Evidence map›Paper›PMID 35759664›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2022

Statistical signature of electrobreakdown in graphene nanojunctions.

Charalambos Evangeli, Sumit Tewari, Jonathan Marcell Kruip, Xinya Bian, Jacob L Swett, John Cully, James Thomas, G Andrew D Briggs, Jan A Mol

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

9 authors.

Charalambos EvangeliDepartment of Materials, University of Oxford, Oxford OX1 3PH, United Kingdom.ORCID 0000-0003-3867-8530
Sumit TewariDepartment of Materials, University of Oxford, Oxford OX1 3PH, United Kingdom.ORCID 0000-0002-9229-0038
Jonathan Marcell KruipSchool of Physics and Astronomy, Queen Mary University of London, London E1 4NS, United Kingdom.
Xinya BianDepartment of Materials, University of Oxford, Oxford OX1 3PH, United Kingdom.
Jacob L SwettDepartment of Materials, University of Oxford, Oxford OX1 3PH, United Kingdom.
John CullyDepartment of Materials, University of Oxford, Oxford OX1 3PH, United Kingdom.
James ThomasDepartment of Materials, University of Oxford, Oxford OX1 3PH, United Kingdom.ORCID 0000-0003-1959-1675
G Andrew D BriggsDepartment of Materials, University of Oxford, Oxford OX1 3PH, United Kingdom.ORCID 0000-0003-1950-2097
Jan A MolSchool of Physics and Astronomy, Queen Mary University of London, London E1 4NS, United Kingdom.

Funding

Medical Research Council MR/S032541/1
6 · The paper itself

Abstract

Controlled electrobreakdown of graphene is important for the fabrication of stable nanometer-size tunnel gaps, large-scale graphene quantum dots, and nanoscale resistive switches, etc. However, owing to the complex thermal, electronic, and electrochemical processes at the nanoscale that dictate the rupture of graphene, it is difficult to generate conclusions from individual devices. We describe here a way to explore the statistical signature of the graphene electrobreakdown process. Such analysis tells us that feedback-controlled electrobreakdown of graphene in the air first shows signs of joule heating-induced cleaning followed by rupturing of the graphene lattice that is manifested by the lowering of its conductance. We show that when the conductance of the graphene becomes smaller than around 0.1

Indexed as

electrobreakdowngrapheneresistive switchingstatisticsvacuum

Identifiers

PMID35759664
PMCPMC9271182

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

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.