Investigating the addition of SiO <sub>2</sub> –CaO–ZnO–Na <sub>2</sub> O–TiO <sub>2</sub> bioactive glass to hydroxyapatite: Characterization, mechanical properties and bioactivity
Bibliographic record
Abstract
Hydroxyapatite (Ca10(PO4)6(OH)2) is widely investigated as an implantable material for hard tissue restoration due to its osteoconductive properties. However, hydroxyapatite in bulk form is limited as its mechanical properties are insufficient for load-bearing orthopedic applications. Attempts have been made to improve the mechanical properties of hydroxyapatite, by incorporating ceramic fillers, but the resultant composite materials require high sintering temperatures to facilitate densification, leading to the decomposition of hydroxyapatite into tricalcium phosphate, tetra-calcium phosphate and CaO phases. One method of improving the properties of hydroxyapatite is to incorporate bioactive glass particles as a second phase. These typically have lower softening points which could possibly facilitate sintering at lower temperatures. In this work, a bioactive glass (SiO2-CaO-ZnO-Na2O-TiO2) is incorporated (10, 20 and 30 wt%) into hydroxyapatite as a reinforcing phase. X-ray diffraction confirmed that no additional phases (other than hydroxyapatite) were formed at a sintering temperature of 560 ℃ with up to 30 wt% glass addition. The addition of the glass phase increased the % crystallinity and the relative density of the composites. The biaxial flexural strength increased to 36 MPa with glass addition, and there was no significant change in hardness as a function of maturation. The pH of the incubation media increased to pH 10 or 11 through glass addition, and ion release profiles determined that Si, Na and P were released from the composites. Calcium phosphate precipitation was encouraged in simulated body fluid with the incorporation of the bioactive glass phase, and cell culture testing in MC-3T3 osteoblasts determined that the composite materials did not significantly reduce cell viability.
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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".