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  5. Bio‐Voltage Diffusive Memristor from CVD Grown WSe<sub>2</sub> as Artificial Nociceptor

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Article
English
2024

Bio‐Voltage Diffusive Memristor from CVD Grown WSe<sub>2</sub> as Artificial Nociceptor

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English
2024
Advanced Materials Technologies
DOI: 10.1002/admt.202401048

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Konstantin ‘kostya’  Novoselov
Konstantin ‘kostya’ Novoselov

The University of Manchester

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Renu Yadav
Ramesh Rajarapu
Saroj Poudyal
+4 more

Abstract

Memristors have emerged as a promising candidate to mimic the human behavior and thus unlocking the potential for bio‐inspired computing advancement. However, these devices operate at a voltages which are still far from the energy‐efficient biological counterpart, which uses an action potential of 50–120 mV to process the information. Here, a diffusive memristor is reported from synthetic WSe 2 fabricated in Ag/WSe 2 /Au vertical device geometry. The devices operate at bio‐voltages of 40–80 mV with I on / I off ratio of 10 6 and steep switching turn ON and OFF slopes of 0.77 and 0.88 mV per decade, respectively. The power consumption in standby mode and power per set transition are found to be 10 fW and 64 pW, respectively. Further, the diffusive memristors are utilized to emulate the nociceptor, a special receptor for sensory neurons that selectively responds to noxious stimuli. Nociceptor in turn imparts a warning signal to the central nervous system which then triggers the motor response to take precautionary actions to prevent the body from injury. The key features of a nociceptor including “threshold”, “relaxation”, “no‐adaptation” and “sensitization” are demonstrated using artificial nociceptors. These illustrations imply the feasibility of developing low‐power diffusive memristors for bio‐inspired computing, humanoid robots, and electronic skins.

How to cite this publication

Renu Yadav, Ramesh Rajarapu, Saroj Poudyal, Bubunu Biswal, Prahalad Kanti Barman, Konstantin ‘kostya’ Novoselov, Abhishek Misra (2024). Bio‐Voltage Diffusive Memristor from CVD Grown WSe<sub>2</sub> as Artificial Nociceptor. Advanced Materials Technologies, DOI: 10.1002/admt.202401048.

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Publication Details

Type

Article

Year

2024

Authors

7

Datasets

0

Total Files

0

Language

English

Journal

Advanced Materials Technologies

DOI

10.1002/admt.202401048

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