A Review on Bioinspired and Green Synthesis of Silver Nanoparticles with Their Antimicrobial Activity
Bibliographic record
Abstract
The biosynthesis of metal nanoparticles (NPs) using plant extracts is one of the simplest, most useful, affordable, and environmentally friendly solutions to prevent the use of dangerous chemicals. The unique antimicrobial properties of silver (Ag) NPs have attracted the most interest among all the other nanoparticles. Concerns regarding the synthesis of these NPs, including the use of hazardous solvents and precursor chemicals, microbial contamination and the creation of toxic byproducts, led to the development of the new alternative process known as "green synthesis." As a result, various environmentally acceptable methods for producing Ag NPs quickly using aqueous extracts of plant parts like bark, roots, leaves, and so forth have been published in recent years. We discuss contemporary advancements in the environmentally friendly manufacturing of AgNPs, their application as antifungal agents, and their mode of action in this study. This review provides insight into the environmentally friendly manufacturing of Ag NPs, their application as antifungal agents with their mode of action, as well as their future prospects.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".