Waste organic dye removal using MOF-based electrospun nanofibers of high amine density
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The exceptional structural stability of UiO-66 metal–organic framework (MOF) and ligands' functional groups render UiO-66 as a versatile candidate for multiple applications, including wastewater treatment. The possibility of a broad spectrum of post-synthetic modification of UiO-66 further expands its prospective uses. However, commercial applications of UiO-66 have been hindered by the polycrystalline nature of the powder. In this research, modification to obtain UiO-66-NH2 and post-processing with nanofibers comprising chitosan and polyvinyl alcohol (PVA) were applied to faciliate deployment as a suitable option for water decontamination. MOF nanoparticles were post-synthetically modified with 2,4,6-trichloro-1,3,5-triazine (TCT) and 5-phenyl-tetrazole (PT) to produce high-amine containing UiO-66, thus introducing active nitrogen-containing functional groups that enhanced the removal efficiency of targeted molecules from aqueous media. A systematic study was undertaken to optimize the supporting nanofibers and to demonstrate that even a low MOF functionalization, of up to 7- wt%, offered a maximum methyl orange adsorption capacity of 619 mg/g, superior to most adsorbents reported so far. Furthermore, selectivity, regeneration ability, and the effect of ambient conditions were demonstrated.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it