Evidence map›Paper›PMID 42014380›Full record

ArticleNature communications2026

Lotus-leaf-mimetic catalytic cleaning membranes with enriched oxygen vacancies for efficient water purification.

Xiaobin Yang, Hongfei Bao, Haoyang Wang, Yangxue Li, Runliang Gao, Xinyu Wang, Jun Ma, Bhekie B Mamba, Alicia Kyoungjin An, Lu Shao

Abstract read
In one paragraph

Article in Nature communications, 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

10 authors.

Xiaobin YangMIIT Key Laboratory of Critical Materials Technology for New Energy Conversion and Storage, State Key Laboratory of Urban-rural Water Resource and Environment, School of Chemistry and Chemical Engineering, Harbin Institute of Technology, Harbin, PR China.ORCID http://orcid.org/0009-0004-5431-730X
Hongfei BaoMIIT Key Laboratory of Critical Materials Technology for New Energy Conversion and Storage, State Key Laboratory of Urban-rural Water Resource and Environment, School of Chemistry and Chemical Engineering, Harbin Institute of Technology, Harbin, PR China.
Haoyang WangMIIT Key Laboratory of Critical Materials Technology for New Energy Conversion and Storage, State Key Laboratory of Urban-rural Water Resource and Environment, School of Chemistry and Chemical Engineering, Harbin Institute of Technology, Harbin, PR China.
Yangxue LiMIIT Key Laboratory of Critical Materials Technology for New Energy Conversion and Storage, State Key Laboratory of Urban-rural Water Resource and Environment, School of Chemistry and Chemical Engineering, Harbin Institute of Technology, Harbin, PR China.
Runliang GaoMIIT Key Laboratory of Critical Materials Technology for New Energy Conversion and Storage, State Key Laboratory of Urban-rural Water Resource and Environment, School of Chemistry and Chemical Engineering, Harbin Institute of Technology, Harbin, PR China.
Xinyu WangMIIT Key Laboratory of Critical Materials Technology for New Energy Conversion and Storage, State Key Laboratory of Urban-rural Water Resource and Environment, School of Chemistry and Chemical Engineering, Harbin Institute of Technology, Harbin, PR China.
Jun MaSchool of Environment, Harbin Institute of Technology, Harbin, PR China.ORCID http://orcid.org/0000-0002-0903-5547
Bhekie B MambaInstitute for Nanotechnology and Water Sustainability, College of Engineering, Science and Technology, University of South Africa Florida Science Campus, Roodepoort, South Africa. mambabb@unisa.ac.za.
Alicia Kyoungjin AnDepartment of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China. alicia.kjan@ust.hk.ORCID http://orcid.org/0000-0003-0041-2817
Lu ShaoMIIT Key Laboratory of Critical Materials Technology for New Energy Conversion and Storage, State Key Laboratory of Urban-rural Water Resource and Environment, School of Chemistry and Chemical Engineering, Harbin Institute of Technology, Harbin, PR China. shaolu@hit.edu.cn.ORCID http://orcid.org/0000-0002-4161-3861

Funding

National Natural Science Foundation of China (National Science Foundation of China) 52403265Postdoctoral Research Foundation of China (China Postdoctoral Research Foundation) BX2021089State Key Laboratory of Urban Water Resource and Environment (SKLUWRE) 2024DX02
6 · The paper itself

Abstract

Separation membranes with inherent low-carbon properties are crucial for energy‒water sustainability but suffer from fouling issue and performance deficiency. Herein, a lotus-leaf-mimetic catalytic membrane is synthesized via 2,3,6,7,10,11-hexahydroxytriphenylene (HHTP)-Co metal-organic intermediate layer-mediated MnO₂ mineralization, transforming hydrophobic polymeric membranes into unique self-cleaning membranes. The derivative abundant oxygen vacancies during hetero-phase mineralization boost their catalytic capability. The lotus leaf-mimicking nano/micro-water pockets at the interface enable the membrane operando flux recovery to reach 99.9%. Most interestingly, the membrane exhibited 24.8-fold greater antifouling ability and 10.6-fold greater recovery compared with the unmineralized membrane, significantly outperforming state-of-the-art membranes. The exceptional performance for water treatment is attributed to active catalytic antifouling coupled with hierarchical antifouling barriers. The computational simulations reveal electron-rich bell-like structures with electron-deficient metal cores. This work paves a way for the fabrication of biomimetic materials for efficient water treatment and beyond.

Identifiers

PMID42014380
PMCPMC13287683

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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.