MétaCan
Menu
Back to cohort
Record W2045384529 · doi:10.1155/2014/485045

Propane Fuel Cells: Selectivity for Partial or Complete Reaction

2014· article· en· W2045384529 on OpenAlexaff
Shadi Vafaeyan, Alain St‐Amant, Marten Ternan

Bibliographic record

VenueJournal of Fuels · 2014
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsDehydrogenationPropaneChemistryCatalysisElectrolyteInorganic chemistryDesorptionAdsorptionPartial oxidationProton exchange membrane fuel cellOrganic chemistryPhysical chemistryElectrode

Abstract

fetched live from OpenAlex

The use of propane fuel in high temperature (120°C) polymer electrolyte membrane (PEM) fuel cells that do not require a platinum group metal catalyst is being investigated in our laboratory. Density functional theory (DFT) was used to determine propane adsorption energies, desorption energies, and transition state energies for both dehydrogenation and hydroxylation reactions on a Ni(100) anode catalyst surface. The Boltzmann factor for the hydroxylation of a propyl species to form propanol and its subsequent desorption was compared to that for the dehydrogenation of a propyl species. The large ratio of the respective Boltzmann factors indicated that the formation of a completely reacted product (carbon dioxide) is much more likely than the formation of partially reacted products (alcohols, aldehydes, carboxylic acids, and carbon monoxide). That finding is evidence for the major proportion of the chemical energy of the propane fuel being converted to either electrical or thermal energy in the fuel cell rather than remaining unused when partially reacted species are formed.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.415
Threshold uncertainty score0.442

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.023
GPT teacher head0.250
Teacher spread0.227 · 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 teacher head, 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

Citations3
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueJournal of FuelsSame topicElectrocatalysts for Energy ConversionFrench-language works237,207