Poly(vinylidene fluoride) ultrafiltration membranes tailored with zirconium‐based <scp>MOF</scp>‐801 for water treatment applications
Bibliographic record
Abstract
Abstract Highly hydrophilic and antifouling poly(vinylidene fluoride) (PVDF) ultrafiltration membranes are developed with excellent permeation using a zirconium‐based metal–organic framework (MOF‐801). MOF‐801 is synthesized by a solvothermal method using zirconium(IV) oxychloride octahydrate (ZrOCl2⋅8H2O) and fumaric acid. The chemical functionality of MOF‐801 is studied by Fourier transform infrared (FTIR) spectroscopy and X‐ray diffraction (XRD) whereas surface morphology and elemental composition are probed by scanning electron microscopy (SEM)/energy‐dispersive X‐ray analysis (EDX). The PVDF/MOF‐801 membranes are characterized in terms of FTIR, XRD, FESEM/EDX and atomic force microscopy. The performance of the hybrid PVDF/MOF‐801 membranes in terms of pure water flux and antifouling ability is found to be improved compared with bare PVDF membranes. The wettability of the membranes is measured by water contact angle and found to be 76.7° for bare PVDF membrane, which decreases upon the addition of MOF‐801 to 55.1° due to the increase in surface hydrophilicity. A notable increase in roughness of 226.29 nm and a porosity of 67.91% is observed for the addition of 2 wt% MOF‐801 in PVDF membrane matrix. The flux recovery ratio of the hybrid membrane is increased from 66.4% to 89.6% and from 68.3% to 85.2% for bovine serum albumin (BSA) and humic acid (HA) separation, respectively. In addition, the reversible and irreversible fouling performance during the rejection of BSA (93%) and HA (88%) indicates the enhanced antifouling property of the PVDF/MOF‐801 membranes. A zone of inhibition test evidences the outstanding antibiofouling activity of the PVDF/MOF‐801 membranes against E. coli and S. aureus. Overall results demonstrated the suitability of hybrid PVDF/MOF‐801 membranes for water and wastewater treatment. © 2023 Society of Industrial Chemistry.
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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) | 0.000 | 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 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".