Predictive stochastic analysis of massive filter-based electrochemical reaction networks

Abstract

Chemical reaction networks (CRNs) are powerful tools for obtaining insight into complex reactive processes. However, they are difficult to employ in domains such as electrochemistry where reaction mechanisms and outcomes...

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

“…While implicit solvation methods such as SMD are suitable for solution-phase calculations involving neutral and charged organic species, they severely underestimate the stabilizing effect of solvent on metal ions. 34 To correct the (free) energies of species with undercoordinated Mg ions in our reaction network, we estimated the effect of each coordinate bond on the Mg 2+ and Mg 1+ ions. We optimized Mg 2+ (G 2 ) n and Mg 1+ (G 2 ) n clusters using DFT in Q-Chem, with n ∈ {0, 1, 2}.…”

“…As in our previous study, 34 when calculating reaction free energies for oxidation or reduction reactions, we used an uncorrected free energy. This is especially important for reduction reactions involving Mg due to the different preferred coordination environments of Mg 2+ and Mg 1+ .…”

“…We used the High-Performance Reaction Generation (HiPRGen) method 34 to automatically construct CRNs from an initial set of species and their properties. HiPRGen is designed for cases where potential energy surface (PES) exploration techniques (stochastic surface walking, 48 AIMD, etc.)…”

“…HiPRGen has previously been used to construct and analyze CRNs relevant to electrolyte degradation and SEI formation in LIBs. 34,49 Instead of using PES exploration or templates, HiPRGen constructs CRNs using extensible filters. For this work, the following types of species were excluded:…”

“…[31][32][33] In order to explain and interpret OEMS data in MIBs, we computationally construct and analyze a chemical reaction network (CRN) describing electrolyte decomposition and SEI formation at the Mg plating potential. Using a recently developed method, 34 we automatically identify potential CRN products, as well as reaction pathways to form those products. With this information, we are able to positively identify the gases formed as byproducts of electrolyte decomposition.…”