Evidence map›Paper›PMID 40863605›Full record

ArticleMembranes2025

Novel Dual-Layer Zwitterionic Modification of Electrospun Nanofibrous Membrane for Produced Water Treatment and Reclamation.

Sunith B Madduri, Raghava R Kommalapati

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.

Sunith B MadduriCenter for Energy and Environmental Sustainability, Prairie View A&M University, Prairie View, TX 77446, USA.ORCID 0000-0001-5318-2192
Raghava R KommalapatiCenter for Energy and Environmental Sustainability, Prairie View A&M University, Prairie View, TX 77446, USA.ORCID 0000-0002-3267-6684

Funding

U.S. National Science Foundation 1900787U.S. National Science Foundation 1914692
6 · The paper itself

Abstract

Produced water, a byproduct of oil and gas extraction, poses significant environmental challenges due to its complex composition and high salinity. Conventional treatment technologies often struggle to achieve efficient contaminant removal while maintaining long-term operational stability. Membrane-based separation processes, particularly forward osmosis (FO), offer a promising alternative due to their low hydraulic pressure requirements, high selectivity, and ability to mitigate fouling and scaling effects. This study fabricated and evaluated a novel dual-layer zwitterion-modified electrospun nanofibrous membrane for enhanced produced water (PW) treatment. The dual-layer design consists of a highly porous electrospun nanofibrous support layer for improved permeability and mechanical strength, coupled with a zwitterionic-modified selective layer to enhance antifouling properties and selective contaminant rejection. The zwitterionic surface modification imparts superior hydration capacity, reducing organic and biological fouling while improving water transport efficiency. The membranes are characterized using scanning electron microscopy (SEM), thermogravimetric analysis (TGA), Fourier Transform Infrared (FTIR) spectroscopy, X-ray diffraction (XRD), contact angle and tensile strength measurements, and nuclear magnetic resonance (NMR) spectroscopy to assess their morphological, structural, and chemical properties. The performance evaluations demonstrated significantly higher water flux (up to 16.05 L m

Indexed as

electrospinningnanofibrous dual-layer membraneproduced water treatmentsustainable water reusezwitterionic surface modification

Identifiers

PMID40863605
PMCPMC12388745

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.