Vision for energy material design:A roadmap for integrated data-driven modeling

被引：8

作者：

Zhilong Wang ^{[1
]}

Yanqiang Han ^{[1
]}

Junfei Cai ^{[1
]}

An Chen ^{[1
]}

Jinjin Li ^{[1
]}

机构：

[1] Key Laboratory of Thin Film and Microfabrication of Ministry of Education, Department of Micro/Nano Electronics, Shanghai Jiao Tong University

来源：

Journal of Energy Chemistry | 2022年 / 71卷 / 08期

基金：

国家重点研发计划; 中国国家自然科学基金;

关键词：

D O I：

暂无

中图分类号：

TB30 [工程材料一般性问题]; TP181 [自动推理、机器学习];

学科分类号：

摘要：

The application scope and future development directions of machine learning models(supervised learning, transfer learning, and unsupervised learning) that have driven energy material design are discussed.

引用

页码：56 / 62 +7

页数：8

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