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Record W4392459833 · doi:10.3390/coatings14030314

Effect of Temperature, Vacuum Condition and Surface Roughness on Oxygen Boost Diffusion of Ti–6Al–4V Alloy

2024· article· en· W4392459833 on OpenAlex

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.

Bibliographic record

VenueCoatings · 2024
Typearticle
Languageen
FieldMaterials Science
TopicTitanium Alloys Microstructure and Properties
Canadian institutionsMcGill University
Fundersnot available
KeywordsAlloyMaterials scienceSurface roughnessDiffusionSurface finishOxygenMetallurgyTitanium alloyComposite materialThermodynamicsChemistryPhysics

Abstract

fetched live from OpenAlex

Oxygen boost diffusion (OBD) is an effective technology for improving the surface hardness of titanium and its alloys. In this present paper, the effect of temperature, vacuum condition and surface roughness on oxygen boost diffusion of Ti–6Al–4V alloy are studied. Test results show that OBD processing can be achieved at a low temperature and over long times, as well as at a high temperature and over short times. By comparing processing efficiency and mechanical properties, high temperatures and short times are preferred for OBD treatment. The influence of vacuum conditions on oxygen vacuum diffusion is significant. Under low vacuum degree conditions, relatively high oxygen content not only corrodes the OBD layer but also leads to spalling of the outmost surface of the OBD layer and the remaining oxide layer. High surface roughness can induce cracking not only in the oxide layer during the oxidation process but also in the outmost surface of the OBD layer during the vacuum diffusion process.

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 score0.002
Threshold uncertainty score0.414

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 head0.006
GPT teacher head0.240
Teacher spread0.234 · 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