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Record W2032049332 · doi:10.1149/2.006301jes

Pathways for Hydrogen Absorption into Zircaloy-2 under Cathodic Polarization Assessed by Scanning Electrochemical Microscopy, Scanning Electron Microscopy, and Electrochemical Impedance Spectroscopy

2012· article· en· W2032049332 on OpenAlexaff
Catherine Nowierski, James J. Noël, David W. Shoesmith, Zhifeng Ding

Bibliographic record

VenueJournal of The Electrochemical Society · 2012
Typearticle
Languageen
FieldChemistry
TopicElectrochemical Analysis and Applications
Canadian institutionsWestern University
Fundersnot available
KeywordsScanning electrochemical microscopyDielectric spectroscopyScanning electron microscopeAnalytical Chemistry (journal)Materials sciencePolarization (electrochemistry)ChemistryGrain boundaryElectrochemistryElectrodeMicrostructureMetallurgyComposite materialPhysical chemistry

Abstract

fetched live from OpenAlex

Hydrogen absorption by Zircaloy-2 has been studied in neutral sodium sulfate solutions using steady-state polarization measurements, electrochemical impedance spectroscopy (EIS), and scanning electrochemical microscopy (SECM). For applied potentials < −1 V (vs. saturated calomel electrode, SCE), water reduction occurs in faults in the passive oxide covering the alloy. For potentials ≤−1.3 VSCE, SECM detects a distribution of reactive locations on the electrode surface. Matched SECM and SEM images of the same electrode surface show more reactive sites to be located in the β-phase grain boundaries than on the α-grains. The reactivity of surface locations was determined using SECM probe approach curves. Secondary phase particles incorporating impurities such as Fe, Ni, and Cr as Zr(Fe, Cr)2 and Zr2(Fe, Ni) are particularly reactive spots, which may act as "windows" for hydrogen absorption into the alloy. This claim is supported by the observation that the surface of the α-grains remains passive even at potentials as low as −2.0 VSCE. The need to include a Warburg impedance element in modeling EIS recorded at potentials ≥−1.3 VSCE suggests that H2O reduction is confined to tight flaws in the oxide at grain boundary locations.

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 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 score0.103
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.273
Teacher spread0.265 · 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.

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

Citations5
Published2012
Admission routes1
Has abstractyes

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