ArticleScientific reports2022
Artificial fast-adapting mechanoreceptor based on carbon nanotube percolating network.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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Who cites it
2 citing papers in PubMed, 5 citations in OpenAlex.
- System-Level Design and Integration of Dexterous Robotic Hands for Complex Manipulation.Research (Washington, D.C.) · 2026Review
- Bio-Inspired Robots and Structures toward Fostering the Modernization of Agriculture.Biomimetics (Basel, Switzerland) · 2022Review
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Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
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Abstract
Most biological sensors preferentially encode changes in a stimulus rather than the steady components. However, intrinsically phasic artificial mechanoreceptors have not yet been described. We constructed a phasic mechanoreceptor by encapsulating carbon nanotube film in a viscoelastic matrix supported by a rigid substrate. When stimulated by a spherical indenter the sensor response resembled the response of fast-adapting mammalian mechanoreceptors. We modelled these sensors from the properties of percolating conductive networks combined with nonlinear contact mechanics and discussed the implications of this finding.
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