Removal of Toxic Organic Micropollutants with FeTsPc-Immobilized Amberlite/H<sub>2</sub>O<sub>2</sub>: Effect of Physicochemical Properties of Toxic Chemicals
Bibliographic record
Abstract
The effect of physicochemical properties of organic micropollutants on removal efficiencies over iron-tetrasulfophthalocyanine (FeTsPc)-immobilized Amberlite was investigated with one endocrine-disrupting chemical (EDC), bisphenol-A (BPA), and three pharmaceutically active chemicals (PhACs), cefaclor, diclofenac, and ibuprofen. The electrical charge of each chemical was the most important factor in overall removal efficiency. Hydrophilicity was the second most important factor. Negatively charged diclofenac and ibuprofen were completely removed at the reaction pH of 7.5 in less than 1 hour in the absence of H 2 O 2 . The FeTsPc-immobilized Amberlite catalyst accelerated BPA and cefaclor removal in the presence of H 2 O 2 at pH 7.5. For BPA, catalytic oxidation accounted for at least 35% of total removal. The stability of FeTsPc was greatly improved by immobilizing it on Amberlite compared to that of the homogeneous FeTsPc in an aqueous solution.
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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) | 0.001 | 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".