Phase-Selective Electroprecipitation of Calcium Phosphate Thin Films at Physiological Temperatures
Bibliographic record
Abstract
A protein-compatible combination of temperature and pH conditions allows for phase-selective electrosynthesis of bonelike calcium phosphate materials. The procedure involves an acidic aqueous electrolyte at 20−40 °C for an electroprecipation reaction based on nitrate reduction. X-ray diffraction and Raman spectroscopic data confirm that hydroxyapatite (Ca 10 (PO 4 ) 6 (OH) 2 ) is the kinetically preferred phase under galvanostatic electroprecipitation conditions with lower phosphate concentrations (∼0.03 M) in the electrolyte, whereas brushite (CaHPO 4 ·2H 2 O) is favored when electrolytes with higher phosphate concentrations are used. Titration data suggest that the origin of this concentration-dependent phase selectivity is related to differences in buffering capacity of the electrolytes in the immediate vicinity of the working electrode surface, which explains the variability in phases in previous reports of calcium phosphate electrosynthesis. Critical parameters for controlling film formation are galvanostatic control of the electroprecipitation (for local pH changes that trigger deposition), phosphate concentration (to regulate buffering effects), and the presence of ammonia and ammonium ions in the bulk electrolyte (for complexing to improve film coverage and uniformity).
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".