangkok 10900, Thailand.

ACS materials Au
|September 15, 2025
PubMed
概括

机器学习力场 (MLFF) 显著加快了Ti2C和Ti3C2 MXenes的晶格导热率预测. 表面功能化降低了导热率,证明了MLFF.

关键词:
第一个原则是计算计算.网格热导电性 网格热导电性机器学习的力量场是机器学习的力量场.基于的MXenes.两个维的材料是二维材料.

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