Resistive Switching Properties in Memristors for Optoelectronic Synaptic Memristors: Deposition Techniques, Key Performance Parameters, and Applications

Abstract

Due to the fast evolution of information technology, high-speed and scalable memory devices are being investigated for data storage and datadriven computation. Resistive switching random access memory (RRAM) is one of the very popular types of memristors, because of its quick program/erase speed and high density as a result of its simple two-terminal structure, low power consumption, and low cost of fabrication. In this review, the market for promising memristor-based memories for smart systems is examined. The switching memory devices are described and classified according to their I−V behavior to underline the physical switching mechanisms. The various filament mechanisms of the RRAM memristor, including the valence change mechanism (VCM), electrochemical metallization mechanism (ECM), and thermochemical mechanism (TCM), are especially highlighted in various structures. The performance of resistive switching devices with different reported electrode materials and resistive layers is summarized. This study provides a detailed review of materials of the different deposition techniques used for surface modification and coating. The two major areas of interest, physical and chemical vapor deposition techniques and the influence parameter on the resistive switching, are discussed in detail. The prospective applications of RRAM memristors to various fields such as security, neuromorphic computing, and non-volatile logic systems for artificial intelligence are addressed briefly as well as the future outlook.

An organized view of reservoir computing: a perspective on theory and technology development

“…There are, however, many successful constructs mimicking neutrons and synapses, and processes like sensory integration and nociception. [47][48][49][50][51][52][53][54][55] Physical neuromorphic computing is slowly coming into reality. 56,57) Furthermore, RC seems to be a perfect tool to understand the relation between the connectome (the connectivity map between all neurons in the nervous system) and the cognitive abilities of the neural system.…”