Nanostructured Hybrid of Immiscible Gold and Silicon and Its Effect on Proliferation and Adhesion of Fibroblasts and Osteoblasts
Bibliographic record
Abstract
Hybrid biomaterials are a combination of two or more different materials that work synergistically to produce superior properties. Nano structuring of such hybrid materials has also posed complications. In this study, we present, for the first time a nanofibrous hybrid of gold and silicon fabricated by femtosecond laser synthesis for tissue engineering applications. The formation of a completely new phase, Au3Si (212) is reported. The formation mechanism is explained by vapor condensation. Particle sizes of 2-10 nm and 37-49 nm for gold and gold concentrations of 35-78% are achieved. The effect of this hybrid on cell growth was assessed using fibroblasts and osteoblasts. There was a significant decrease in both osteoblast and fibroblast proliferation with the increase of gold in the hybrid nanostructure. This novel hybrid nanofibrous matrix provides a method to effectively control the proliferation and adhesion of cells. Femtosecond laser synthesis presents a new standard by which not only a single element biomaterial but also multiple immiscible element hybrid biomaterials can be fabricated. This technique provides a paradigm shift in the fabrication of novel nanostructured immiscible hybrid biomaterials.
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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) | 0.000 | 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".