Stress-induced Artificial neuron spiking in Diffusive memristors

TL;DR

This paper demonstrates a flexible diffusive memristor that exhibits controllable spiking behavior induced by mechanical impact, enabling touch-perception sensors for neural network applications.

Contribution

It introduces a mechanically responsive diffusive memristor on PET substrate with tunable spiking, and proposes a mathematical model for its operation.

Findings

Mechanical impact modulates memristor spiking behavior.

Spiking response can be controlled by impact magnitude and frequency.

The device functions as a touch-perception sensor for neural networks.

Abstract

Diffusive memristors owing to their ability to produce current spiking when a constant or slowly changing voltage is applied are competitive candidates for the development of artificial electronic neurons. These artificial neurons can be integrated into various prospective autonomous and robotic systems as sensors, e.g. ones implementing object grasping and classification. We report here Ag nanoparticle-based diffusive memristor prepared on a flexible polyethylene terephthalate (PET) substrate in which the electric spiking behaviour was induced by the electric voltage under an additional stimulus of external mechanical impact. By changing the magnitude and frequency of the mechanical impact, we are able to manipulate the spiking response of our artificial neuron. This functionality to control the spiking characterstics paves a pathway for the development of touch-perception sensors that can convert local pressure into electrical spikes for further processing in neural networks. We have proposed a mathematical model which captures the operation principle of the fabricated memristive sensors and qualitatively describes the measured spiking behaviour.