The DOI matches its Crossref record.
Symmetry-, time-, and temperature-dependent strength of carbon nanotubes
Open accessAbstract
Although the strength of carbon nanotubes has been of great interest, their ideal value has remained elusive both experimentally and theoretically. Here, we present a comprehensive analysis of underlying atomic mechanisms and evaluate the yield strain for arbitrary nanotubes at realistic conditions. For this purpose, we combine detailed quantum mechanical computations of failure nucleation and transition-state barriers with the probabilistic approach of the rate theory. The numerical results are then summarized in a concise set of equations for the breaking strain. We reveal a competition between two alternative routes of brittle bond breaking and plastic relaxation, determine the domains of their dominance, and map the nanotube strength as a function of chiral symmetry, tensile test time, and temperature.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Georgakilas, V., Perman, J. A., Tucek, J., & Zboril, R. (2015) · Chemical Reviews · doi:10.1021/cr500304f · Cited by 2,147
Ab initio calculation of ideal strength and phonon instability of graphene under tension
Liu, F., Ming, P., & Li, J. (2007) · Physical Review B · doi:10.1103/physrevb.76.064120 · Cited by 1,447
Carbyne from First Principles: Chain of C Atoms, a Nanorod or a Nanorope
Liu, M., Artyukhov, V. I., Lee, H., Xu, F., & Yakobson, B. I. (2013) · ACS Nano · doi:10.1021/nn404177r · Cited by 451
Self-citationFullerene Nanocage Capacity for Hydrogen Storage
Pupysheva, O. V., Farajian, A. A., & Yakobson, B. I. (2008) · Nano Letters · doi:10.1021/nl071436g · Cited by 272
Self-citation
Metadata
- Authors
- Dumitrica, T., Hua, M., & Yakobson, B. I.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2006-04-18
- Volume
- 103
- Issue
- 16
- Pages
- 6105-6109
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2160852466
- Cited by
- 255
- References
- 0
- FWCI
- 14.76
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Symmetry-, time-, and temperature-dependent strength of carbon nanotubes. https://app.cochat.ai/papers/10.1073/pnas.0600945103
- The paper
- Dumitrica, T., Hua, M., & Yakobson, B. I. (2006). Symmetry-, time-, and temperature-dependent strength of carbon nanotubes. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.0600945103
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.