NanoSilver/CS Solutions Optical Characterizations and Some Applications
Bibliographic record
Abstract
In this paper we demonstrate physical method (Gamma irradiation technique) for synthesizing Ag-NPs when there is no reduction agent or heat treatment as useful in antimicrobial applications and medical devices.As a strong support, stabilizer, and silver precursor, Chitosan (CS) and AgNO3 were utilized.Ag/Cs characteristics were investigated as a function of gamma dose and -irradiation periods in recent published paper.For conducting the research in Ag-CS-Isopropanol (IPA) by gamma Irradiation method, here we used UV-vis spectroscopy for examining energy gap and Plasmon resonance of surface (SPR) of the produced silver nanoparticles (Ag-NPs).Manufactured Ag-NP UV-vis spectroscopy revealed as the gamma dose increased, the highest wavelength intensity of the plasmon peaks rose.and with energy gap in rang (2.1-2.4)eV.The effect of Ag/CS-APA solutions has examined due on human blood properties and antibacterial activity to water samples selected from local riverbank in Iraq.Overall, the optical characteristic of Ag-CS-APA nanocomposite solution make them promising material for optical thin films and as antibacterial agent in health sector.
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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) | 0.003 | 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".