Studies on photo‐assisted removal of Cr(VI) by ZnO particles
Bibliographic record
Abstract
The present work deals with the photocatalytic removal of Cr(VI) by zinc oxide particles. Cr(VI) removal capacity of 494.4 mg/g, 369.27 mg/g, and 355.59 mg/g was noted in sunlight, fluorescent, and dark conditions respectively at optimized parameters (pH: 5.0, initial Cr(VI) concentration: 50 mg/L, particle dosage: 10 mg/L, contact time: 60 min). A Langmuir isotherm model and pseudo first order kinetics were observed. The aggregation of Cr(VI) interacted ZnO particles was observed by dynamic light scattering (DLS), field emission scanning electron microscopy (FESEM), and transmission electron microscopy (TEM). The results suggest the photon‐assisted reduction of Cr(VI) to Cr(III) on the ZnO particle. The EDX, FTIR, and EELS indicated Cr(VI) removal by an adsorption‐coupled reduction mechanism. Lower aggregation observed in the sunlight condition favoured enhanced Cr(VI) sorption compared to that in fluorescent light. Fourier transform infrared spectroscopy (FTIR) and energy‐dispersive X‐ray spectroscopy (EDX) confirmed the interaction of Cr(VI) on the particle surface and the electron energy loss spectroscopy (EELS) confirmed its subsequent reduction to Cr(III). The applicability of the process was studied with Cr(VI)–Cr(III) binary mixture and the multi–metal solutions.
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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".