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Record W2762646262 · doi:10.1021/acsami.7b10750

Rapid Diffusion and Nanosegregation of Hydrogen in Magnesium Alloys from Exposure to Water

2017· article· en· W2762646262 on OpenAlexaff
Michael P. Brady, Anton V. Ievlev, Mostafa Fayek, Donovan N. Leonard, Matthew G. Frith, Harry M. Meyer, Anibal J. Ramirez‐Cuesta, Luke L. Daemen, Yongqiang Cheng, Wei Guo, Jonathan D. Poplawsky, Olga S. Ovchinnikova, Jeffrey K Thomson, Lawrence M. Anovitz, Gernot Rother, Dongwon Shin, Guang‐Ling Song, Bruce Davis

Bibliographic record

VenueACS Applied Materials & Interfaces · 2017
Typearticle
Languageen
FieldMaterials Science
TopicMagnesium Alloys: Properties and Applications
Canadian institutionsUniversity of Manitoba
FundersOak Ridge National LaboratoryVehicle Technologies Program
KeywordsMaterials scienceMagnesiumDiffusionHydrogenMetallurgyThermodynamics

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide Hydrogen gas is formed when Mg corrodes in water; however, the manner and extent to which the hydrogen may also enter the Mg metal is poorly understood. Such knowledge is critical as stress corrosion cracking (SCC)/embrittlement phenomena limit many otherwise promising structural and functional uses of Mg. Here, we report via D 2 O/D isotopic tracer and H 2 O exposures with characterization by secondary ion mass spectrometry, inelastic neutron scattering vibrational spectrometry, electron microscopy, and atom probe tomography techniques direct evidence that hydrogen rapidly penetrated tens of micrometers into Mg metal after only 4 h of exposure to water at room temperature. Further, technologically important microalloying additions of <1 wt % Zr and Nd used to improve the manufacturability and mechanical properties of Mg significantly increased the extent of hydrogen ingress, whereas Al additions in the 2–3 wt % range did not. Segregation of hydrogen species was observed at regions of high Mg/Zr/Nd nanoprecipitate density and at Mg(Zr) metastable solid solution microstructural features. We also report evidence that this ingressed hydrogen was unexpectedly present in the alloy as nanoconfined, molecular H 2 . These new insights provide a basis for strategies to design Mg alloys to resist SCC in aqueous environments as well as potentially impact functional uses such as hydrogen storage where increased hydrogen uptake is desired.

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 categoriesInsufficient payload (model declined to judge)
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 score1.000

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 science0.0010.001
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 head0.015
GPT teacher head0.228
Teacher spread0.213 · 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

Citations18
Published2017
Admission routes1
Has abstractyes

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Same venueACS Applied Materials & InterfacesSame topicMagnesium Alloys: Properties and ApplicationsFrench-language works237,207