Characterizations and analysis of the antioxidant, antimicrobial, and dye reduction ability of green synthesized silver nanoparticles
Bibliographic record
Abstract
Abstract The current study was conducted to assess the potential of ginger rhizome extract ( Zingiber officinale ) for the synthesis of silver nanoparticles (AgNPs) through the green method and its mitigating activity against pathogenic bacterial strains. AgNPs were synthesized through a simple one-step approach and characterized by UV-Visible (UV-Vis) spectroscopy, powder X-ray diffraction (PXRD), transmission electronic microscopy (TEM), and energy dispersive X-rays spectroscopy (EDS). PXRD and TEM results of AgNPs showed the face central cubic structures and predominantly spherical structures with a size of 6.5 nm. EDS analysis confirms the elemental silver in nanoparticles. Moreover, the impact of the pH, as well as temperature, during the synthesis of AgNPs has also been investigated. At 25°C and pH 5, there was no significant peak for AgNPs in the absorption spectra. However, with an increase in temperature from 25°C to 85°C and pH 5 to pH 11, particles started attaining the spherical shape of different sizes due to an increase in the reduction rate. The AgNPs displayed effective results against selected pathogenic strains, Pseudomonas aeruginosa (MTCC 424), Methicillin-resistant Staphylococcus aureus (ATCC 43300), and fungus Candida albicans (KACC 30003). The prepared AgNPs exhibited excellent antioxidant activity and catalytic reduction of methyl orange with the pseudo-first-order rate constant of 3.9 × 10 −3 .
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".