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Microstructure and first hydrogenation properties of Ti30V60M10 + 4 wt% Zr (M=Fe, Co, and Ni)

2025· article· en· W4409283965 on OpenAlexafffund
Chourouk Kefi, Jacques Huot

Bibliographic record

VenueInternational Journal of Hydrogen Energy · 2025
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen Storage and Materials
Canadian institutionsUniversité du Québec à Trois-Rivières
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMicrostructureMaterials scienceHydrogen storageMetallurgyNuclear chemistryChemical engineeringChemistryCrystallographyAlloy

Abstract

fetched live from OpenAlex

The hydrogenation properties of Ti 30 V 60 M 10 (M = Fe, Co, and Ni) + 4 wt% Zr alloys at room temperature were investigated. The alloys were tested in their as-cast state and after being heat treated at 300 °C under a dynamic vacuum for 2 h. All as-cast alloys presented a two-phase microstructure consisting of a BCC matrix and a C14 secondary bright phase rich in Zr and M atoms. The BCC structure transformed into a face-centred cubic (FCC) main phase upon hydrogenation, while the C14 phase also hydrogenate but kept its structure. The as-cast alloys showed slow hydrogen absorption initially, but heat treatment reduced incubation times and improved hydrogenation kinetics for all compositions. • Investigated hydrogenation properties of Ti 30 V 60 M 10 (M = Fe, Co, and Ni) alloys with 4 wt% Zr at room temperature. • As-Cast alloys presented a two-phase microstructure of BCC matrix and C14 bright phase. • Heat treatment at 300 °C before activation reduced incubation times and improved hydrogenation kinetics. • Hydrogenation transformed the BCC structure to FCC, while the C14 phase also hydrogenate but kept its structure. • After heat treatment, Ti 30 V 60 Ni 10 alloy showed the most significant enhancement in hydrogenation kinetics.

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 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 score0.016
Threshold uncertainty score0.468

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 science0.0000.000
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 head0.009
GPT teacher head0.238
Teacher spread0.229 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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