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Toughness and strength of nanocrystalline graphene

Authors: Shekhawat, Ashivni; Ritchie, Robert O;

Toughness and strength of nanocrystalline graphene

Abstract

AbstractPristine monocrystalline graphene is claimed to be the strongest material known with remarkable mechanical and electrical properties. However, graphene made with scalable fabrication techniques is polycrystalline and contains inherent nanoscale line and point defects—grain boundaries and grain-boundary triple junctions—that lead to significant statistical fluctuations in toughness and strength. These fluctuations become particularly pronounced for nanocrystalline graphene where the density of defects is high. Here we use large-scale simulation and continuum modelling to show that the statistical variation in toughness and strength can be understood with ‘weakest-link’ statistics. We develop the first statistical theory of toughness in polycrystalline graphene, and elucidate the nanoscale origins of the grain-size dependence of its strength and toughness. Our results should lead to more reliable graphene device design, and provide a framework to interpret experimental results in a broad class of two-dimensional materials.

Country
United States
Keywords

Condensed Matter - Materials Science, Science, 51 Physical Sciences (for-2020), 5104 Condensed Matter Physics (for-2020), Q, Materials Science (cond-mat.mtrl-sci), FOS: Physical sciences, Materials Engineering, Condensed Matter Physics, 40 Engineering (for-2020), 530, Article, 620, 4016 Materials Engineering (for-2020), Engineering, Physical Sciences

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    200
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
200
Top 1%
Top 10%
Top 1%
Green
gold