Magnetic Nitrogen-Rich UiO-66 Metal–Organic Framework: An Efficient Adsorbent for Water Treatment
Bibliographic record
Abstract
The postsynthetic modification of metal–organic frameworks (MOFs) has opened up a promising area to widen their water treatment application. However, their polycrystalline powdery state still restricts their widespread industrial-scale applications. Herein, the magnetization of UiO-66-NH 2 is reported as a promising approach to facilitate the separation of the used MOFs after water treatment. A two-step postmodification procedure employing 2,4,6-trichloro-1,3,5-triazine (TCT) and 5-phenyl-1 H -tetrazole (PTZ) agents was introduced to level up the adsorption performance of the magnetic nanocomposite. Despite a decrement in porosity and specific surface area of the designed MOFs (m-UiO-66-TCT) compared to neat UiO-66-NH 2, it outweighs in adsorption capacity. It was observed that m-UiO-66-TCT has an adsorption capacity of ≈298 mg/g for methyl orange (MO) with facile MOF separation using an external magnet. Pseudo-second-order kinetic model and Freundlich isotherm models suitably interpret the experimental data. Thermodynamic studies showed that MO removal using m-UiO-66-TCT is spontaneous and thermodynamically favorable at higher temperatures. The m-UiO-66-TCT composite exhibited easy separation, high adsorption capacity, and good recyclability, rendering it an attractive candidate for the adsorptive removal of MO dye from aqueous environments.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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; both teacher heads agree on what is shown here.
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".