Enhanced Ionic Conductivity Through Crystallization of Li<sub>3</sub>PS<sub>4</sub> Glass by Machine Learning Molecular Dynamics Simulations-Reference-Cited by-同舟云学术

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Enhanced Ionic Conductivity Through Crystallization of Li₃PS₄ Glass by Machine Learning Molecular Dynamics Simulations

Published:2024-06-10 Issue:24 Volume:128 Page:10139-10145
ISSN:1932-7447
Container-title:The Journal of Physical Chemistry C
language:en
Short-container-title:J. Phys. Chem. C

Author:

Shimizu Koji¹^ORCID,Bahuguna Parth²,Mori Shigeo³,Hayashi Akitoshi⁴^ORCID,Watanabe Satoshi¹^ORCID

Affiliation:

1. Department of Materials Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan

2. Department of Physics, Indian Institute of Technology Roorkee, Roorkee 247667, India

3. Department of Material Science, Osaka Metropolitan University, 1-1 Gakuen-cho, Naka-ku, Sakai, Osaka 599-8531, Japan

4. Department of Applied Chemistry, Osaka Metropolitan University, 1-1 Gakuen-cho, Naka-ku, Sakai, Osaka 599-8531, Japan

Funder

Japan Society for the Promotion of Science

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jpcc.4c01076

Reference40 articles.

1. A lithium superionic conductor

2. High-power all-solid-state batteries using sulfide superionic conductors

3. Inducing High Ionic Conductivity in the Lithium Superionic Argyrodites Li6+xP1–xGexS5I for All-Solid-State Batteries

4. Preparation of Li2S-P2S5 Amorphous Solid Electrolytes by Mechanical Milling

5. Structural and electronic features of binary Li2S-P2S5 glasses

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