Investigating the Fracture Resistance of Bioactive Glass Coatings on Metallic Implants
Bibliographic record
Abstract
Bioactive glasses have been used experimentally as coatings for medical implants because of their good osseointegration properties and ability to inhibit bacterial proliferation. However, the available literature lacks quantitative studies for characterizing their mechanical properties. This research postulates two fracture mechanics testing methodologies that facilitate measuring the nearly pure mode I (opening) and mode II (shearing) critical strain energy release rate (GIC, GIIC) of the coating/substrate system. Using these methodologies, the effects of coating thickness, glass composition and degradation on the GIC and GIIC of the system were evaluated. The developed mode I testing methodology was applied on a silicate bioactive glass/Ti6Al4V substrate system and it was found that increasing the coating thickness from 90 to 390 μm, decreased the measured GIC of the system significantly, from 6.2 to 2.5 J/m2. This decrease was found to be due to the increase in the residual stresses in the thicker coatings. The mode I testing methodology was then applied on two series of silica-based and borate-based glass coating, with increasing amounts of TiO2 incorporated, and it was observed that an increase in the content of TiO2 in the glasses resulted in an increase in the GIC for both the bulk glass and for the coating/substrate system. The borate-based series was found to have a closer CTE to the substrate compared to the silica counterpart, suggesting that use of such glasses as coatings can minimize the chances of delamination and cracking. Incorporating SrCO3 in a series of borate bioactive glass coating also proved to significantly increase the GIC and GIIC of the system. In order to study the effect of degradation, the borate bioactive glass coatings on Ti6Al4V substrates were immersed in deionized water for different time periods, dried and tested. It was found that after 17% weight loss of the glass, the GIC and GIIC of the coating/substrate system for all compositions decreased by at least 80%.
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 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 | 0.000 | 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".