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Record W2141032275 · doi:10.1149/04523.0109ecst

Low Cost Hydrogen Fuel Cell

2013· article· en· W2141032275 on OpenAlexafffund
Mohammad S. Dara, Alfred Lam, Khalid Fatih, David P. Wilkinson

Bibliographic record

VenueECS Transactions · 2013
Typearticle
Languageen
FieldEngineering
TopicFuel Cells and Related Materials
Canadian institutionsUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsElectrolyteProton exchange membrane fuel cellHydrogenDirect-ethanol fuel cellFuel cellsCathodeChemistryHydrogen fuelCatalysisPower densityInorganic chemistryChemical engineeringElectrodeOrganic chemistryPower (physics)

Abstract

fetched live from OpenAlex

In this paper a hydrogen fuel cell is operated in the absence of a membrane at 60°C. The fuel cell was fed a non-humidified hydrogen fuel and a 2 M Fe(ClO 4 ) 3 , 0.22M Fe(ClO 4 ) 2 , and 0.2 M HClO 4 oxidant catholyte. A 3-D carbon cathode in conjunction with a 0.5 M HClO 4 liquid electrolyte was used to eliminate the membrane. Non-optimized maximum power density upwards of 220 mW/cm² was achieved with a total Pt content of the fuel cell as low as 0.05 mg/cm². Elimination of the PEM and reduction in total fuel cell Pt-catalyst content are expected to offer significant cost savings over conventional fuel cell technology.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.725
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.003

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 head0.005
GPT teacher head0.167
Teacher spread0.162 · 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; both teacher heads agree on what is shown here.

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

Citations2
Published2013
Admission routes2
Has abstractyes

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