Evidence map›Paper›PMID 40998846›Full record

ArticleNature communications2025

Microstructure engineering of polyamide membranes for ultrafast polar and non-polar solvent transport.

Huiqing Wu, Yang Xu, Qingchen Tang, Baohu Wu, Peiyi Wu

Abstract read
In one paragraph

Article in Nature communications, 2025. 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

5 authors.

Huiqing WuState Key Laboratory of Advanced Fiber Materials (Donghua University), College of Chemistry and Chemical Engineering, Donghua University, Shanghai, China. huiqingwu@dhu.edu.cn.ORCID http://orcid.org/0009-0003-8170-6004
Yang XuState Key Laboratory of Advanced Fiber Materials (Donghua University), College of Chemistry and Chemical Engineering, Donghua University, Shanghai, China.
Qingchen TangState Key Laboratory of Advanced Fiber Materials (Donghua University), Center for Advanced Low-Dimension Materials, and College of Materials Sciences and Engineering, Donghua University, Shanghai, China.
Baohu WuJülich Centre for Neutron Science (JCNS) at Heinz Maier-Leibnitz Zentrum (MLZ) Forschungszentrum Jülich, Garching, Germany.ORCID http://orcid.org/0000-0002-1291-8965
Peiyi WuState Key Laboratory of Advanced Fiber Materials (Donghua University), College of Chemistry and Chemical Engineering, Donghua University, Shanghai, China. wupeiyi@dhu.edu.cn.ORCID http://orcid.org/0000-0001-7235-210X

Funding

National Natural Science Foundation of China (National Science Foundation of China) 52433003
6 · The paper itself

Abstract

Highly permselective membranes with superior permeability and broad applicability are essential for organic solvent nanofiltration (OSN). However, conventional polyamide membranes often suffer from limited permeability, especially for non-polar solvents. We herein propose a simple yet effective strategy to fabricate polyamide membranes capable of ultrafast separation for both polar and non-polar solvents. By utilizing a non-planar amine monomer with diphenyl ether moiety, interfacial polymerization is rationally conducted at the deep eutectic solvent/alkane interface, yielding an ultrathin polyamide layer (~12 nm) with enhanced microporosity, uniform nanopores and a Janus-like microstructure. The resultant membrane demonstrates high permeability (36.6 L m⁻² h⁻¹ bar⁻¹ for methanol, 56.6 L m⁻² h⁻¹ bar⁻¹ for hexane), precise molecular sieving capability and excellent structural stability. The work provides a paradigm for developing high-performance OSN membranes through the molecular-level design and powerful control of the manufacturing process.

Identifiers

PMID40998846
PMCPMC12462488

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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.