Computational framework for discovery of degradation mechanisms of organic flow battery electrolytes

The stability of organic redox-active molecules is a key challenge for the long-term viability of organic redox flow batteries (ORFBs). Electrolyte degradation leads to capacity fade, reducing the efficiency and lifespan of ORFBs. To systematically investigate degradation mechanisms, we present a computational framework that automates the exploration of degradation pathways. The approach integrates local reactivity descriptors to generate reactive complexes and employs a single-ended process search to discover elementary reaction steps, including transition states and intermediates. The resulting reaction network is iteratively refined with heuristics and human-guided validation. The framework is applied to study the degradation mechanisms of quinone- and quinoxaline-based electrolytes under acidic and basic aqueous conditions. The predicted reaction pathways and degradation products align with experimental observations, highlighting key degradation modes such as Michael addition, disproportionation, dimerization, and electrochemical transformation. The framework provides a valuable tool for <i>in silico</i> screening of stable electrolyte candidates and guiding the molecular design of next-generation ORFBs.

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Publication Details

Journal
Chemical Science
Published
2025-01-01
DOI
https://doi.org/10.1039/d4sc07640k
Citations
3
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
2.05

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article

Computational framework for discovery of degradation mechanisms of organic flow battery electrolytes

Piotr de Silva, Xiaotong Zhang
3 citations
Chemical Science
Advanced Battery Technologies Research
2.05
article

Computational framework for discovery of degradation mechanisms of organic flow battery electrolytes

Piotr de Silva, Xiaotong Zhang
article en
3 citations

Abstract

The stability of organic redox-active molecules is a key challenge for the long-term viability of organic redox flow batteries (ORFBs). Electrolyte degradation leads to capacity fade, reducing the efficiency and lifespan of ORFBs. To systematically investigate degradation mechanisms, we present a computational framework that automates the exploration of degradation pathways. The approach integrates local reactivity descriptors to generate reactive complexes and employs a single-ended process search to discover elementary reaction steps, including transition states and intermediates. The resulting reaction network is iteratively refined with heuristics and human-guided validation. The framework is applied to study the degradation mechanisms of quinone- and quinoxaline-based electrolytes under acidic and basic aqueous conditions. The predicted reaction pathways and degradation products align with experimental observations, highlighting key degradation modes such as Michael addition, disproportionation, dimerization, and electrochemical transformation. The framework provides a valuable tool for <i>in silico</i> screening of stable electrolyte candidates and guiding the molecular design of next-generation ORFBs.

Chemical ScienceVol. 16(19)
Technical University of Denmark (DK)
European Commission
Openalex Percentile: Top 14%
Advanced Battery Technologies Research
2.05
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Computational framework for discovery of degradation mechanisms of organic flow battery electrolytes — Piotr de Silva, Xiaotong Zhang · Chemical Science (2025) | TGRS Research Map | TGRS