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Chemical Reaction Networks Explain Gas Evolution Mechanisms in Mg-Ion Batteries.


ABSTRACT: Out-of-equilibrium electrochemical reaction mechanisms are notoriously difficult to characterize. However, such reactions are critical for a range of technological applications. For instance, in metal-ion batteries, spontaneous electrolyte degradation controls electrode passivation and battery cycle life. Here, to improve our ability to elucidate electrochemical reactivity, we for the first time combine computational chemical reaction network (CRN) analysis based on density functional theory (DFT) and differential electrochemical mass spectroscopy (DEMS) to study gas evolution from a model Mg-ion battery electrolyte─magnesium bistriflimide (Mg(TFSI)2) dissolved in diglyme (G2). Automated CRN analysis allows for the facile interpretation of DEMS data, revealing H2O, C2H4, and CH3OH as major products of G2 decomposition. These findings are further explained by identifying elementary mechanisms using DFT. While TFSI- is reactive at Mg electrodes, we find that it does not meaningfully contribute to gas evolution. The combined theoretical-experimental approach developed here provides a means to effectively predict electrolyte decomposition products and pathways when initially unknown.

SUBMITTER: Spotte-Smith EWC 

PROVIDER: S-EPMC10251523 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

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Chemical Reaction Networks Explain Gas Evolution Mechanisms in Mg-Ion Batteries.

Spotte-Smith Evan Walter Clark EWC   Blau Samuel M SM   Barter Daniel D   Leon Noel J NJ   Hahn Nathan T NT   Redkar Nikita S NS   Zavadil Kevin R KR   Liao Chen C   Persson Kristin A KA  

Journal of the American Chemical Society 20230526 22


Out-of-equilibrium electrochemical reaction mechanisms are notoriously difficult to characterize. However, such reactions are critical for a range of technological applications. For instance, in metal-ion batteries, spontaneous electrolyte degradation controls electrode passivation and battery cycle life. Here, to improve our ability to elucidate electrochemical reactivity, we for the first time combine computational chemical reaction network (CRN) analysis based on density functional theory (DF  ...[more]

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