Understanding the sluggish and highly variable transport kinetics of lithium ions in LiFePO_4

作     者：Youcheng Hu Xiaoxiao Wang Peng Li Junxiang Chen Shengli Chen 

作者机构：Hubei Electrochemical Power Sources Key LaboratoryDepartment of ChemistryWuhan UniversityWuhan 430072China CAS Key Laboratory of Design and Assembly of Functional NanostructuresFujian Institute of Research on the Structure of MatterChinese Academy of SciencesFuzhou 350002China 

出 版 物：《Science China Chemistry》 (中国科学(化学英文版))

年 卷 期：2023年第66卷第11期

页      面：3297-3306页

核心收录：

学科分类：081702[工学-化学工艺] 0808[工学-电气工程] 08[工学] 0817[工学-化学工程与技术] 0714[理学-统计学（可授理学、经济学学位）] 0701[理学-数学] 0702[理学-物理学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：financially supported by the National Natural Science Foundation of China(22272122 21832004 and 21673163)。 

主　　题：lithium iron phosphate diffusion coefficient machine-learning potential kinetic Monte Carlo simulations 

摘      要：LiFePO_(4),one of the mainstream cathode materials of current EV batteries,exhibits experimental diffusion coefficients(D_(c))of Li^(+)which are not only several orders of magnitude lower than those predicted by the ionic hopping barriers obtained from theoretical calculations and spectroscopic measurements,but also span several orders from 10^(-14)to 10^(-18)cm^(2)s^(-1)under different states of charge(SOC)and the charging rates(C-rates).Atomic level understanding of such sluggishness and diversity of Li^(+)transport kinetics would be of significance in improving the rate performance of LiFePO_(4)through material and operation optimization but remain challenging.Herein,we show that the high sensitivity of Li^(+)hopping barriers on the local Li–Li coordination environments(numbers and configurations)plays a key role in the ion transport kinetics.This is due a neural network-based deep potential(DP)which allows accurate and efficient calculation of hopping barriers of Li^(+)in LiFePO_(4)with various Li–Li coordination environments,with which the kinetic Monte-Carlo(KMC)method was employed to determine the D_(c)values at various C-rates and SOC across a broad spectrum.Especially,an accelerated KMC simulation strategy is proposed to obtain the D_(c)values under a wide range of SOC at low C-rates,which agree well with that obtained from the galvanostatic intermittent titration technique(GITT).The present study provides accurate descriptions of Li^(+)transport kinetics at both very high and low C-rates,which remains challenging to experiments and first-principles calculations,respectively.Finally,it is revealed that the gradient distributions of Li^(+)density along the diffusion path result in great asymmetry in the barriers of the forward and backward hopping,causing very slow diffusion of Li^(+)and the diverse variation of D_(c).