Predicting Ionic Conductivity in Thin Films of Garnet Electrolytes Using Machine Learning

Predicting Ionic Conductivity in Thin Films of Garnet Electrolytes Using Machine Learning

All-solid-state batteries (ASSBs) are the important attributes of the forthcoming technologies for electrochemical energy storage. A key element of ASSBs is the solid electrolyte materials. Garnets are considered promising candidates for solid electrolytes of ASSBs due to their chemical stability wi...

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Bibliographic Details
Main Authors: Natalia Kireeva, Aslan Yu. Tsivadze, Vladislav S. Pervov
Format: Article
Language:English
Published: MDPI AG 2023-08-01
Series:Batteries
Subjects:
solid electrolytes
thin films
ionic conductivity
elastic characteristics
machine learning
Online Access:https://www.mdpi.com/2313-0105/9/9/430

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