@samblau.bsky.social, Brett Savoie (Notre Dame), and I are organizing a symposium for @amerchemsociety.bsky.social Fall 2025 called "Chemical Reaction Networks, Retrosynthesis, and Reaction Prediction" under @acscomp.bsky.social. #reactionnetwork #CRN #retrosynthesis 🧪 ⚗️ #CompChem
Sam Blau (@samblau.bsky.social)

Research scientist & computational chemist at Berkeley Lab using HT DFT workflows, machine learning, and reaction networks to model complex reactivity.

Bluesky Social

New preprint on ChemRxiv! In "Chemical Reaction Networks Explain Gas Evolution Mechanisms in Mg-Ion Batteries", I teamed up with experimentalists at Argonne and Sandia National Labs to explain gassing behavior in next-generation Mg-ion batteries. Combining reaction network analysis with online electrochemical mass spec, we identify H2O, CH3OH, and C2H4 as major evolved gases and explain how these gases form!

https://doi.org/10.26434/chemrxiv-2023-tntkg

@chemistry @compchem #reactionnetwork

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

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 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 its decomposition does not meaningfully contribute to gas evolution. The combined theoretical-experimental approach developed here provides a means to elucidate electrolyte reactivity, improving our ability to predict decomposition products and pathways when initially unknown.

ChemRxiv

If folks want the Springer Nature SharedIt link, DM me, and I'm happy to share that as well.

Thanks so much to my co-authors, especially Mingjian, who organized us all and wrote many of the ML sections, and Sam Blau, who included me on the manuscript in the first place and made so many of our pretty figures!

#chemistry #compchem #paper #reactionnetwork #machinelearning #ml #crn #reactivity #network @chemistry @compchem