Nanocomposite egg shell powder with in situ generated silver nanoparticles using inherent collagen as reducing agent
Bibliographic record
Abstract
Silver nanoparticles (AgNPs) were in situ generated in poultry hen egg shell powder (ESP) by one step thermal assisted method using the inherently present collagen as a reducing agent. The nanocomposite egg shell powder (NCESP) with in situ generated silver nanoparticles was characterized by scanning electron microscopy (SEM), Fourier transform infrared (FT-IR) spectroscopy, X-ray diffraction (XRD), thermogravimetric analysis (TGA) and antibacterial tests. The prepared NCESP had the spherical AgNPs in the size range of 50–120 nm with most of them from 81 nm to 90 nm. Further, the average size of the AgNPs generated in the NCESP was 88 nm. The X-ray analysis indicated the presence of both AgNPs and AgO nanoparticles (AgONPs) in the NCESP. The possible mechanism of generation of AgNPs and AgONPs in the NCESP was also proposed. The thermal stability of the NCESP was found to be higher than that of the ESP. The NCESP exhibited excellent antibacterial activity against both the Gram negative and positive bacteria. The NCESP made from poultry waste ESP can be utilized as a low-cost antibacterial cleaning powder for house ware and also as low-cost antibacterial filler in polymer matrices to make antibacterial hybrid nanocomposites.
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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) | 0.001 | 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".