| Machine Learning towards Screening Solid-state Lithium Ion Conductors |
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| 作者姓名： | Feng Pan |
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| 作者单位： | School of Advanced Materials |
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| 基金项目： | Supported by the National Key Research and Development Program;and National Natural Science Foundation of China |
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| 摘 要： | Machine learning is an emerging method to discover new materials with specific characteristics.An unsupervised machine learning research is highlighted to discover new potential lithium ionic conductors by screening and clustering lithium compounds,providing inspirations for the development of solid-state electrolytes and practical batteries.
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| 关 键 词： | UNSUPERVISED machine learning first principles calculation solid state lithium ion CONDUCTORS ANION frameworks high IONIC CONDUCTIVITIES |
Machine Learning towards Screening Solid-state Lithium Ion Conductors |
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| Feng Pan.Machine Learning towards Screening Solid-state Lithium Ion Conductors[J].Chinese Journal of Structural Chemistry,2020,39(1):7-10. |
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| Institution: | Beijing Key Laboratory of Green Chemical Reaction Engineering and Technology,Department of Chemical Engineering, Tsinghua University, Beijing 100084, China;Beijing Key Laboratory of Green Chemical Reaction Engineering and Technology,Department of Chemical Engineering, Tsinghua University, Beijing 100084, China;Beijing Key Laboratory of Green Chemical Reaction Engineering and Technology,Department of Chemical Engineering, Tsinghua University, Beijing 100084, China;Beijing Key Laboratory of Green Chemical Reaction Engineering and Technology,Department of Chemical Engineering, Tsinghua University, Beijing 100084, China |
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| Abstract: | Machine learning is an emerging method to discover new materials with specific characteristics. An unsupervised machine learning research is highlighted to discover new potential lithium ionic conductors by screening and clustering lithium compounds, providing inspirations for the development of solid-state electrolytes and practical batteries. |
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