Development of Multifunctional Materials Based on Poly(ether ether ketone) with Improved Biological Performances for Dental Applications
Bibliographic record
Abstract
The main target for the future of materials in dentistry aims to develop dental implants that will have optimal integration with the surrounding tissues, while preventing or avoiding bacterial infections. In this project, poly(ether ether ketone) (PEEK), known for its suitable biocompa-tibility and mechanical properties for dental applications, was loaded with 1, 3, and 5 wt.% ZnO nanoparticles to provide antibacterial properties and improve interaction with cells. Sample cha-racterization by X-ray diffraction (XRD), thermogravimetric analysis (TGA), and differential scanning calorimetry (DSC) as well as mechanical properties showed the presence of the nanoparticles and their effect in PEEK matrices, preserving their relevant properties for dental applications. Al-though, the incorporation of ZnO nanoparticles did not improve the mechanical properties and a slight decrease in the thermal stability of the materials was observed. Hemocompatibility and osteoblasts-like cell viability tests showed improved biological performances when ZnO was present, demonstrating high potential for dental implant applications.
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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 | 0.000 | 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".