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

07 April 2023, Version 2
This content is a preprint and has not undergone peer review at the time of posting.

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 on 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 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.

Keywords

Mg
Mg-ion
Mg-ion battery
battery
electrolyte
reaction mechanism
differential electrochemical mass spectroscopy
online electrochemical mass spectroscopy
oems
dems
gas evolution
electrolyte decomposition
computational chemistry
density functional theory
chemical reaction network
CRN
Mg(TFSI)2
diglyme
G2
autocatalysis
electrochemistry
DFT
solid electrolyte interphase
electrode passivation

Supplementary materials

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Title
Supplementary Information: Chemical Reaction Networks Explain Gas Evolution Mechanisms in Mg-Ion Batteries
Description
Schematic of experimental setup; cyclic voltammetry data; snapshot OEMS spectra; discussion of solvent corrections to free energy; discussion of predicted reduction potentials with and in the absence of explicit solvent; further description of CRN-predicted products; average stochastic trajectories obtained during CRN analysis; SEM images.
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