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A Fast Forward Prediction Framework for Energy Materials Design Based on Machine Learning Methods

Xinhua Liu Kaiyi Yang Lisheng Zhang Wentao Wang Sida Zhou Billy Wu Mengyu Xiong Shichun Yang Rui Tan

能源材料前沿（英文）2026，Vol.2026Issue(1)：41-59,19.

能源材料前沿（英文）2026，Vol.2026Issue(1)：41-59,19.DOI:10.34133/energymatadv.0131

A Fast Forward Prediction Framework for Energy Materials Design Based on Machine Learning Methods

Xinhua Liu ¹Kaiyi Yang ¹Lisheng Zhang ¹Wentao Wang ¹Sida Zhou ¹Billy Wu ²Mengyu Xiong ¹Shichun Yang ¹Rui Tan³

作者信息

1. School of Transportation Science and Engineering,Beihang University,Beijing 102206,China
2. Dyson School of Design Engineering,Imperial College London,London SW7 2AZ,UK
3. Energy Innovation Centre,Warwick Manufacturing Group,University of Warwick,Coventry CV5 7AL,UK||Department of Chemical Engineering,Swansea University,Swansea SA1 8EN,UK
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摘要

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Xinhua Liu,Kaiyi Yang,Lisheng Zhang,Wentao Wang,Sida Zhou,Billy Wu,Mengyu Xiong,Shichun Yang,Rui Tan..A Fast Forward Prediction Framework for Energy Materials Design Based on Machine Learning Methods[J].能源材料前沿（英文）,2026,2026(1):41-59,19.

基金项目

This work was financially supported by the Defense Industrial Technology Development Program(JCKY2021-601B019). （JCKY2021-601B019）

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