Evidence map›Paper›PMID 42059125›Full record

ArticleEnvironmental science & technology2026

Mechanistic Insights into PFAS Rejection in Nanofiltration and Reverse Osmosis from Data-Driven Analysis.

Yukai Tomsovic, Siwei Gu, Kyle Doudrick, Anthony P Straub

Abstract read
In one paragraph

Article in Environmental science & technology, 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.

Yukai TomsovicDepartment of Mechanical and Process Engineering, ETH Zürich, Zürich 8092, Switzerland.
Siwei GuDepartment of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, Indiana 46556, United States.ORCID 0009-0002-9647-5109
Kyle DoudrickDepartment of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, Indiana 46556, United States.ORCID 0000-0003-1912-9819
Anthony P StraubDepartment of Mechanical and Process Engineering, ETH Zürich, Zürich 8092, Switzerland.ORCID 0000-0001-7233-6839

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The structural diversity and complex transport behavior of per- and polyfluoroalkyl substances (PFAS) complicate a universal characterization of their removal in membrane systems. This study compiles 2353 data points from the literature on PFAS rejection by nanofiltration and reverse osmosis membranes, spanning a broad range of PFAS, membranes, feedwater compositions, and operating conditions. Using machine learning, this data set is modeled to evaluate how solute, membrane, and solution properties jointly influence PFAS removal. Of the 13 experimental system descriptors analyzed, membrane water permeance and PFAS molecular volume demonstrated the strongest main effect on rejection, emphasizing the significance of steric exclusion. The effects of background ions and dissolved organic matter were highly condition-dependent, exhibiting nonmonotonic behavior governed by competing mechanisms. Low concentrations of organic matter and ions enhanced PFAS rejection, consistent with complexation that increases apparent solute size, while higher concentrations reduced PFAS rejection, indicating that charge shielding and concentration polarization increasingly drive transport behavior. Overall, this analysis provides a unified, data-driven framework for interpreting previously inconsistent findings across studies, identifies critical gaps in existing experimental data, and highlights opportunities to guide targeted membrane design and treatment strategies.

Indexed as

FluorocarbonsFiltrationMembranes, ArtificialOsmosisFluorocarbonsMembranes, Artificialmachine learningmeta-analysisnanofiltrationper- and polyfluoroalkyl substancesreverse osmosis

Identifiers

PMID42059125
PMCPMC13173650

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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.