Mapping the frontiers of quinone stability in aqueous media: implications for organic aqueous redox flow batteries
Bibliographic record
Abstract
Quinone-hydroquinone pairs have been proposed as biologically-inspired, low-cost redox couples for organic electrolytes for electrical energy storage, particularly in aqueous redox flow batteries. In their oxidized form, quinones are electrophiles that can react with the nucleophilic water solvent resulting in loss of active electrolyte. Here we study two mechanisms of nucleophilic addition of water, one reversible and one irreversible, that limit quinone performance in practical flow batteries. Using a combination of density functional theory and semi-empirical calculations, we have quantified the source of the instability of quinones in water, and explored the relationships between chemical structure, electrochemical reduction potential, and decomposition or instability mechanisms. By combining these computational estimates with the experimental study of the aqueous stability of alizarin-derived quinones, quantitative thresholds for chemical stability of oxidized quinones were established. Finally, ∼140,000 prospective quinone pairs (over 1,000,000 calculations including decomposition products) were analyzed in a virtual screening using the learned design principles. Our conclusions suggest that numerous low reduction potential molecules are stable with respect to nucleophilic addition, but promising high reduction potential molecules are much rarer. This latter fact suggests the existence of a stability cliff for this family of quinone-based organic molecules, which challenges the development of all-quinone aqueous redox flow batteries.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".