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Updated: Jan 18, 2026

Bulk and Thin Film Synthesis of Compositionally Variant Entropy-stabilized Oxides
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通过人工智能或机器学习识别幸存的关键特征和设计高化碳的相关机制

Dong Zhang1, Dongyang Li1

  • 1Department of Chemical and Material Engineering, University of Alberta, Edmonton, Alberta T6G 2H5, Canada.

Journal of chemical information and modeling
|September 12, 2025
PubMed
概括

机器学习有助于通过识别预测弹性模块的关键特征来发现高碳化物 (HEC). 功能选择最大限度地减少干扰,提高了先进HEC开发的预测准确度.

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