Carbon Aerogel Based Thin Electrodes for Zero‐Gap all Vanadium Redox Flow Batteries – Quantifying the Factors Leading to Optimum Performance
Bibliographic record
Abstract
Abstract Direct growth of resorcinol−formaldehyde carbon aerogels (CAGs) on carbon paper electrodes was achieved using a new approach. Materials with variations in density, mesoporosity and microporosity were prepared. Microstructural properties of the resultant thin electrodes are shown to directly influence performance in zero‐gap redox flow battery (RFB). BET analysis shows a total surface area between 643 to 931 m2 g−1. Deposition of only ≈15 wt.% CAG on the carbon electrode leads to a 320‐fold increase in electrochemical surface area. Analysis of the results saw a strong positive correlation of RFB performance with surface area. The best performing electrodes had a good balance between microporous and external surface area, and on the macroscopic scale had sufficiently large pores to allow efficient electrolyte permeation. The poorest performing electrodes which had the highest surface area, also had poor macroscopic porosity leading to large mass transport and solution resistance losses. The best performing electrodes were tested in a zero‐gap setup using polarization curves, showing a 25 % increase in power density at 100 mA cm−2 and a peak power density of 706 mW cm−2 at 1 V using thin electrodes.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".