Nanowire-based synaptic devices for neuromorphic computing

Abstract

The traditional von Neumann structure computers cannot meet the demand of high-speed big data processing, therefore, neuromorphic computing has got a lot of interest in recent years. Brain-inspired neuromorphic computing has the advantages of low power consumption, high-speed and high-accuracy. In human brains, the data transmission and processing are realized through synapses. Artificial synaptic devices can be adopted to mimic the biological synaptic functionalities. Nanowire is an important building block for nanoelectronics and optoelectronics, and many efforts have been made to promote the application of nanowires based synaptic devices for neuromorphic computing. Here, we will introduce the current progress of nanowires based synaptic memristors and synaptic transistors. The applications of nanowires based synaptic devices for neuromorphic computing will be discussed. The challenges faced by nanowires based synaptic devices will be proposed. We hope this perspective will be beneficial for the application of nanowires based synaptic devices in neuromorphic systems.

Thermally Driven Multilevel Non-Volatile Memory with Monolayer MoS2 for Brain-Inspired Artificial Learning

“…Recently, memtransistors (integration of transistors with memristive functionalities) based on novel materials have been proposed with various architectures showing controlled transport with digital switching ratios, , multibit optoelectronic memory, neuromorphic computing applications, etc. − Especially, the electrolyte-gated transistors show better conductance modulation benefited from its ion-gating mechanism over electrostatic charge trap phenomena, making them viable candidates for brain-inspired computation and logic-in-memory applications. , Despite the recent development of synaptic ion-gated transistors, multilevel memory based on ion-gating mechanisms is still lacking. However, liquid electrolytes practically limit the large-density integration of devices and high-temperature applications.…”

Investigating the Role of Interfacial Layer for Resistive Switching in a Hybrid Dion-Jacobson Perovskite-Based Memristor

“…The need to solve this issue inspires the development of alternative ways to store and process the data simultaneously. In recent years, memristor has emerged as one the most promising candidates to support the advanced intelligence system . Different from transistor-based memory elements, a perovskite based memristor has simple two-terminal structure and low-cost fabrication .…”

“…In recent years, memristor has emerged as one the most promising candidates to support the advanced intelligence system. 31 Different from transistor-based memory elements, a perovskite based memristor has simple two-terminal structure and low-cost fabrication. 32 Moreover, a biological synapse also exhibits two terminal structures, and memristors sharing such a structural similarity have been widely used to simulate neuromorphic characteristics.…”

Low-dimensional optoelectronic synaptic devices for neuromorphic vision sensors

“…One-dimensional materials, such as NWs and nanorods, exhibit unique characteristics including high aspect ratio, large surface area volume ratio, and sub-wavelength size effects, which enable carriers to move freely on a single nanometer scale. The 1D structure results in high carrier mobility, high photoelectric conversion efficiency, and adjustable optical absorption coefficients [165][166][167][168], allowing for a wide spectrum of detection capabilities from ultraviolet to infrared waves. The simple and low-cost preparation process of semiconductor NWs, such as the vapor-liquid-solid (VLS), enables the transfer of NWs to any substrate or material to form flexible devices or heterostructures.…”