Atom substitution of the solid-state electrolyte Li_(10)GeP_(2)S_(12)for stabilized all-solid-state lithium metal batteries  

作　　者：Zijing Wan Xiaozhen Chen Ziqi Zhou Xiaoliang Zhong Xiaobing Luo Dongwei Xu 

机构地区：[1]State Key Laboratory of Coal Combustion,School of Energy and Power Engineering,Huazhong University of Science and Technology,Wuhan 430074,Hubei,China

出　　处：《Journal of Energy Chemistry》2024年第1期28-38,I0002,共12页能源化学（英文版）

基　　金：support from the National Natural Science Foundation of China (No.51806072)。

摘　　要：Solid-state electrolyte Li_(10)GeP_(2)S_(12)(LGPS)has a high lithium ion conductivity of 12 mS cm^(-1)at room temperature,but its inferior chemical stability against lithium metal anode impedes its practical application.Among all solutions,Ge atom substitution of the solid-state electrolyte LGPS stands out as the most promising solution to this interface problem.A systematic screening framework for Ge atom substitution including ionic conductivity,thermodynamic stability,electronic and mechanical properties is utilized to solve it.For fast screening,an enhanced model Dop Net FC using chemical formulas for the dataset is adopted to predict ionic conductivity.Finally,Li_(10)SrP_(2)S_(12)(LSrPS)is screened out,which has high lithium ion conductivity(12.58 mS cm^(-1)).In addition,an enhanced migration of lithium ion across the LSr PS/Li interface is found.Meanwhile,compared to the LGPS/Li interface,LSrPS/Li interface exhibits a larger Schottky barrier(0.134 eV),smaller electron transfer region(3.103?),and enhanced ability to block additional electrons,all of which contribute to the stabilized interface.The applied theoretical atom substitution screening framework with the aid of machine learning can be extended to rapid determination of modified specific material schemes.

关 键 词：Atom substitution Solid-state electrolyte Machine learning Stabilized interface 

分 类 号：TQ131.11[化学工程—无机化工] TM912[电气工程—电力电子与电力传动]