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Record W2109181651 · doi:10.2298/ciceq0802069c

Evolution of fuel cells powered by H2S-containing gases

2008· article· en· W2109181651 on OpenAlex
Karl T. Chuang, Jing‐Li Luo, Alan R. Sanger

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChemical Industry and Chemical Engineering Quarterly · 2008
Typearticle
Languageen
FieldEngineering
TopicIndustrial Gas Emission Control
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of AlbertaShell Global Solutions InternationalShell
KeywordsAnodeElectrolyteCatalysisMaterials scienceChemical engineeringProcess (computing)SulfurProcess engineeringElectrochemistryPower densityFuel cellsSteam reformingOperating temperatureWaste managementPower (physics)ElectrodeChemistryComputer scienceEngineeringOrganic chemistryMetallurgyThermodynamicsElectrical engineering

Abstract

fetched live from OpenAlex

The development of the process and electrochemical materials for conversion of H2S in a fuel cell to co-generate electrical power and benign products is outlined. While the thermodynamic basis for the process was clear, it was necessary to perform extensive research into the development of materials as catalysts and electrolytes, and to determine the optimal process and operating conditions. Through the use of composite anode catalysts and compatible new protonic electrolytes that are both chemically and thermally stable in the operating environment, we have achieved good and sustainable power densities. The only products are power, elemental sulfur and steam.

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)
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 score0.016
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.008
GPT teacher head0.183
Teacher spread0.175 · 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