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Record W2009384963 · doi:10.1149/1.3641289

Passivation Rates for Small Particulate Aluminum in Contact with Oxide and Nitride Powders

2011· article· en· W2009384963 on OpenAlexafffund
Victor E. Padilla, John Skrovan, Zuhair M. Gasem

Bibliographic record

VenueECS Transactions · 2011
Typearticle
Languageen
FieldMaterials Science
TopicCatalytic Processes in Materials Science
Canadian institutionsUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsPassivationNitrideMaterials scienceAluminiumAluminum oxideOxideScratchMetallurgyHydrogenCorrosionLayer (electronics)Composite materialChemistry

Abstract

fetched live from OpenAlex

The self passivation of aluminum in water generally prevents the generation of hydrogen from an aluminum-water reaction in conditions preferred for portable systems. However the corrosion rate of aluminum powders is seen to greatly increase when in contact with alumina powder. This allows commercially useful amounts of hydrogen to be generated at moderate temperatures and neutral pH regions. Scratch tests were run on aluminum disks covered with oxide and nitride powders to look at repassivation rates after the surface film was disturbed and a decrease in the repassivation time observed. Small pellets of aluminum powder mixed with oxide or nitride powders were also studied with scratch events showing far lower current perturbation than seen for pure aluminum.

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 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 score0.082
Threshold uncertainty score0.415

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)0.0000.000

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 head0.030
GPT teacher head0.251
Teacher spread0.221 · 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

Citations0
Published2011
Admission routes2
Has abstractyes

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