Atomistic modeling of bulk and grain boundary diffusion in solid electrolyte Li6PS5Cl using machine-learning interatomic potentials

被引：0
|
作者：
Ou, Yongliang [1 ]
Ikeda, Yuji [1 ]
Scholz, Lena [2 ]
Divinski, Sergiy [3 ]
Fritzen, Felix [2 ]
Grabowski, Blazej [1 ]
机构：
[1] Institute for Materials Science, University of Stuttgart, Pfaffenwaldring 55, Stuttgart,70569, Germany
[2] Institute of Applied Mechanics, University of Stuttgart, Universitätsstraße 32, Stuttgart,70569, Germany
[3] Institute of Materials Physics, University of Münster, Wilhelm-Klemm-Straße 10, Münster,48149, Germany
来源：
Physical Review Materials | 2024年 / 8卷 / 11期
关键词：
This project is funded by the Deutsche Forschungsgemeinschaft (DFG; German Research Foundation)-EXC 2075-390740016 under Germany's Excellence Strategy (Y.O. and L.S.); IK 125/1-1-519607530 (Y.I.); DI 1419/18-1-429191048 (S.D.); FR 2702/10-517847245 (F.F.); INST 40/575-1-405998092 FUGG (JUSTUS 2 cluster). B.G. is funded by the European Research Council (ERC) under the European Union's Horizon 2020 Research and Innovation Program (Grant Agreement No. 865855). The authors acknowledge the support by the Stuttgart Center for Simulation Science (SimTech) and the state of Baden-Wu00FCrttemberg through bwHPC;
D O I：
10.1103/PhysRevMaterials.8.115407
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