Silica-Based and Borate-Based, Titania-Containing Bioactive Coatings Characterization: Critical Strain Energy Release Rate, Residual Stresses, Hardness, and Thermal Expansion
Bibliographic record
Abstract
Silica-based and borate-based glass series, with increasing amounts of TiO2 incorporated, are characterized in terms of their mechanical properties relevant to their use as metallic coating materials. It is observed that borate-based glasses exhibit CTE (Coefficient of Thermal Expansion) closer to the substrate’s (Ti6Al4V) CTE, translating into higher mode I critical strain energy release rates of glasses and compressive residual stresses and strains at the coating/substrate interface, outperforming the silica-based glasses counterparts. An increase in the content of TiO2 in the glasses results in an increase in the mode I critical strain energy release rate for both the bulk glass and for the coating/substrate system, proving that the addition of TiO2 to the glass structure enhances its toughness, while decreasing its bulk hardness. Borate-based glass BRT3, with 15 mol % TiO2 incorporated, exhibits superior properties overall compared to the other proposed glasses in this work, as well as 45S5 Bioglass® and Pyrex.
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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 | 0.000 | 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) | 0.001 | 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 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".