Evidence map›Paper›PMID 37898660›Full record

ArticleNature communications2023

A super liquid-repellent hierarchical porous membrane for enhanced membrane distillation.

Youmin Hou, Prexa Shah, Vassilios Constantoudis, Evangelos Gogolides, Michael Kappl, Hans-Jürgen Butt

Abstract read
In one paragraph

Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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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

6 authors.

Youmin HouMax Planck Institute for Polymer Research, Ackermannweg 10, 55128, Mainz, Germany.
Prexa ShahMax Planck Institute for Polymer Research, Ackermannweg 10, 55128, Mainz, Germany.
Vassilios ConstantoudisInstitute of Nanoscience and Nanotechnology NCSR Demokritos, 15341, Agia Paraskevi, Greece.
Evangelos GogolidesInstitute of Nanoscience and Nanotechnology NCSR Demokritos, 15341, Agia Paraskevi, Greece.
Michael KapplMax Planck Institute for Polymer Research, Ackermannweg 10, 55128, Mainz, Germany. kappl@mpip-mainz.mpg.de.ORCID http://orcid.org/0000-0001-7335-1707
Hans-Jürgen ButtMax Planck Institute for Polymer Research, Ackermannweg 10, 55128, Mainz, Germany.ORCID http://orcid.org/0000-0001-5391-2618

Funding

EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020) 801229National Natural Science Foundation of China (National Science Foundation of China) 52276160
6 · The paper itself

Abstract

Membrane distillation (MD) is an emerging desalination technology that exploits phase change to separate water vapor from saline based on low-grade energy. As MD membranes come into contact with saline for days or weeks during desalination, membrane pores have to be sufficiently small (typically <0.2 µm) to avoid saline wetting into the membrane. However, in order to achieve high distillation flux, the pore size should be large enough to maximize transmembrane vapor transfer. These conflicting requirements of pore geometry pose a challenge to membrane design and currently hinder broader applications of MD. To address this fundamental challenge, we developed a super liquid-repellent membrane with hierarchical porous structures by coating a polysiloxane nanofilament network on a commercial micro-porous polyethersulfone membrane matrix. The fluorine-free nanofilament coating effectively prevents membrane wetting under high hydrostatic pressure (>11.5 bar) without compromising vapor transport. With large inner micro-porous structures, the nanofilament-coated membrane improves the distillation flux by up to 60% over the widely used commercially available membranes, while showing excellent salt rejection and operating stability. Our approach will allow the fabrication of high-performance composite membranes with multi-scale porous structures that have wide-ranging applications beyond desalination, such as in cleaning wastewater.

Identifiers

PMID37898660
PMCPMC10613234

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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.