Low-Dimensional Layered Light-Sensitive Memristive Structures for Energy-Efficient Machine Vision

Gennady N Panin

doi:10.3390/electronics11040619

Abstract

Layered two-dimensional (2D) and quasi-zero-dimensional (0D) materials effectively absorb radiation in the wide ultraviolet, visible, infrared, and terahertz ranges. Photomemristive structures made of such low-dimensional materials are of great interest for creating optoelectronic platforms for energy-efficient storage and processing of data and optical signals in real time. Here, photosensor and memristor structures based on graphene, graphene oxide, bismuth oxyselenide, and transition metal dichalcogenides are reviewed from the point of view of application in broadband image recognition in artificial intelligence systems for autonomous unmanned vehicles, as well as the compatibility of the formation of layered neuromorphic structures with CMOS technology.

Highlights

IntroductionInrecent recentyears, years, there therehas hasbeen beenan anincreased increased interest interest in in the the creation creation of of optoelectronic optoelectronicIn devices based on photomemristors capable of energy-saving storage and processing of of devices based on photomemristors capable of energy-saving storage and processing signals, such as neurons [1].The need to improve the signals, neurons and andsynapses synapsesininbiological biologicalsystems systemsThe need to improve speed andand energy efficiency of big data processing is especially acute in in systems such as the speed energy efficiency of big data processing is especially acute systems such as artificial intelligence (AI)in autopilot autonomous unmanned vehicles.In 2021, artificial intelligence in autopilot andand autonomous unmanned vehicles
Low-dimensional layered (LDL) photosensitive memristive materials and structures offer good scalability, and the potential for photodetection and in-memory computing is seen as a promising candidate for next-generation broadband complementary metal-oxide semiconductor (CMOS)-compatible imagerecognition devices for AI applications in autonomous unmanned vehicles
Photomemristor and photosensor structures based on two-dimensional crystals and van der Waals heterostructures are a new class of optoelectronic components for autonomous energysaving neuromorphic visual information processing systems

Summary

Introduction

Years, there therehas hasbeen beenan anincreased increased interest interest in in the the creation creation of of optoelectronic optoelectronic. Memristor structures made the development of a fundamentally new element base of effectively sensor and computing devices of photosensitive low-dimensional layered materials [13,14,15,16], which absorb radiation in the ultraviolet, visible, and infrared ranges [17,18,19], cantime. Memristor structures made tronic platform embedded in CMOS technology for materials fast and energy-efficient neuromorof photosensitive low-dimensional layered [13,14,15,16], which effectively absorb phic processing an optical signal and pattern recognition. The memristor, polarized at different voltages, shows eight different states the fast optical access make it possible to detect and quickly process signals in the memory.

Current–voltage

Schematic photomemristor matrix on aon

Photosensitive 2D Crystals and Their Embedding in CMOS Technology

Layered Quantum Dots

QDs are tous channel from phase

Conclusions and Perspectives