Efficient removal of tebuconazole from wastewater by zinc‐modified passion fruit peels: Adsorption behaviour and mechanism
Bibliographic record
Abstract
Abstract In this research, an effective adsorbent, ZnCl2‐modified biochar (Zn‐PFPB), was prepared from unprocessed passion fruit peel (PFP) for the removal of tebuconazole (TE) from wastewater. The synthesized Zn‐PFPB was characterized by Fourier transform infrared spectroscopy (FT‐IR), scanning electron microscopy (SEM), X‐ray photoelectron spectroscopy (XPS), X‐ray diffraction (XRD), N 2 adsorption/desorption curves, and point of zero charge, which suggested that Zn‐PFPB had an amorphous structure and high porosity. Optimal TE removal occurred at pH 2 with an adsorbent dosage of 0.5 g L −1 . The kinetics of the adsorption process followed the pseudo‐second‐order model while the isotherm model used was the Langmuir model, suggesting monolayer chemisorption. The maximum adsorption capacity reached 201.32 mg g −1 for TE. The adsorption mechanisms were pore filling, hydrogen bonding, π‐π interactions, and surface complexation. Importantly, Zn‐PFPB maintained removal efficiency of more than 65% over a broad pH range (2–10), which can be considered as a promising candidate for practical applications. The regeneration rate of Zn‐PFPB was determined to be 70% after the third cycle when using 1 mol L −1 NaOH. The cost analysis showed a fabrication cost of $5.093/kg for Zn‐PFPB. Batch mode scale‐up design showed that 18 g of Zn‐PFPB can remove 95% TE from 50 L of wastewater containing 50 mg L −1 TE. This work proposes a new, economical, and eco‐friendly way of managing agricultural waste in wastewater treatment and soil management.
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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) | 0.000 | 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 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".