Soybean (<i>Glycine Max</i>) Leaf Extract Based Green Synthesis of Palladium Nanoparticles
Bibliographic record
Abstract
Palladium (Pd) nanoparticles were synthesized using protein rich soybean leaf extract based biological process. Reduction of palladium ions by soybean leaf extract was examined by UV-visible spectroscopic technique. It was believed that the proteins and some of the amino acids that are exist in soybean leaf extracts were actively involved in the reduction of palladium ions. Further it was confirmed by Fourier transformations infrared spectroscopic (FTIR) analysis. These amino acids are not only involving in the reduction of palladium ions but also acting as surfactants that inhibits the rapid agglomeration. The phase purity of the synthesized palladium nanoparticles was investigated through X-Ray Diffraction (XRD) analysis and the obtained pattern was compared with JCPDS data. Transmission electron microscopic (TEM) images of the palladium particles were recorded and the particle size was found to be ~15 nm.
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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".