Survey and Investigation of Nanostructure Hardystonite/Biphasic Calcium Phosphate to Use in Biomedical Engineering
Bibliographic record
Abstract
The development of structures serving as scaffolds to fill bone defects, and promote bone regeneration is of a particular importance in bone tissue engineering. In this study, highly porous (≈75%) nanostructured hardystonite/biphasic calcium phosphate scaffolds (BCPS) with interconnected porosity were developed using various hardystonite contents via the space holder technique. Transmission electron microscopy (TEM), X-ray diffraction (XRD) and scanning electron microscopy (SEM) techniques were employed to evaluate different samples. In addition, the role of scaffold composition on the mechanical performance, bioactivity and biodegradability was studied. The results showed that the scaffolds produced have an average pore size of 350 nm and a density between 2.2 ± 0.4 and 1.7 ± 0.2 gr/cm3, depending on the hardystonite contents. Furthermore, increasing the hardystonite content of scaffolds from 0 (control) to 30 wt. % enhanced the bioactivity test, biodegradability, and compressive strength from 1.1 ± 0.1 to 3.1 ± 0.2 MPa, respectively. Our project suggests that nanostructured hardystonite/BCPS with improved biological and mechanical properties could potentially be used for biomedical engineering such as bone tissue engineering application.
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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 | 0.001 | 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) | 0.000 | 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".