Parylene Based Memristive Devices with Multilevel Resistive Switching for Neuromorphic Applications

Abstract

In this paper, the resistive switching and neuromorphic behaviour of memristive devices based on parylene, a polymer both low-cost and safe for the human body, is comprehensively studied. The Metal/Parylene/ITO sandwich structures were prepared by means of the standard gas phase surface polymerization method with different top active metal electrodes (Ag, Al, Cu or Ti of ~500 nm thickness). These organic memristive devices exhibit excellent performance: low switching voltage (down to 1 V), large OFF/ON resistance ratio (up to 10 4 ), retention (≥10 4 s) and high multilevel resistance switching (at least 16 stable resistive states in the case of Cu electrodes). We have experimentally shown that parylene-based memristive elements can be trained by a biologically inspired spike-timing-dependent plasticity (STDP) mechanism. The obtained results have been used to implement a simple neuromorphic network model of classical conditioning. The described advantages allow considering parylene-based organic memristors as prospective devices for hardware realization of spiking artificial neuron networks capable of supervised and unsupervised learning and suitable for biomedical applications.

Spatial Properties of STDP in a Self-Learning Spiking Neural Network Enable Controlling a Mobile Robot

“…Upon reaching the technology maturity, arrays of memristive synapses offer unique scalability being integrated with CMOS layers and showing spatiotemporal functions , as well as combined with artificial memristive neurons (Wang Z. et al, 2018) within a single network. Simple spiking architectures of Pavlov's dog association have been proposed on memristors (Ziegler et al, 2012;Milo et al, 2017;Tan et al, 2017;Minnekhanov et al, 2019). However, more sophisticated architectures are required to reproduce different types of associative learning to be adopted in advanced robotic systems.…”

Sputtering-deposited amorphous SrVOx-based memristor for use in neuromorphic computing

“…Various materials have been proposed for the active layer, such as binary oxides [21][22][23] , perovskite materials [24][25][26][27][28] , and organic materials 29,30 , and these materials exhibit different types of resistive switching mechanism under certain conditions. For instance, Pt/TiO 2 /Pt devices have been found to exhibit unipolar resistive switching behavior 31 , but modulation of the polarity of the electroforming in Pt/TiO 2 /Pt leads to bipolar reset 32 .…”

Мемристоры на основе поли-n-ксилилена с внедренными наночастицами серебра

“…Одним из перспективных органических материалов для создания мемристоров является поли-n-ксилилен (PPX) [13]. Мемристоры на основе PPX имеют высокое значение отношения R o f f /R on , большие времена хранения резистивных состояний, многоуровневый характер РП [14]. Однако количество циклов переключения для таких структур остается низким, а разброс напряжений переключения может достигать больших величин (десятки процентов) [11].…”