Postsynthetic Polymerization of UiO-66-NH <sub>2</sub> for the Fabrication of Nylon/MOF Hybrid Membranes with Enhanced PFOS and PFOA Uptake
Bibliographic record
Abstract
This study presents an approach for fabricating Nylon/MOF hybrid membranes via the postsynthetic modification of UiO-66-NH 2 to introduce polymerizable moieties, followed by in situ polymerization with Nylon. Comprehensive characterization (FTIR, XPS, TGA, powder X-ray diffraction, SEM/EDS, TEM, and LC-MS) confirms the retention of MOF crystallinity, homogeneous dispersion within the Nylon (PA) matrix, and effective capture of per- and polyfluoroalkyl substances (PFAS). The resulting composites exhibit markedly enhanced adsorption capacities from water: for perfluorooctanesulfonic acid (PFOS), PA membranes show Q max = 94 mg g –1 while PA–MOF achieves 102 mg g –1; for perfluorooctanoic acid (PFOA), PA membranes show Q max = 18 mg g –1 while PA–MOF reaches 31 mg g –1, corresponding to increases of 9 and 72%, respectively. Although the hybrid membranes display lower Q max values than the pure MOF (160 to >2000 mg g –1 ), they exhibit significantly higher affinity constants. From the best-fit models, the affinity constants were: PFOS─PA (Double-Langmuir) K L,1 = 0.22, K L,2 = 11.02; PA–MOF (Double-Langmuir) K L,1 = 0.36, K L,2 = 25.96; and PFOA─PA (Sips) K S = 0.90 ( n = 0.68), PA–MOF (Sips) K S = 0.36 ( n = 1.32). These results indicate stronger interactions and superior uptake efficiency at low PFAS concentrations─an essential feature for real water treatment applications─and, in the case of PA–MOF, a cooperative intrapore mechanism for PFOA adsorption ( n > 1). Adsorption modeling reveals dual-site interactions best described by the Double-Langmuir and Sips isotherms, consistent with heterogeneous binding arising from polar amide functionalities in Nylon and the intrinsically high surface area of the MOF. Overall, this work demonstrates a robust and scalable route to hybrid membranes for advanced water purification and environmental remediation.
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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) | 0.000 | 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 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".