Tackling structural complexity in li2s-p2s5 solid-state electrolytes using machine learning potentials

HIGHLIGHTS

• who: Carsten G. Staacke et al. from the Fritz-Haber-Institut der Max-Planck-Gesellschaft, Faradayweg, Berlin, Germany have published the article: Tackling Structural Complexity in Li2S-P2S5 Solid-State Electrolytes Using Machine Learning Potentials, in the Journal: Nanomaterials 2022, 12, 2950. of /2022/
• what: To overcome the length and time scale restrictions of ab initio calculations to industrially applicable LPS materials the authors develop a near-universal machine-learning interatomic potential for the LPS material class. In the first part of this work the authors present the data -efficient training protocol and evaluate the . . .
  

   

  

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