Triethylphosphite as a network forming agent enhances in vitro biocompatibility and corrosion protection of hybrid organic–inorganic sol–gel coatings for Ti6Al4V alloys
Bibliographic record
Abstract
The biocompatibility and life of metallic implants can be enhanced through improving the biocompatibility and corrosion protection characteristics of the coatings used with these materials. In this study, triethylphosphite (TEP) was used to introduce phosphorus into organic-inorganic hybrid silica based sol-gel coatings prepared using γ-methacryloxypropyltrimethoxysilane and tetramethylorthosilicate. Addition of TEP dramatically increased the rate of intermolecular condensation and resulted in materials showing greater cross-linking. Protein (fibrinogen) uptake, osteoblast in vitro biocompatibility and corrosion resistance was enhanced in coatings containing TEP. Although higher concentrations of phosphorus supported the greatest improvement in biocompatibility, a compromise in the phosphorus concentration used would be required if corrosion resistance was most desirable parameter for optimisation. Films prepared by dip coating on Ti6Al4V alloys from these sols offer a promising alternative to wholly metallic prostheses.
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".