Reduced Flow Battery Capacity Fade from Mixed Redox-Active Organics Beyond the Rule of Mixtures
Bibliographic record
Abstract
Aqueous organic redox flow batteries offer a sustainable approach to long-duration energy storage but suffer from molecular degradation. Here, we present a mixed redox-active strategy that stabilizes 2,6-dihydroxyanthraquinone (DHAQ) by enabling in situ regeneration of redox-active species under standard operating conditions. By incorporating 0.1 M of 4,4′-((9,10-anthraquinone-2,6-diyl)dioxy)dibutyrate (DBEAQ) into a 0.1 M DHAQ electrolyte, the fade rate is reduced from 4.7% to 0.9% per day, a 62% decrease relative to the 2.35%/day expected from a noninteracting mixture. Increasing DBEAQ concentration to 0.2 M further lowers fade to 0.43% per day, representing a 73% reduction relative to the expected value of 1.57%. Electrochemical and NMR data show that regeneration occurs via chemical oxidation of anthrone to a dimer, followed by electrochemical reoxidation to DHAQ. This approach is not limited to DBEAQ, suggesting broad applicability to other anthraquinones. The underlying regeneration mechanism offers a general framework for improving electrolyte stability in organic 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".