In Situ Synthesis of a Hydroxyapatite and Reduced Graphene Oxide Composite for Potential Electrochemical Biosensing Applications
Bibliographic record
Abstract
Hydroxyapatite/reduced graphene oxide (HA/rGO) composites are extensively used in numerous applications, including tissue engineering, energy storage, catalysis, and electrochemical sensing. In this study, a novel microwave hydrothermal-assisted coprecipitation method was implemented to synthesize an in situ HA/rGO composite for potential electrochemical biosensing applications. The structural, optical, and morphological properties were thoroughly analyzed using XRD, Raman spectroscopy, FTIR, STXM, and SEM. Rietveld refinement confirmed the presence of a hexagonal crystalline phase in the HA/rGO composite with a mean crystallite size of 28.1 nm. Raman spectroscopy revealed characteristic vibrational modes of each precursor, while STXM spectra displayed electronic transitions corresponding to rGO (C 1s to π* and σ* levels) as well as Ca L-edge and O and P K-edge transitions of HA, confirming a composite material. FTIR analysis confirmed the reduction of GO to rGO by tracking the presence and disappearance of oxygen-functional groups in the graphitic structure. Electron microscopy revealed that HA nanorods, averaging 75 nm in length, were uniformly distributed along the surface and edges of the rGO layers.
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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".