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Record W3163775190 · doi:10.53063/synsint.2021.1114

Influence of molybdenum content on the microstructure of spark plasma sintered titanium alloys

2021· article· en· W3163775190 on OpenAlexvenueno aff
S. Rashia Begum, M. Vasumathi, Chinh Chien Nguyen, Quyet Van Le

Bibliographic record

VenueSynthesis and Sintering · 2021
Typearticle
Languageen
FieldMaterials Science
TopicTitanium Alloys Microstructure and Properties
Canadian institutionsnot available
Fundersnot available
KeywordsMolybdenumSpark plasma sinteringMaterials scienceMicrostructureRelative densityTitaniumMetallurgyBrittlenessPhase (matter)SinteringChemistry

Abstract

fetched live from OpenAlex

Five titanium-based alloys containing 4, 8, 12, 16, and 20 wt% molybdenum additive were fabricated by spark plasma sintering process at 1200 ˚C. The samples were scrutinized in terms of relative density, phase evolution, and microstructural development. The relative density reached 99.9% with the molybdenum addition up to 16 wt% but slightly dropped in the sample with 20 wt% additive. In the specimens with 4 wt% Mo, molybdenum solved completely in the matrix and three different phase morphologies were observed, namely continuous α-Ti, laminar α-Ti, and very thin laminar β-Ti. With increasing Mo content to 20 wt%, widespread single β-Ti appeared alongside remained Mo and α-Ti. Ductile fracture mode was dominant in the samples with low Mo contents whilst it changed to brittle in the specimens with higher content of molybdenum.

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 score0.001
Threshold uncertainty score0.003

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 head0.024
GPT teacher head0.210
Teacher spread0.185 · 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

Citations26
Published2021
Admission routes1
Has abstractyes

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