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. 2022 Mar 9;12(1):2818.
doi: 10.1038/s41598-021-04483-2.

Artificial fast-adapting mechanoreceptor based on carbon nanotube percolating network

Cyril Bounakoff  1 , Vincent Hayward  2 , Jonathan Genest  3 , François Michaud  3 , Jacques Beauvais  4
Affiliations

Artificial fast-adapting mechanoreceptor based on carbon nanotube percolating network

Cyril Bounakoff et al. Sci Rep. .

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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Conflict of interest statement

A patent related to the sensors described in this paper has been submitted by the Université de Sherbrooke.

Figures

Figure 1
Figure 1
Sensor cell test by a spherical probe. (a) Sensor structure. (b) Testing sequence. (c) Resulting load. (d) Relative change of resistance ΔR=(R-R0)/R0. (e) Repeated tests and responses.
Figure 2
Figure 2
Sensor response. (a) Dependence of the response on deflection magnitude. Lines with grey levels indicate different deflections. (b) Dependence of the response on deflection rate. Lines with grey levels indicate different rates.
Figure 3
Figure 3
Large displacement analysis. (a) Rate dependent hysteresis. (b) Non-monotonic relationship between load-rate and deflection. (c) Relationship between the variation of resistance and deflection. The red line shows the prediction of the model (1). (d) Relationship between the rate of change of resistance and the deflection. The red line shows the prediction of the model (2).
Figure 4
Figure 4
Finite element simulation. (a) The top sequence shows the result of the simulation of the progressive indentation by a cylindrical probe in the sensor cell. Arrows show direction and magnitude of principal strain. Beyond 0.4 mm of deflection, the behaviour departed from a Hertzian model as indicated by the pressure profile. The bottom sequence shows the unloading phase after a five-second plateau at fixed indentation. (b) Axial and transverse strain profiles along the MWCNT film during the loading phase.
Figure 5
Figure 5
Qualitative model. (a) The interplay of two piezoresistive phenomena explains the sensitivity curve reversal. (b) Option for a practical e-Skin implementation.
Figure 6
Figure 6
Fabrication. (a) PDMS plus Triton X, with deposited MWCNT film. (b) Conductive polymer patterned electrode. (c) Encapsulation. (d) Interconnection with printed circuits. (e) Scanning Electron Microscopy image of MWCNT film (Scan time 50μs, 7.5μm Field-of-view).
See this image and copyright information in PMC

References

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