Paracetamol removal by bimetallic zero-valent Fe/Cu with benjamina leaf extract
Bibliographic record
Abstract
A green synthesis approach using Ficus benjamina leaf extract was successfully used for preparing bimetallic zero-valent iron (Fe)/copper (Cu) nanoparticles. The F. benjamina nano-zero-valent iron/copper (FB-nZVFe/Cu) was characterised by energy-dispersive X-ray spectroscopy, scanning electron microscopy and Fourier transform infrared spectroscopy. The characterisation showed that bimetallic nanoparticles had been synthesized. The removal efficiency at a concentration of 10 mg/l reached 86% under the following conditions: dose of 0·5 g/l, time of 45 min and pH of 5. FB-nZVFe/Cu had good durability and stability and possessed excellent reusability for removal of paracetamol (C 15 H 12 N 2 O) even after being reused five times. The results were analysed according to the Langmuir and Freundlich adsorption isotherm models. The adsorption data agree more with the Langmuir model (R 2 = 0·9989), with q max = 16·49 mg/g. The results of adsorption kinetics indicate that paracetamol uptake on FB-nZVFe/Cu follows a pseudo-second-order kinetic model. Overall, FB-nZVFe/Cu is a favourable green material for removal of paracetamol from aqueous solutions. The effect of varying the functional parameters was investigated using linear regression analysis; they were found to account for more than 98% of the variables affecting the removal procedure.
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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 | 0.000 | 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 | 0.001 |
| 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".