Evidence map›Paper›PMID 42389581›Full record

ArticleiScience2026

Data-driven design of hybrid graphene oxide-MXene polymeric membranes for water purification.

Rauf Khan, Nadeem Baig, Zaher Mundher Yaseen, Mohammad Al-Suwaiyan

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in iScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Rauf KhanDepartment of Civil and Environmental Engineering, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia.
Nadeem BaigInterdisciplinary Research Center for Membranes and Water Security, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia.
Zaher Mundher YaseenDepartment of Civil and Environmental Engineering, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia.
Mohammad Al-SuwaiyanDepartment of Civil and Environmental Engineering, King Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Two-dimensional (2D) materials offer promising platforms for water purification, particularly for challenging oil-in-water emulsions. Here, a hybrid membrane combining graphene oxide (GO) and MXene nanosheets was fabricated on a nylon support to explore the relationship between membrane composition and separation performance. Four membranes with varying GO loadings were evaluated, and machine learning models were applied to predict rejection efficiency using key operational parameters. Among the tested models, support vector regression achieved the highest predictive accuracy (R

Indexed as

Applied sciencesMaterials sciencePolymers

Identifiers

PMID42389581
PMCPMC13319368

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.