Sintering studies of synthesised manganese-oxide-doped calcium phosphate via wet chemical precipitation method
Bibliographic record
Abstract
The beneficial effects of incorporating small amounts of manganese oxide, MnO2 (0·05, 0·1, 0·3, 0·5 and 1·0 wt%) into biphasic calcium phosphate in promoting sintering and its effect on physical and mechanical properties of the dense sample sintered at 1000–1400°C were investigated. In this work, a wet precipitation method was employed to prepare biphasic calcium phosphate powder. The starting materials of calcium hydroxide and orthophosphoric acid were used in the titration process and the as-synthesised powder was subsequently doped with manganese oxide by wet milling. The X-ray diffraction analysis revealed that the phase present in the as-synthesised powder was predominantly hydroxyapatite. However, upon sintering, all the samples revealed the existence of biphasic calcium phosphate i.e. a mix phase comprising of hydroxyapatite and tricalcium phosphate. The highest relative density of 99·5% was obtained for biphasic calcium phosphate doped with 0·3 wt% MnO2 when sintered at 1400°C. The results also revealed that 0·3 wt% MnO2-doped biphasic calcium phosphate gave a maximum Vickers hardness of 5·14 GPa. On the other hand, 1·0 wt% MnO2-doped biphasic calcium phosphate exhibited highest fracture toughness of 1·32 MPa m1/2 as compared to 0·88 MPa m1/2 for undoped biphasic calcium phosphate when sintered at 1200°C.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".