在液温度以上的酸超导材料来自机器学习的机器学习

Yuxue Wang1,2,3, Tianhao Su1,2,3, Yaning Cui1,2,3

  • 1Department of Physics, Material Genome Institute, Institute for the Conservation of Cultural Heritage, Shanghai University Shanghai 200444 China renwei@shu.edu.cn shunbohu@shu.edu.cn.

RSC advances
|July 5, 2023
PubMed
概括

机器学习模型将酸盐识别为高温超导的有希望的候选者. 共价键的长度和孔剂度是影响临界温度的关键因素,指导着未来的材料发现.

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