Synthesis of Pure Hydroxyapatite and the Effect of Synthesis Conditions on its Yield, Crystallinity, Morphology and Mean Particle Size
Bibliographic record
Abstract
Hydroxyapatite (HAP) is a calcium phosphate compound with the chemical formula Ca5(PO4)3OH. This compound is especially significant in biomedical applications since it resembles the mineral constituents of the hard tissue in the human body. Its biocompatibility, castability, and sinterability make it a very attractive material for simulating bones and therefore for implantations. The objective of this study was to produce HAP with a high purity and to determine quantitatively the exact percentage of HAP in the synthesized powder. Hydrothermal methods have been used to produce HAP. In the present work, Hydroxyapatite powder was produced using the chemical precipitation method in a batch and semi‐batch modes of operation. The effect of temperature, pH, and reactant addition rates on the mean particle size was studied. Results showed a maximum in the mean particle size at pH 9, while a minimum was observed at around 45°C. As the reactant addition rate increased the mean particle size increased as well. The purity of the obtained powder was characterized using both quantitative and qualitative techniques. The quantitative results were performed using the powerful Rietveld refinement method. The quantitative results were obtained for three samples. Results showed that pure HAP was produced at a temperature of 85°C, pH 9 and reactant addition rate of 1.3 mL/min.
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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 | 0.001 | 0.001 |
| 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".