The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.
Fluid-driven origami-inspired artificial muscles
Open accessAbstract
Significance: Artificial muscles are flexible actuators with capabilities similar to, or even beyond, natural muscles. They have been widely used in many applications as alternatives to more traditional rigid electromagnetic motors. Numerous studies focus on rapid design and low-cost fabrication of artificial muscles with customized performances. Here, we present an architecture for fluidic artificial muscles with unprecedented performance-to-cost ratio. These artificial muscles can be programed to produce not only a single contraction but also complex multiaxial actuation, and even controllable motion with multiple degrees of freedom. Moreover, a wide variety of materials and fabrication processes can be used to build the artificial muscles with other functions beyond basic actuation.
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Cites
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Cited by
Whitesides, G. M. (2018) · Angewandte Chemie International Edition · doi:10.1002/anie.201800907 · Cited by 850
Design, fabrication and control of origami robots
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Self-citationA Review on Origami Simulations: From Kinematics, To Mechanics, Toward Multiphysics
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Programmable soft robotics based on nano-textured thermo-responsive actuators
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Metadata
- Authors
- Li, S., Vogt, D. M., Rus, D., & Wood, R. J.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2017-11-27
- Volume
- 114
- Issue
- 50
- Pages
- 13132-13137
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2769501833
- Cited by
- 747
- References
- 46
- FWCI
- 44.09
- Type
- journal article
- Language
- en
- Open access
- hybrid
- Funders
- DOD | Defense Advanced Research Projects Agency (FA8650-15-C-7548)
- National Science Foundation (IIS-1226075)
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- Li, S., Vogt, D. M., Rus, D., & Wood, R. J. (2017). Fluid-driven origami-inspired artificial muscles. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1713450114
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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