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Record W4410885324 · doi:10.1117/12.3053867

Study of metal electrodes in a single-cell hydrogen peroxide fuel cell

2025· article· en· W4410885324 on OpenAlexaff
Raveen Appuhamy, Faraz Alderson, S. Andrew Gadsden

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsMcMaster University
Fundersnot available
KeywordsHydrogen peroxideFuel cellsElectrodeMaterials scienceMetalHydrogenChemical engineeringChemistryMetallurgyEngineeringPhysical chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Hydrogen peroxide is a promising alternative to Hydrogen gas as a fuel cell fuel. As hydrogen peroxide can act as both the oxidizing and reducing agent, it reduces the complexity of the cell. The cell can be contained as a single compartment where both the anode and cathode reactions occur. It follows a similar chemical reaction to hydrogen fuel cells, where water is created. The benefit of hydrogen peroxide is that it can be stored more easily and in safer conditions. Evaluating the efficiency of hydrogen peroxide fuel cells is important to justify their validity as a fuel cell alternative. For this study, tantalum and poly(copper phthalocyanine) were tested in a single-compartment fuel cell configuration. The electrodes are tested in an acidic electrolyte solution. To evaluate the cell performances, custom electrodes were made for metals that were not already available and then tested. It was found that the electrode combination of tantalum metal and poly(copper phthalocyanine) carbon cloth electrodes in an acidic electrolyte solution had an output potential of 620 mV. From here, the cell should be scaled to a stack to test its effectiveness further.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.007
GPT teacher head0.195
Teacher spread0.187 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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