Solid state synthesis, characterization and biological evaluation of silver doped nanosized metal oxides
Bibliographic record
Abstract
Nanomaterials have attracted a great deal of attention from the scientific community due to their unique properties and applications. The small size metal oxides have opened up the door for intensive research to utilize their properties for biomedical applications. Silver nanoparticle (AgNPs) and metal oxide nanomaterials like MgO, ZnO, NiO and its silver doped nanocomposites (Ag-MgO, Ag-ZnO, Ag-NiO) have been prepared using solid state combustion method using polyvinyl alcohol (PVA) as a fuel. The structure of as prepared oxides and its silver doped nanocomposites were characterized using X-ray diffraction (XRD) tool and morphology by Scanning Electron Micrograph (SEM) tool as well as Transmission electron micrograph tool respectively. Presence of the metals in the oxides and its Ag composite was confirmed by the EDX pattern. Bonding nature in the composite is well studied by the Fourier transform infrared (FT-IR) tool. Antibacterial activity studies of the nanocomposites are carried out against various bacteria.
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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 | 0.001 | 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) | 0.000 | 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".