Research Progress of Biomimetic Memristor Flexible Synapse

Abstract

With the development of the Internet of things, artificial intelligence, and wearable devices, massive amounts of data are generated and need to be processed. High standards are required to store and analyze this information. In the face of the explosive growth of information, the memory used in data storage and processing faces great challenges. Among many types of memories, memristors have received extensive attentions due to their low energy consumption, strong tolerance, simple structure, and strong miniaturization. However, they still face many problems, especially in the application of artificial bionic synapses, which call for higher requirements in the mechanical properties of the device. The progress of integrated circuit and micro-processing manufacturing technology has greatly promoted development of the flexible memristor. The use of a flexible memristor to simulate nerve synapses will provide new methods for neural network computing and bionic sensing systems. In this paper, the materials and structure of the flexible memristor are summarized and discussed, and the latest configuration and new materials are described. In addition, this paper will focus on its application in artificial bionic synapses and discuss the challenges and development direction of flexible memristors from this perspective.

Performance Evaluation of Low Power Hybrid Combinational Circuits using Memristor

“…The resistance recorded in the used memristors represents the logic state in the MAGIC implementation, where ROFF and RON represent logic "0" and "1," respectively. In [24,25] MAGIC NOR is employed as a foundation for performing logic computations inside the memory, hence increasing processing capabilities. To put it another way, each processing work is broken down into a series of MAGIC NOR operations that are carried out one after the other, employing memory cells as computation elements.…”

Compact SPICE Model of Memristor with Barrier Modulated Considering Short- and Long-Term Memory Characteristics by IGZO Oxygen Content

“…Memristor can be a building block in neuromorphic systems by controlling conductance [ 7 , 8 , 9 , 10 , 11 , 12 , 13 ]. Various resistive switching behaviors are observed in a lot of materials, such as oxides, nitrides and other materials [ 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 ]. Among them, the indium gallium zinc oxide (IGZO)-based memristor is very promising for memory applications because of its interface-type switching and good compatibility with conventional Si processing [ 14 , 15 , 16 , 17 , 18 , 19 ].…”

“…In previous studies, IGZO-based memristors have shown good synaptic properties for neuromorphic systems and memory applications [ 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 ]. Similarly to other oxide memristors, when Ag is used as the top electrode (TE) in IGZO-based memristors, Ag plays a dominant role in switching through the formation of the Ag filament [ 22 , 23 , 24 ].…”

CuI: An Attractive Material for Constructing Transparent and Metal-electrode-free Optoelectronic Synapse

“…Artificial synapse is the basis to construct artificial neural morphological networks at the physical level, which is one of the promising ways to overcome the existing von Neumann bottleneck and attracts more and more research efforts. − Until now, a lot of artificial synapses with different structures and working principles have been reported, such as ferroelectric devices, − phase change memory, , and field-effect transistors (FETs). − Most of bio-synaptic functionalities, like short-term plasticity (STP) and long-term potentiation/depression (LTP/LTD), have been successfully simulated by these devices. − …”