Synthesis and Characterization of Zirconium Doped Nickel Oxide Nanoparticles Using Acalypha indica L Extract and Its Antimicrobial Activities
Bibliographic record
Abstract
Nanomaterials have had one of the dimensions in the range of 1-100 nm and it's had wide range of application in various fields.The materials produces by the processing in the greener route have more sustain nature.Based on this, the investigation focused on plants based green synthesis of Zr-doped Nickel oxide nanoparticles (NiO Nps) using Acalypha indica Leaf extract for synthesis and its potential applications.The synthesized Zr doped NiO nanoparticles were characterized using Scanning electron microscopy (SEM), X-ray diffraction spectroscopy (XRD), and Fourier transform-infrared spectroscopy (FT-IR) and UV Visible spectroscopy (UV-Vis).The optical absorption calculated and confirmed by UV Visible spectroscopy, the wavelength range is 260 nm.The FCC indexing with its crystalline structure confirmed by XRD.The band at 470 confirmed the presence of NiO using FTIR, Prepared Nano sized materials present in 85 nm ensured through SEM analysis.AFM analysis of the synthesized materials represents the topography Zr doped NiO NPs deliberates good antibacterial activity.
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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".