Rechargeable Metal–Hydrogen Peroxide Battery, A Solution to Improve the Metal–Air Battery Performance
Bibliographic record
Abstract
Rechargeable metal–air batteries are set to play an important role in electrifying the transportation sector and transitioning to a sustainable energy society with zero carbon footprint. However, their performance is vastly hampered by the sluggish kinetics of oxygen redox reactions at the air electrode. Herein, a rechargeable metal–hydrogen peroxide battery is introduced that is air-free and uses onsite generated and reduced hydrogen peroxide (H2O2) as an oxygen source for charging and discharging. Replacing oxygen redox reactions with H2O2 redox reactions results in a much faster kinetics and a significant improvement in the overall battery performance. Using computationally driven material design with a set of thermodynamic rules, highly stable, active, and selective bifunctional catalyst materials for H2O2 generation and reduction are proposed. This technology has the potential to overcome the long-standing issues with metal–air batteries paving the path for advancing the next-generation rechargeable battery technology based on H2O2 redox chemistry.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Electrochemistry study of a rechargeable metal-hydrogen peroxide battery.
The study develops a rechargeable battery technology rather than examining research.
Battery electrochemistry proposal for metal–hydrogen peroxide systems; domain energy materials.
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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".