Interfacial reactions are notoriously difficult to characterize, and robust prediction of the chemical evolution and associated functionality of the resulting surface film is one of the grand challenges of materials chemistry. The solid-electrolyte interphase (SEI), critical to Li-ion batteries (LIBs), exemplifies such a surface film, and despite decades of work, considerable controversy remains regarding the major components of the SEI as well as their formation mechanisms. Here we use a reaction network to investigate whether lithium ethylene monocarbonate (LEMC) or lithium ethylene dicarbonate (LEDC) is the major organic component of the LIB SEI. Our data-driven, automated methodology is based on a systematic generation of relevant species using a general fragmentation/recombination procedure which provides the basis for a vast thermodynamic reaction landscape, calculated with density functional theory. The shortest pathfinding algorithms are employed to explore the reaction landscape and obtain previously proposed formation mechanisms of LEMC as well as several new reaction pathways and intermediates. For example, we identify two novel LEMC formation mechanisms: one which involves LiH generation and another that involves breaking the (CH2)O-C(=O)OLi bond in LEDC. Most importantly, we find that all identified paths, which are also kinetically favorable under the explored conditions, require water as a reactant. This condition severely limits the amount of LEMC that can form, as compared with LEDC, a conclusion that has direct impact on the SEI formation in Li-ion energy storage systems. Finally, the data-driven framework presented here is generally applicable to any electrochemical system and expected to improve our understanding of surface passivation.
Xie, Xiaowei, et al. "Data-Driven Prediction of Formation Mechanisms of Lithium Ethylene Monocarbonate with an Automated Reaction Network." Journal of the American Chemical Society, vol. 143, no. 33, Aug. 2021. https://doi.org/10.1021/jacs.1c05807
Xie, Xiaowei, Clark Spotte-Smith, Evan Walter, Wen, Mingjian, Patel, Hetal D., Blau, Samuel M., & Persson, Kristin A. (2021). Data-Driven Prediction of Formation Mechanisms of Lithium Ethylene Monocarbonate with an Automated Reaction Network. Journal of the American Chemical Society, 143(33). https://doi.org/10.1021/jacs.1c05807
Xie, Xiaowei, Clark Spotte-Smith, Evan Walter, Wen, Mingjian, et al., "Data-Driven Prediction of Formation Mechanisms of Lithium Ethylene Monocarbonate with an Automated Reaction Network," Journal of the American Chemical Society 143, no. 33 (2021), https://doi.org/10.1021/jacs.1c05807
@article{osti_1825253,
author = {Xie, Xiaowei and Clark Spotte-Smith, Evan Walter and Wen, Mingjian and Patel, Hetal D. and Blau, Samuel M. and Persson, Kristin A.},
title = {Data-Driven Prediction of Formation Mechanisms of Lithium Ethylene Monocarbonate with an Automated Reaction Network},
annote = {Interfacial reactions are notoriously difficult to characterize, and robust prediction of the chemical evolution and associated functionality of the resulting surface film is one of the grand challenges of materials chemistry. The solid-electrolyte interphase (SEI), critical to Li-ion batteries (LIBs), exemplifies such a surface film, and despite decades of work, considerable controversy remains regarding the major components of the SEI as well as their formation mechanisms. Here we use a reaction network to investigate whether lithium ethylene monocarbonate (LEMC) or lithium ethylene dicarbonate (LEDC) is the major organic component of the LIB SEI. Our data-driven, automated methodology is based on a systematic generation of relevant species using a general fragmentation/recombination procedure which provides the basis for a vast thermodynamic reaction landscape, calculated with density functional theory. The shortest pathfinding algorithms are employed to explore the reaction landscape and obtain previously proposed formation mechanisms of LEMC as well as several new reaction pathways and intermediates. For example, we identify two novel LEMC formation mechanisms: one which involves LiH generation and another that involves breaking the (CH2)O-C(=O)OLi bond in LEDC. Most importantly, we find that all identified paths, which are also kinetically favorable under the explored conditions, require water as a reactant. This condition severely limits the amount of LEMC that can form, as compared with LEDC, a conclusion that has direct impact on the SEI formation in Li-ion energy storage systems. Finally, the data-driven framework presented here is generally applicable to any electrochemical system and expected to improve our understanding of surface passivation.},
doi = {10.1021/jacs.1c05807},
url = {https://www.osti.gov/biblio/1825253},
journal = {Journal of the American Chemical Society},
issn = {ISSN 0002-7863},
number = {33},
volume = {143},
place = {United States},
publisher = {American Chemical Society (ACS)},
year = {2021},
month = {08}}
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
National Institutes of Health (NIH); USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office. Vehicle Technologies Office; USDOE Office of Science (SC), Basic Energy Sciences (BES)
Grant/Contract Number:
AC02-05CH11231
OSTI ID:
1825253
Journal Information:
Journal of the American Chemical Society, Journal Name: Journal of the American Chemical Society Journal Issue: 33 Vol. 143; ISSN 0002-7863