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RESEARCH PAPER · Chemical Engineering Science · 2025

Decoding the ZT optimization of BiCuSeO thermoelectrics via interpretable machine learning

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Decoding the ZT optimization of BiCuSeO thermoelectrics via interpretable machine learningOriginalMachine learning–driven thermoelectric materials: Review on prediction, optimization, and discovery2Synergistic Optimization of Thermoelectric Performance in AgSbTe 2 via Ag Vacancy and In Doping3Synergistic band engineering and interface regulation in carbon- and iron- doped BNNS/SWCNT composite films for enhanced thermoelectric performance0Thermoelectric hydrogels: Strategies for controlled fabrication and performance tuning0

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  1. Machine learning–driven thermoelectric materials: Review on prediction, optimization, and discovery

    Journal of Alloys and Compounds · 2025-12-20

    Xinmei Zhang, Xingxing Wang, Wei Wang, Zhipeng Yuan, Jin Zhang Peng, Jianjun Shi, Peng He, Yunfeng Chang

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  2. Synergistic Optimization of Thermoelectric Performance in AgSbTe 2 via Ag Vacancy and In Doping

    ACS Applied Energy Materials · 2026-03-21

    Di Liu, Meihua Hu, Ning Bi, Shangsheng Li, Siyu Zhang, Haobo Zhang, Zhenyang Wang

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  3. Synergistic band engineering and interface regulation in carbon- and iron- doped BNNS/SWCNT composite films for enhanced thermoelectric performance

    Chemical Engineering Science · 2026-06-20

    Aoxuan Zhang, Xiaoliang Ma, Si Chen, Yunfei Zhang, Can Jiang, Weiyi Wang, Feipeng Du

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  4. Thermoelectric hydrogels: Strategies for controlled fabrication and performance tuning

    Applied Physics Reviews · 2026-07-28

    Ran Su, Suyi Wen, Saeed Ahmed Khan, Xingpeng Li, Shengli Cao, Xiaojing Cui, Jie Zhang, Hulin Zhang

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