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Record W4416904858 · doi:10.3390/hydrogen6040114

Effect of Mechanical Processing on First Hydrogenation of Gas-Atomized Ti0.488Fe0.46Mn0.052 Alloy

2025· article· en· W4416904858 on OpenAlexafffund
Seyedehfaranak Hosseinigourajoubi, Chris Schade, Jacques Huot

Bibliographic record

VenueHydrogen · 2025
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen Storage and Materials
Canadian institutionsUniversité du Québec à Trois-Rivières
FundersMitacsUniversité du Québec à Trois-Rivières
KeywordsArgonAlloyPressingHydrogenIncubationBall millBall (mathematics)

Abstract

fetched live from OpenAlex

In this paper, we report the effects of cold rolling, ball milling, and cold pressing on the first hydrogenation behavior of Ti0.488Fe0.460Mn0.052 alloy synthesized by gas atomization and exposed to the air for an extended period. It was found that cold pressing led to a higher hydrogen absorption capacity of 1.9 wt.%, while ball milling significantly improved the kinetics, achieving an incubation time of only 7 min. The cold-rolled sample (5 passes) showed a hydrogen absorption capacity similar to the ball-milled sample (1.5 wt.%) but with a slower hydrogenation rate. To further optimize the cold rolling process, the influence of the rolling atmosphere and the number of passes was systematically examined. In both air and argon, increasing the number of cold rolling passes resulted in longer incubation times. However, samples rolled under argon showed shorter incubation times compared to those rolled in the air. The difference between the two atmospheres became more pronounced after 20 rolling passes; the sample rolled in argon showed an incubation time of 55 min, whereas the sample rolled in air failed to absorb hydrogen even after 24 h.

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)0.002
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 score0.002
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.008
GPT teacher head0.266
Teacher spread0.258 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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