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Record W4408569114 · doi:10.1016/j.mtla.2025.102390

Effect of Si concentration on the liquid metal embrittlement susceptibility of advanced high strength steels

2025· article· en· W4408569114 on OpenAlex
Fateme Abdiyan, Joseph R. McDermid, A. Macwan, Bita Pourbahari, Mirnaly Saenz de Miera, Brian Langelier, Hatem S. Zurob

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMaterialia · 2025
Typearticle
Languageen
FieldEngineering
TopicMicrostructure and Mechanical Properties of Steels
Canadian institutionsArcelorMittal (Canada)McMaster University
FundersNatural Sciences and Engineering Research Council of CanadaArcelorMittal
KeywordsMaterials scienceEmbrittlementLiquid metal embrittlementMetallurgyMetalHigh strength steelLiquid metalMicrostructureGrain boundary

Abstract

fetched live from OpenAlex

Resistance spot welding (RSW) trials were performed on electrogalvanized steel sheets with 0.6 and 1.5 wt% Si. It was shown that LME cracks were longer in the 1.5Si alloy. Moreover, Atom Probe Tomography (APT) in the vicinity of the crack tips revealed (i) an accumulation of Si at the solid/liquid interface due to the low solubility of Si in the Zn-based liquid and (ii) greater Zn diffusion from the liquid into the bulk steel substrate on either side of the crack for the 0.6Si alloy. Diffusion simulations indicated that a longer time is needed for the solidification of the Zn-based liquid in the 1.5Si alloy compared with the 0.6Si alloy, further suggesting a prolonged period of contact between the aggressive Zn-based liquid and substrate grain boundaries in the case of the 1.5Si alloy.

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.

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 score0.003
Threshold uncertainty score0.377

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 head0.004
GPT teacher head0.216
Teacher spread0.211 · 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