Controlled microstructural evolution of Hydroxyapatite–Bioglass® nanocomposites via two-step sintering
Bibliographic record
Abstract
Hydroxyapatite (HA)-Bioglass® (45S) nanocomposites were fabricated via two-step sintering (TSS) to optimize densification, phase stability, and mechanical performance for potential bone regeneration applications. Composite nanopowders were prepared by a sol-gel route, compacted into pellets, and subjected to a TSS protocol with systematically varied temperatures and holding times. The selected two-step sintering (TSS2) parameters were identified as an initial temperature of 1150 °C with a 15 min hold, followed by a seconday treatment at 1050 °C for 25 h, which yielded the best balance of densification and phase stability. X-ray diffraction and scanning electron microscopy revealed that HA remained the primary phase, while β-tricalcium phosphate (β-TCP) formation increased with Bioglass® content, enhancing fracture toughness via crack-bridging and transformation-induced local compressive stresses. Bulk density and nanoindentation measurements showed that Bioglass® acted as an effective sintering aid, promoting densification and improving hardness, elastic modulus, and toughness. Among the studied compositions, the 10 wt% Bioglass® composite processed under selected TSS2 conditions exhibited the highest density and superior mechanical properties, while maintaining nanoscale grains (<100 nm). These results demonstrate that controlled TSS can effectively tailor the microstructure and performance of HA- Bioglass® composites, offering a promising strategy for advanced bioceramic implants.
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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) | 0.000 | 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".