Evidence map›Paper›PMID 41878466›Full record

ArticleThe journal of physical chemistry. C, Nanomaterials and interfaces2026

Revealing the Innate Subnanometer Porous Structure of Carbon Nanomembranes with Molecular Dynamics Simulations and Highly-Charged Ion Spectroscopy.

Filip Vuković, Anna Niggas, Levin Mihlan, Zhen Yao, Armin Gölzhäuser, Louise Fréville, Vladislav Stroganov, Andrey Turchanin, Jürgen Schnack, Nigel A Marks and 1 more

Abstract read
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Article in The journal of physical chemistry. C, Nanomaterials and interfaces, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

11 authors.

Filip VukovićInstitute of Applied Physics, TU Wien, Vienna 1040, Austria.ORCID https://orcid.org/0000-0003-3463-651X
Anna NiggasInstitute of Applied Physics, TU Wien, Vienna 1040, Austria.ORCID https://orcid.org/0000-0002-5838-5789
Levin MihlanFaculty of Physics, Bielefeld University, Bielefeld 33501, Germany.
Zhen YaoFaculty of Physics, Bielefeld University, Bielefeld 33501, Germany.ORCID https://orcid.org/0009-0000-4197-6606
Armin GölzhäuserFaculty of Physics, Bielefeld University, Bielefeld 33501, Germany.ORCID https://orcid.org/0000-0002-0838-9028
Louise FrévillePhelma INP Grenbole, Grenoble 38016, France.
Vladislav StroganovInstitute of Physical Chemistry, Friedrich Schiller University Jena, Jena 07743, Germany.
Andrey TurchaninInstitute of Physical Chemistry, Friedrich Schiller University Jena, Jena 07743, Germany.ORCID https://orcid.org/0000-0003-2388-1042
Jürgen SchnackFaculty of Physics, Bielefeld University, Bielefeld 33501, Germany.ORCID https://orcid.org/0000-0003-0702-2723
Nigel A MarksDepartment of Physics, Curtin University, Perth 6845, Australia.
Richard A WilhelmInstitute of Applied Physics, TU Wien, Vienna 1040, Austria.ORCID https://orcid.org/0000-0001-9451-5440

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Carbon nanomembranes (CNMs) are nanometer-thin disordered carbon materials that are suitable for a range of applications, from energy generation and storage through to water filtration. The structure-property relationships of these nanomembranes are challenging to study using traditional experimental characterization techniques, primarily due to the radiation sensitivity of the free-standing membrane. Highly charged ion spectroscopy is a novel characterization method that is able to infer structural details of the carbon nanomembrane without concern about induced damage affecting the measurements. Here we employ molecular dynamics simulations to produce candidate structural models of terphenylthiol-based CNMs with varying degrees of nanoscale porosity and compare predicted ion charge exchange data and tensile moduli to experiment. The results suggest that the in-vacuum CNM composition likely comprises a significant fraction of under-coordinated carbon, with an open subnanometer porous structure. Such a carbon network would be reactive in the atmosphere and would be presumably stabilized by hydrogen and oxygen groups under atmospheric conditions.

Identifiers

PMID41878466
PMCPMC13007017

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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.