Status and prospects for symmetric organic redox flow batteries
Bibliographic record
Abstract
This comprehensive review classifies the various bipolar organic active materials that have been studied in symmetric redox flow batteries, emphasizing current challenegs and prospects for this emerging field. As environmental concerns from fossil fuel consumption intensify, large-scale energy storage becomes imperative for the integration of renewable sources like wind, hydro, and solar with the electrical grid. Redox flow batteries, particularly those employing organic molecules, are positioned as a key technology for this purpose. This review explores the growing field of symmetric organic redox flow batteries (ORFBs) within this context. Unlike traditional asymmetric designs based on unique active materials for each electrode, symmetric ORFBs involve a single bipolar species for both electrodes. This review highlights the benefits of a symmetric design, and categorizes five distinct classes of organic bipolar molecules used in both aqueous and non-aqueous solvents. By providing a comprehensive overview of their cell cycling and performance characteristics, the strengths and weaknesses of the diverse categories of bipolar molecules are highlighted for both solvent systems, as are opportunities for future development. This should guide new research directions and advance the development of practical symmetric ORFBs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".