One-pot synthesis of trifunctional chitosan-EDTA-β-cyclodextrin polymer for simultaneous removal of metals and organic micropollutants
Bibliographic record
Abstract
Abstract The global contamination of water resources with inorganic and organic micropollutants, such as metals and pharmaceuticals, poses a critical threat to the environment and human health. Herein, we report on a bio-derived chitosan-EDTA-β-cyclodextrin (CS-ED-CD) trifunctional adsorbent fabricated via a facile and green one-pot synthesis method using EDTA as a cross-linker, for the adsorption of toxic metals and organic micropollutants from wastewater. In this system, chitosan chain is considered as the backbone, and the immobilized cyclodextrin cavities capture the organic compounds via host-guest inclusion complexation, while EDTA-groups complex metals. The thoroughly characterized CS-ED-CD was employed for batch adsorption experiments. The adsorbent displayed a monolayer adsorption capacity of 0.803, 1.258 mmol g −1 for Pb(II) and Cd(II) respectively, while a heterogeneous sorption capacity of 0.177, 0.142, 0.203, 0.149 mmol g −1 for bisphenol-S, ciprofloxacin, procaine, and imipramine, respectively. The adsorption mechanism was verified by FT-IR and elemental mapping. Importantly, the adsorbent perform is effective in the simultaneous removal of metals and organic pollutants at environmentally relevant concentrations. All these findings demonstrate the promise of CS-ED-CD for practical applications in the treatment of micropollutants. This work adds a new insight to design and preparation of efficient trifunctional adsorbents from sustainable materials for water purification.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".