Evidence map›Paper›PMID 31891480›Full record

ArticleACS nano2020

Tunable Anion-Selective Transport through Monolayer Graphene and Hexagonal Boron Nitride.

Mustafa Caglar, Inese Silkina, Bertram T Brown, Alice L Thorneywork, Oliver J Burton, Vitaliy Babenko, Stephen Matthew Gilbert, Alex Zettl, Stephan Hofmann, Ulrich F Keyser

Abstract read
In one paragraph

Article in ACS nano, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 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

10 authors.

Mustafa CaglarCavendish Laboratory, University of Cambridge, J.J. Thomson Avenue, Cambridge CB3 0HE, United Kingdom.ORCID http://orcid.org/0000-0001-7547-1817
Inese SilkinaDepartment of Materials Science and Metallurgy, University of Cambridge, Cambridge CB3 0FS, United Kingdom.
Bertram T BrownCavendish Laboratory, University of Cambridge, J.J. Thomson Avenue, Cambridge CB3 0HE, United Kingdom.
Alice L ThorneyworkCavendish Laboratory, University of Cambridge, J.J. Thomson Avenue, Cambridge CB3 0HE, United Kingdom.
Oliver J BurtonDepartment of Engineering, University of Cambridge, Cambridge CB3 0FA, United Kingdom.
Vitaliy BabenkoDepartment of Engineering, University of Cambridge, Cambridge CB3 0FA, United Kingdom.
Stephen Matthew GilbertDepartment of Physics, University of California, Berkeley, Berkeley, California 94720, United States.
Alex ZettlDepartment of Physics, University of California, Berkeley, Berkeley, California 94720, United States.
Stephan HofmannDepartment of Engineering, University of Cambridge, Cambridge CB3 0FA, United Kingdom.ORCID http://orcid.org/0000-0001-6375-1459
Ulrich F KeyserCavendish Laboratory, University of Cambridge, J.J. Thomson Avenue, Cambridge CB3 0HE, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Membranes that selectively filter for both anions and cations are central to technological applications from clean energy generation to desalination devices. 2D materials have immense potential as these ion-selective membranes due to their thinness, mechanical strength, and tunable surface chemistry; however, currently, only cation-selective membranes have been reported. Here we demonstrate the controllable cation and anion selectivity of both monolayer graphene and hexagonal boron nitride. In particular, we measure the ionic current through membranes grown by chemical vapor deposition containing well-known defects inherent to scalably produced and wet-transferred 2D materials. We observe a striking change from cation selectivity with monovalent ions to anion selectivity by controlling the concentration of multivalent ions and inducing charge inversion on the 2D membrane. Furthermore, we find good agreement between our experimental data and theoretical predictions from the Goldman-Hodgkin-Katz equation and use this model to extract selectivity ratios. These tunable selective membranes conduct up to 500 anions for each cation and thus show potential for osmotic power generation.

Indexed as

anion-selectivecharge inversionGHKgraphenehBNion-selective membranestunable

Identifiers

PMID31891480
PMCPMC7098055

What OpenQuestion holds

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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.