Stretchable hierarchical metal wire networks for neuromorphic emulation of nociception and anti-nociception

Among biomimetic technologies, the incorporation of sensory hardware holds exceptional utility in human-machine interfacing. In this context, devices receptive to nociception and emulating antinociception gain significance as part of pain management. Here we report, a stretchable two-terminal resistive neuromorphic device consisting of a hierarchical Ag microwire network formed using a crack templating protocol. The device demonstrates sensitivity to strain, where the application of strain induces the formation of gaps across active elements, rendering the device electrically open. Following activation by voltage pulses, the device exhibits potentiated states with finite retentions arising from filamentary growth across these gaps due to field migration. Remarkably, the strain-induced functioning alongside controllable gaps enables achieving user-controlled neuromorphic properties, desired for self-adaptive intelligent systems. Interestingly, in the neuromorphic potentiated state, the response to strain is enhanced by ∼10<sup>6</sup> due to higher sensitivities associated with nanofilaments. The device emulates basic neuromorphic functionalities such as threshold switching, and short-term (STP) and long-term potentiations (LTP). Furthermore, the sensitivity has been exploited in mimicking nociception through strain-induced changes in the potentiated state. Interestingly, repetition of the strain stimulus leads to endurance making the device restore its conductance, thereby emulating adaptation and habituation representing the antinociceptive behavior.

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Publication Details

Journal
Materials Horizons
Published
2024-10-24
DOI
https://doi.org/10.1039/d4mh01208a
Citations
3
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
1.03

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article

Stretchable hierarchical metal wire networks for neuromorphic emulation of nociception and anti-nociception

Indrajit Mondal, N. S. Vidhyadhiraja, Bhupesh Yadav, Giridhar U. Kulkarni et al.
3 citations
Materials Horizons
EEG and Brain-Computer Interfaces
1.03
article

Stretchable hierarchical metal wire networks for neuromorphic emulation of nociception and anti-nociception

Indrajit Mondal, N. S. Vidhyadhiraja, Bhupesh Yadav, Giridhar U. Kulkarni, Manpreet Kaur
article en
3 citations

Abstract

Among biomimetic technologies, the incorporation of sensory hardware holds exceptional utility in human-machine interfacing. In this context, devices receptive to nociception and emulating antinociception gain significance as part of pain management. Here we report, a stretchable two-terminal resistive neuromorphic device consisting of a hierarchical Ag microwire network formed using a crack templating protocol. The device demonstrates sensitivity to strain, where the application of strain induces the formation of gaps across active elements, rendering the device electrically open. Following activation by voltage pulses, the device exhibits potentiated states with finite retentions arising from filamentary growth across these gaps due to field migration. Remarkably, the strain-induced functioning alongside controllable gaps enables achieving user-controlled neuromorphic properties, desired for self-adaptive intelligent systems. Interestingly, in the neuromorphic potentiated state, the response to strain is enhanced by ∼10<sup>6</sup> due to higher sensitivities associated with nanofilaments. The device emulates basic neuromorphic functionalities such as threshold switching, and short-term (STP) and long-term potentiations (LTP). Furthermore, the sensitivity has been exploited in mimicking nociception through strain-induced changes in the potentiated state. Interestingly, repetition of the strain stimulus leads to endurance making the device restore its conductance, thereby emulating adaptation and habituation representing the antinociceptive behavior.

Materials HorizonsVol. 12(2)
Jawaharlal Nehru Centre for Advanced Scientific Research (IN)
Department of Science and Technology, Ministry of Science and Technology, India, Council of Scientific and Industrial Research, India, Science and Engineering Research Board
Openalex Percentile: Top 24%
EEG and Brain-Computer Interfaces
1.03
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