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Record W2060660524 · doi:10.1149/1.2408970

Nickel Cathode Passivation in Alkaline Water Electrolysis

2007· article· en· W2060660524 on OpenAlex
Donald W. Kirk, Steven J. Thorpe

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

VenueECS Transactions · 2007
Typearticle
Languageen
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNickelElectrolysisCathodeAlkaline water electrolysisElectrolyteElectrodeMaterials sciencePassivationAlkaline batteryInorganic chemistryMetallurgyChemistryNanotechnologyLayer (electronics)

Abstract

fetched live from OpenAlex

During water electrolysis in alkaline electrolytes, nickel cathodes deactivate over time. The presence of soluble iron species in the alkaline electrolyte mitigates the deactivation. Congruently, iron deposits are observed on the Ni electrodes. The role of the iron deposits in preventing deactivation is explored in this work. Nickel deactivation has been proposed to be due to the formation of a surface Ni hydride phase. A complete coating of metallic iron is known to prevent nickel electrode deactivation. In industrial electrolysis, however, there is never complete coverage of the Ni electrode by iron deposition. In this work, we focused on determining the extent of iron surface coverage required to prevent nickel deactivation. A metallic grid placed over the nickel electrodes during iron vacuum sputtering was used to achieve iron coverages ranging from 20 to 100%.

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 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 score0.183
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

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

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 head0.226
Teacher spread0.218 · 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