Characterization of thin oxide layers formed by Ti-Nb alloy anodization
Bibliographic record
Abstract
Ti-Nb alloys are gaining more prominence in the industrial and scientific environment due to their high biocompatibility, mechanical strength/weight ratio, and exceptional corrosion resistance compared to other metallic materials. Metals exhibiting this passivation characteristic are known as metal valves and may exhibit semiconductive or insulating oxides. Controlling the growth of distinct thickness layer films is possible through tunning anodization conditions. In this work, a Ti-Nb binary system is anodized, and the grown oxide layer is comprehensively characterized using ellipsometry based on its optical properties and thickness at different applied potentials. Confocal Microscopy assessed their surface roughness, and SEM/EDS probed the surface material's elemental composition. CF-LIBS successfully confirmed the 70/30 composition of the Ti-Nb alloy. Raman spectra have detected the presence of amorphous TiO 2 and Nb 2 O 5 at potentials 80 V, 100 V, and 120 V. Finally, a linear dependence of the oxide thickness with the applied potential was observed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".