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Cited by 296

The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.

Nonlinear conduction via solitons in a topological mechanical insulator

Open access
Chen, Bryan Gin-ge, Upadhyaya, Nitin, Vitelli, Vincenzo·2014·Proceedings of the National Academy of Sciences

Abstract

Significance: Mechanisms are zero-energy motions that are key to the operation of mechanical devices, from windshield wipers to robotic arms. We built and studied chain-like mechanisms of coupled rigid rotors that are topologically protected, which means that they are not affected by smooth changes in material parameters like their quantum analogues. These prototypes are examples of mechanical structures that we dub topological metamaterials. Their mechanical excitations are nonlinear solitary waves which are topologically protected and yet tunable by changing the geometry of the unit cell. Although the left and right edges of the sample are equivalent in terms of local constraint counting, the solitary waves can start propagating only from the edge singled out by the topological polarization of the chain.

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Metadata

Authors
Chen, B. G.-G., Upadhyaya, N., & Vitelli, V.
Venue
Proceedings of the National Academy of Sciences
Published
2014-08-25
Volume
111
Issue
36
Pages
13004-13009
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2004279045
Cited by
296
References
17
FWCI
10.98
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Nonlinear conduction via solitons in a topological mechanical insulator. https://app.cochat.ai/papers/10.1073/pnas.1405969111
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Chen, B. G.-G., Upadhyaya, N., & Vitelli, V. (2014). Nonlinear conduction via solitons in a topological mechanical insulator. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1405969111

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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.