Abstracts of the 2nd International Electronic Conference on Metals
Bibliographic record
Abstract
Metastable molybdenum (Mo)-based titanium alloys exhibit a low Young's modulus, along with excellent biocompatibility, corrosion resistance, and mechanical properties, making them ideal for biomedical applications.The microstructure of Ti-Mo alloys can be tailored through thermomechanical processing, where Mo diffusion significantly influences microstructural evolution.To investigate the deformation mechanisms of a Ti-18Mo alloy, hot compression tests were performed using a Gleeble ® 3800 in both the α+βand β-phase regions at temperatures ranging from 610 • C to 910 • C and strain rates between 0.01 s -1 and 10 s -1 , reaching final strains of 0.50 and 0.80, followed by an immediate water quench.Scanning electron microscopy images and electron backscatter diffraction measurements were used to examine the microstructure of the deformed samples in the α+βand β-phase regions, respectively.In the β-phase region, the flow curves exhibit a broad work hardening, uncommon in various β-Ti alloys, representing a slowing of dynamic restoration processes, likely due to the influence of Mo on the softening kinetics.Flow curves from α+β-phase deformation show a softening after the peak value, attributed to the globularisation of the α phase.Heterogeneous microstructures were observed during deformation in both regions, indicating that the subgrain formation and α phase globularisation primarily occurred near the previous grain boundaries.Dynamic recovery, dynamic recrystallisation, subgrain size, and α phase globularisation were quantified and correlated with deformation parameters and the influence of Mo. Gas Tungsten Arc Welding of As-Cast AlCoCrFeNi2.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.181 | 0.071 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".