Calcium Phosphate Coatings Produced by Solution Precursor Plasma Spray
Bibliographic record
Abstract
Abstract Calcium phosphate (Ca-P) coatings have been used as surface coatings on porous metallic implants in dentistry and orthopaedics for the last twenty years. These Ca-P coatings, nominally hydroxyapatite (HA), have been shown to promote bone fixation and osteconductivity on Ti and Ti alloy substrates used for those purposes. Such coatings can be formed by different methods including plasma spray. In addition to the well known advantages of the plasma spray technique to deposit coatings, a new version of this technique, i.e. solution precursor plasma spray (SPPS), has been reported to produce submicron/nanocrystalline structured coatings. Nanocrystalline HA coatings may improve the resorption of the coating in the body, avoiding the irritant effect of large particles which may be seen in current thermal sprayed HA coatings. The main purpose of this work was to study the suitability of a sol-gel Ca-P solution precursor (calcium nitrate tetrahydrate and ammonium dihydrogen phosphate) as feedstock for the air plasma spray (APS) coating technique. We report on the formation and the characteristics of the coatings so formed on Ti6Al4V substrates. The presence of different Ca-P crystalline and amorphous phases was assessed by X-ray diffraction analysis. The X-ray photoelectron spectroscopy technique was used to characterize the surface chemical composition of the Ca-P coatings. The microstructural features of the coatings were characterized by scanning/transmission electron microscopy combined with image analysis in order to evidence the presence of submicron/nanocrystalline Ca-P features. Final results are discussed in terms of the spraying parameters. Abstract only; no full-text paper available.
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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".