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A computational approach to characterize formation of a passivation layer in lithium metal anodes
Author(s) -
Sitapure Niranjan,
Lee Hyeonggeon,
OspinaAcevedo Francisco,
Balbuena Perla B.,
Hwang Sungwon,
Kwon Joseph SangII
Publication year - 2021
Publication title -
aiche journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.958
H-Index - 167
eISSN - 1547-5905
pISSN - 0001-1541
DOI - 10.1002/aic.17073
Subject(s) - dendrite (mathematics) , electrolyte , anode , kinetic monte carlo , passivation , interphase , lithium (medication) , materials science , lithium metal , chemical physics , electrochemistry , molecular dynamics , monte carlo method , chemistry , nanotechnology , chemical engineering , layer (electronics) , electrode , computational chemistry , engineering , medicine , endocrinology , statistics , geometry , mathematics , biology , genetics
Li metal anode is the “Holy Grail” material of advanced Lithium‐ion‐batteries (LIBs). However, it is plagued by uncontrollable dendrite growth resulting in poor cycling efficiency and short‐circuiting of batteries. This has spurred a plethora of research to understand the underlying mechanism of dendrite formation. While experimental studies suggest that there are complex physical and chemical interactions between heterogeneous solid‐electrolyte interphase (SEI) and dendrite growth, most of the studies do not reveal the mechanisms triggering these interactions. To deal with this knowledge gap, we propose a multiscale modeling framework which couples kinetic Monte Carlo and Molecular Dynamics simulations. Specifically, the model has been developed to account for (a) heterogeneous SEI, (b) dendrite‐SEI interactions, and (c) effect of electrolyte on Li electrodeposition and potential dendrite formation. This allows the proposed computational model to be extended to various electrolytes and SEI species and generate results consistent with previous experimental studies.