Development of highly permeable and antifouling poly(vinylidene fluoride) hybrid membranes tailored with <scp>ZIF</scp>‐8 metal–organic frameworks for water treatment
Bibliographic record
Abstract
Abstract This study deals with the making of poly(vinylidene fluoride) (PVDF) hybrid ultrafiltration (UF) membranes incorporated with zeolitic imidazolate framework‐8 (ZIF‐8) nanocrystals. The surface morphology and roughness of ZIF‐8 are explored in terms of atomic force microscopy (AFM) and scanning electron microscopy (SEM) whereas their distribution in PVDF matrix and antibacterial activity are probed by energy dispersive X‐ray (EDX) analysis and zone of inhibition test. The chemical functionality of ZIF‐8 is verified by Fourier transform infrared (FTIR) and X‐ray diffraction (XRD) spectroscopic studies. The permeability of hybrid membranes is raised to 2 wt% addition of ZIF‐8 into the PVDF matrix owing to an enhancement in hydrophilicity and porosity. The FESEM images of the top and cross‐section view make visible the formation of macrovoids with the addition of ZIF‐8. On account of high porosity and surface hydrophilicity, the pure water permeation of hybrid membranes is increased to 278.6 Lm−2 h−1. The hybrid membranes showed higher rejection and permeate flux of bovine serum albumin (BSA; 92.8 Lm−2 h−1) and humic acid (HA; 94.3 Lm−2 h−1) owing to the synergetic effect of their enhanced hydrophilicity and surface roughness. This is confirmed by the higher flux recovery ratio (FRR) and lower irreversible fouling characteristics of hybrid PVDF membranes. The atomic absorption spectroscopy (AAS) revealed the long‐standing stability of ZIF‐8 in the PVDF matrix. Among all, the PVDF hybrid membrane with 2 wt% of ZIF‐8 showed excellent permeability, antifouling, and antibiofouling ability and was found to be more effective in water treatment applications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".