Microwave-assisted synthesis and characterizations of nanosized copper ferrite and barium titanate for antimicrobial applications
Bibliographic record
Abstract
Science and technology of nanosized bimetallic oxide nanomaterials records the various properties and applications. Especially biomedical applications are viewed in particular due to its nanosized particle size. The present experimentation is reporting the microwave-assisted synthesis of nanosized bimetallic oxides like copper ferrite (CuFe2O4) and barium titanate (BaTiO3) by solid state combustion route using poly (vinyl alcohol) (PVA) as a fuel. The structural and morphological characterizations of the bimetallic oxide nanomaterials are performed out by X-ray diffraction (XRD) and scanning electron micrograph (SEM) tools respectively. These analyses report the crystalline nature of both samples. EDX spectral study is also undertaken to know the existence of different metals in the above-mentioned samples. Bonding nature of the bimetallic oxide samples were readied by Fourier transfer infrared (FT-IR) instrumentation. The study reviewed the varied vibrational modes confirms the phase formation of the samples. UV-Vis and thermal study of these bimetallic oxide samples are also studied extensively to know the thermal and absorption behavior respectively. TGA of both the samples are traced and are showing decomposition at rapid rate. In addition, the maximum absorption peaks due to π - π* transition confirms the sample formation. Antimicrobial activity of the prepared oxide samples was studied for antibacterial and antifungal behavior. Both samples showing considerable activity against various bacteria and fungi.
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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".