Essential structural and experimental descriptors for bulk and grain boundary conductivities of Li solid electrolytes.

ABSTRACT: We present a computational approach for identifying the important descriptors of the ionic conductivities of lithium solid electrolytes. Our approach discriminates the factors of both bulk and grain boundary conductivities, which have been rarely reported. The effects of the interrelated structural (e.g. grain size, phase), material (e.g. Li ratio), chemical (e.g. electronegativity, polarizability) and experimental (e.g. sintering temperature, synthesis method) properties on the bulk and grain boundary conductivities are investigated via machine learning. The data are trained using the bulk and grain boundary conductivities of Li solid conductors at room temperature. The important descriptors are elucidated by their feature importance and predictive performances, as determined by a nonline

SUBMITTER: Wu YJ 

PROVIDER: S-EPMC7594868 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature