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Record W2892369411 · doi:10.1071/ch18328

Progress Towards Direct Hydrogen Peroxide Fuel Cells (DHPFCs) as an Energy Storage Concept*

2018· article· en· W2892369411 on OpenAlex
Ciaran McDonnell‐Worth, Douglas R. MacFarlane

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAustralian Journal of Chemistry · 2018
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsnot available
FundersQueen's UniversityMonash UniversityAustralian Academy of ScienceQueen's University Belfast
KeywordsElectrochemical energy conversionFuel cellsHydrogen peroxideHydrogen fuelRenewable energyChemical energyEnergy storageRegenerative fuel cellElectrochemistryWind powerProcess engineeringChemistryPower to gasWaste managementSolar fuelEnvironmental scienceChemical engineeringCatalysisPower (physics)EngineeringElectrodeElectrical engineeringElectrolyteOrganic chemistry

Abstract

fetched live from OpenAlex

This review introduces the concept of direct H2O2 fuel cells and discusses the merits of these systems in comparison with other ‘clean-energy’ fuels. Through electrochemical methods, H2O2 fuel can be generated from environmentally benign energy sources such as wind and solar. It also produces only water and oxygen when it is utilised in a direct H2O2 fuel cell, making it a fully reversible system. The electrochemical methods for H2O2 production are discussed here as well as the recent research aimed at increasing the efficiency and power of direct H2O2 fuel cells.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.056
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.010
GPT teacher head0.249
Teacher spread0.239 · 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