Performance Model of a Regenerative Hydrogen Bromine Fuel Cell for Grid-Scale Energy Storage
Bibliographic record
Abstract
We develop a performance model for a polymer electrolyte membrane based regenerative hydrogen-bromine fuel cell (rHBFC). The model includes four voltage loss mechanisms: ohmic loss through the membrane, hydrogen electrode activation, bromine electrode activation, and bromine electrode mass transport. We explore a large parameter space by looking at the dependences of each of these losses as a function of two “operating parameters”, acid concentration and temperature; and five “engineering parameters”, bromine electrode exchange current density, hydrogen electrode exchange current density, membrane thickness, diffusion layer thickness, and hydrogen gas pressure. The relative importance of each of the losses is explored as both the engineering parameters and operating parameters are varied. The model is also compared to published experimental results on the performance of a hydrogen-bromine cell. By varying engineering parameters and operating parameters within plausible ranges, we project that, with further research, a cell of this design could be developed that operates at greater than 90% voltage efficiency at current densities 700 mA cm-2 in both electrolytic and galvanic modes and that has a peak galvanic power density of 2760 mW cm-2.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".