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Record W6977007362 · doi:10.60692/s3ggh-v9d52

Tracer Film Growth Study of Hydrogen and Oxygen from the Corrosion of Magnesium in Water

2014· article· en· W6977007362 on OpenAlexaff

Bibliographic record

VenueGreater South Information System · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsHydrogenOxygenCorrosionTRACERAlloySecondary ion mass spectrometryMagnesiumSputteringMetal

Abstract

fetched live from OpenAlex

An isotopic tracer study of the film growth mechanism for pure magnesium, AZ31B, and ZE10A (Elektron 717, E717) magnesium alloys in water at room temperature was performed. A series of individual and sequential exposures were conducted in both H218O and D216O, with isotopic tracer profiles obtained using secondary ion mass spectrometry (SIMS). The water-formed films consisted primarily of partially hydrated MgO. The SIMS sputter depth profiles indicate that H and D penetrated throughout the film and into the underlying metal, particularly for the Zr- and Nd-containing E717 alloy. Film growth for the UHP Mg involved aspects of both metal outward diffusion and oxygen/hydrogen inward diffusion. In contrast, the film on the Al-containing AZ31B alloy grew primarily by inward oxygen and inward hydrogen diffusion. The 18O and D profiles for the film formed on E717 were the most complex, with the 18O data most consistent with inward lattice oxygen diffusion, but the D data suggests inward, short-circuit diffusion through the film. It is speculated that preferential inward short circuit hydrogen transport may have been aided by the presence of nano Zn2Zr3 particles throughout the E717 film. Such hydrogen penetration may have implications from both a corrosion resistance and hydrogen storage perspective.

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 score0.005
Threshold uncertainty score0.010

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 head0.031
GPT teacher head0.165
Teacher spread0.135 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

Explore more

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