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Record W2522834534 · doi:10.5006/c2015-05985

Hydrogen Permeability of Ion Vapor Deposited (IVD) and Electroplated Al Coatings by Electrochemical Permeation Cell Technique

2015· article· en· W2522834534 on OpenAlexaff
P. Behera, K. R. Sriraman, L. Lee, S. Brahimi, Richard R. Chromik, S. Yue

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen embrittlement and corrosion behaviors in metals
Canadian institutionsMcGill University
Fundersnot available
KeywordsElectroplatingPermeationMaterials sciencePermeability (electromagnetism)ElectrochemistryHydrogenIonCorrosionChemical engineeringMetallurgyComposite materialChemistryMembraneElectrodeEngineering

Abstract

fetched live from OpenAlex

Abstract Ion vapor deposited (IVD) and electroplated Al coatings are potential replacements for electroplated low hydrogen embrittlement (LHE) Cd coatings on high strength steel substrates due to their sacrificial protection. As compared to LHE Cd coating, which needs a post baking process to remove hydrogen, both IVD and electroplated Al coatings do not introduce any hydrogen during plating process. But in corroding environments, it is possible that evolved hydrogen may diffuse through the coating into substrate and cause hydrogen damage. In this work the electrochemical permeation cell technique is used to study the effective diffusivity of hydrogen for IVD and electroplated Al coating using an LHE Cd coating as a base line. The effective diffusivities obtained from galvanostatic charging were modelled using the classical diffusion equation to obtain hydrogen permeation flux. The effective diffusivities of hydrogen in Al coated steel are further utilized to understand hydrogen embrittlement susceptibility by mechanical property measurements on Al coated, aerospace high strength steels and components.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.011
GPT teacher head0.246
Teacher spread0.235 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2015
Admission routes1
Has abstractyes

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