Evidence map›Paper›PMID 38669337›Full record

ArticleScience advances2024

Accurate prediction of solvent flux in sub-1-nm slit-pore nanosheet membranes.

Xiaofang Chen, Yao Qin, Yudan Zhu, Xueling Pan, Yuqi Wang, Hongyu Ma, Ruoxin Wang, Christopher D Easton, Yu Chen, Cheng Tang and 9 more

Abstract read
In one paragraph

Article in Science advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 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

19 authors.

Xiaofang ChenDepartment of Chemical and Biological Engineering, Monash University, Clayton, Victoria 3800, Australia.ORCID 0000-0001-5848-4413
Yao QinState Key Laboratory of Materials-Oriented Chemical Engineering, Nanjing Tech University, Nanjing, Jiangsu 211816, China.ORCID 0000-0003-4309-963X
Yudan ZhuState Key Laboratory of Materials-Oriented Chemical Engineering, Nanjing Tech University, Nanjing, Jiangsu 211816, China.
Xueling PanState Key Laboratory of Materials-Oriented Chemical Engineering, Nanjing Tech University, Nanjing, Jiangsu 211816, China.ORCID 0000-0002-9798-053X
Yuqi WangDepartment of Chemical and Biological Engineering, Monash University, Clayton, Victoria 3800, Australia.ORCID 0000-0001-7722-393X
Hongyu MaDepartment of Chemical and Biological Engineering, Monash University, Clayton, Victoria 3800, Australia.ORCID 0009-0007-8444-8564
Ruoxin WangDepartment of Chemical and Biological Engineering, Monash University, Clayton, Victoria 3800, Australia.
Christopher D EastonCSIRO Manufacturing, Private Bag 10, Clayton South, Victoria 3169, Australia.ORCID 0000-0002-1981-3779
Yu ChenMonash Centre for Electron Microscopy, Monash University, Victoria 3800, Australia.ORCID 0000-0001-7882-1077
Cheng TangSchool of Chemistry, Physics and Mechanical Engineering, Science and Engineering Faculty, Queensland University of Technology, Brisbane, Queensland 4001, Australia.ORCID 0000-0003-4543-7591
Aijun DuSchool of Chemistry, Physics and Mechanical Engineering, Science and Engineering Faculty, Queensland University of Technology, Brisbane, Queensland 4001, Australia.ORCID 0000-0002-3369-3283
Aisheng HuangState Key Laboratory of Molecular & Process Engineering, Shanghai Key Laboratory of Green Chemistry and Chemical Processes, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai, China.ORCID 0000-0002-9727-4379
Zongli XieCSIRO Manufacturing, Private Bag 10, Clayton South, Victoria 3169, Australia.ORCID 0000-0002-4610-0758
Xiwang ZhangUQ Dow Centre, School of Chemical Engineering, The University of Queensland, St Lucia, Queensland 4072, Australia.ORCID 0000-0002-4319-527X
George P SimonDepartment of Materials Science and Engineering, Monash University, Clayton, Victoria 3800, Australia.ORCID 0000-0001-8832-1164
Mark M Banaszak HollDepartment of Chemical and Biological Engineering, Monash University, Clayton, Victoria 3800, Australia.ORCID 0000-0001-7759-7456
Xiaohua LuState Key Laboratory of Materials-Oriented Chemical Engineering, Nanjing Tech University, Nanjing, Jiangsu 211816, China.ORCID 0000-0001-9244-6808
Kostya NovoselovInstitute for Functional Intelligent Materials, National University of Singapore, Building S9, 4 Science Drive 2, Singapore 117544, Singapore.ORCID 0000-0003-4972-5371
Huanting WangDepartment of Chemical and Biological Engineering, Monash University, Clayton, Victoria 3800, Australia.ORCID 0000-0002-9887-5555

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nanosheet-based membranes have shown enormous potential for energy-efficient molecular transport and separation applications, but designing these membranes for specific separations remains a great challenge due to the lack of good understanding of fluid transport mechanisms in complex nanochannels. We synthesized reduced MXene/graphene hetero-channel membranes with sub-1-nm pores for experimental measurements and theoretical modeling of their structures and fluid transport rates. Our experiments showed that upon complete rejection of salt and organic dyes, these membranes with subnanometer channels exhibit remarkably high solvent fluxes, and their solvent transport behavior is very different from their homo-structured counterparts. We proposed a subcontinuum flow model that enables accurate prediction of solvent flux in sub-1-nm slit-pore membranes by building a direct relationship between the solvent molecule-channel wall interaction and flux from the confined physical properties of a liquid and the structural parameters of the membranes. This work provides a basis for the rational design of nanosheet-based membranes for advanced separation and emerging nanofluidics.

Identifiers

PMID38669337
PMCPMC11051674

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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.