Evidence map›Paper›PMID 40863589›Full record

ArticleMembranes2025

Pilot-Scale Polysulfone Ultrafiltration Patterned Membranes: Phase-Inversion Parametric Optimization on a Roll-to-Roll Casting System.

Ayesha Ilyas, Ivo F J Vankelecom

Abstract read
In one paragraph

Article in Membranes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Ayesha IlyasMembrane Technology Group (MTG), Division cMACS, Faculty of Bioscience Engineering, KU Leuven, Celestijnenlaan 200F, P.O. Box 2454, 3001 Leuven, Belgium.
Ivo F J VankelecomMembrane Technology Group (MTG), Division cMACS, Faculty of Bioscience Engineering, KU Leuven, Celestijnenlaan 200F, P.O. Box 2454, 3001 Leuven, Belgium.ORCID 0000-0002-0104-9493

Funding

European Union 101058426Flanders Innovation and Entrepreneurship 3E240263KU Leuven 3E230579Research Foundation - Flanders 12B3M24N
6 · The paper itself

Abstract

The scalability and processability of high-performance membranes remain significant challenges in membrane technology. This work focuses on optimizing the pilot-scale production of patterned polysulfone (PSf) ultrafiltration membranes using the spray-modified non-solvent-induced phase separation (s-NIPS) method on a roll-to-roll pilot line. s-NIPS has already been studied extensively at lab-scale to prepare patterned membranes for various applications including membrane bioreactors (MBR), reverse osmosis (RO) and forward osmosis (FO). Although studied at the lab scale, membranes prepared at a larger scale can significantly differ in performance; therefore, phase inversion parameters, including polymer concentration, molecular weight, and additive type (i.e., polyethylene glycol (PEG) or polyvinylpyrolidine (PVP)) and concentration, were systematically varied when casting on a roll-to-roll, 12″ wide pilot line to identify optimal conditions for achieving defect-free, high-performance, patterned PSf membranes. The membranes were characterized for their pure water permeance, BSA rejection, casting solution viscosities, and resulting morphology. s-NIPS patterned membranes exhibit 150-350% increase in water flux as compared to their reference flat membrane, thanks to very high pattern heights up to 825 µm and formation of finger-like macrovoids. This work bridges the gap between lab-scale and pilot-scale membrane preparation, while proposing an upscaled membrane with great potential for use in water treatment.

Indexed as

fouling controlpatterned membranesphase inversionpilot-scale preparationroll-to-roll membrane productionupscaling

Identifiers

PMID40863589
PMCPMC12388136

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.