Impact of Sintering Duration on the Mechanical and Bioactive Properties of Pure Ti, Ti-Al Alloy, and Ti-Al-HAp Composite for Biomedical Applications
Bibliographic record
Abstract
Commercially pure titanium is widely used in biomedical applications due to its excellent biocompatibility, although its bioinert nature limits osseointegration.This study incorporated hydroxyapatite (HAp) to enhance bioactivity, and aluminum (Al) was added to improve mechanical performance.The effect of sintering time on the relative density, compressive strength, microhardness, and bioactivity of CP-Ti, Ti-6%Al, and Ti-6%Al-2%HAp composites was investigated.The samples were fabricated via powder metallurgy and sintered at 1300℃ for 60, 90, and 120 minutes.Results indicated that increasing the sintering time improved all evaluated properties.At 120 minutes, relative densities reached 91.72%, 92.78%, and 93.31%, while compressive strengths were 511 MPa, 492 MPa, and 476 MPa for CP-Ti, Ti-6%Al, and Ti-6%Al-2%HAp, respectively.Microhardness values also increased, reaching 379 HV, 351 HV, and 298 HV.XRD analysis identified the formation of bioactive phases, including TiP₂O₇, TiO₂, Al₂Ti, Na₂Ti₃O₇, CaTi₄P₆O₂₄, and CaTiO₃.The MTT assay confirmed low cytotoxicity (13.3%) in three days.AAS results showed minimal Ti (0.912 ppm) ions and no Al ions release in 14 days.These findings highlight the significant role of sintering time in enhancing the mechanical and bioactive performance of Ti-based composites for biomedical 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".