A pre-trained deep potential model for sulfide solid electrolytes with broad coverage and high accuracy
Abstract Solid electrolytes with fast ion transport are crucial for solid state lithium metal batteries. Chemical doping has been the most effective strategy for improving ion condictiviy, and atomistic simulation with machine-learning potentials helps optimize doping by predicting ion conductivity...
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| Main Authors: | Ruoyu Wang, Mingyu Guo, Yuxiang Gao, Xiaoxu Wang, Yuzhi Zhang, Bin Deng, Mengchao Shi, Linfeng Zhang, Zhicheng Zhong |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-08-01
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| Series: | npj Computational Materials |
| Online Access: | https://doi.org/10.1038/s41524-025-01764-6 |
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