Biogenic Sulfur-Based Chalcogenide Nanocrystals: Methods of Fabrication, Mechanistic Aspects, and Bio-Applications
Bibliographic record
Abstract
Bio-nanotechnology has emerged as an efficient and competitive methodology for the production of added-value nanomaterials (NMs). This review article gathers knowledge gleaned from the literature regarding the biosynthesis of sulfur-based chalcogenide nanoparticles (S-NPs), such as CdS, ZnS and PbS NPs, using various biological resources, namely bacteria, fungi including yeast, algae, plant extracts, single biomolecules, and viruses. In addition, this work sheds light onto the hypothetical mechanistic aspects, and discusses the impact of varying the experimental parameters, such as the employed bio-entity, time, pH, and biomass concentration, on the obtained S-NPs and, consequently, on their properties. Furthermore, various bio-applications of these NMs are described. Finally, key elements regarding the whole process are summed up and some hints are provided to overcome encountered bottlenecks towards the improved and scalable production of biogenic S-NPs.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".