Antibacterial properties of synthesized Ag and Ag@SiO<sub>2</sub> core–shell nanoparticles: a comparative study
Bibliographic record
Abstract
Spherical bare silver nanoparticles (AgNPs) and silica-coated silver nanoparticles (Ag@SiO2) have been prepared using the one-step chemical reduction method. The optical, structural, and morphological studies were done by UV–visible absorption spectroscopy, X-ray diffraction (XRD), and transmission electron microscopy (TEM). The antibacterial effects of AgNP and Ag@SiO2 were further compared based on diameter of zone of inhibition and minimum inhibitory concentration (MIC) test against B. subtilis AST5–2, S. aureus ATCC 25923, S. marcescens AL2–16, and K. pneumoniae AWD5. Enhanced antibacterial activities were observed for Ag@SiO2 core–shell nanoparticles as compared to AgNPs against all tested bacteria. The results were attributed to the prolonged release of Ag (I) through porous silica shell that inhibits the growth of tested bacteria and also infers the possibility to be used in potential antibacterial applications.
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".