Volatile threshold switching memristor: An emerging enabler in the AIoT era

Abstract

With rapid advancement and deep integration of artificial intelligence and the internet-of-things, artificial intelligence of things has emerged as a promising technology changing people’s daily life. Massive growth of data generated from the devices challenges the AIoT systems from information collection, storage, processing and communication. In the review, we introduce volatile threshold switching memristors, which can be roughly classified into three types: metallic conductive filament-based TS devices, amorphous chalcogenide-based ovonic threshold switching devices, and metal-insulator transition based TS devices. They play important roles in high-density storage, energy efficient computing and hardware security for AIoT systems. Firstly, a brief introduction is exhibited to describe the categories (materials and characteristics) of volatile TS devices. And then, switching mechanisms of the three types of TS devices are discussed and systematically summarized. After that, attention is focused on the applications in 3D cross-point memory technology with high storage-density, efficient neuromorphic computing, hardware security (true random number generators and physical unclonable functions), and others (steep subthreshold slope transistor, logic devices, etc.). Finally, the major challenges and future outlook of volatile threshold switching memristors are presented.

AgBiS2 quantum dot based multilevel resistive switching for low power electronics

“…4,45,53 The device's volatile nature can also be leveraged in volatile memristor-based applications, such as enabling information gathering, storage, processing, neuromorphic computing and communication in Artificial Intelligence of Things (AIoT) systems. 54…”

Threshold Switching Memristor Based on 2D SnSe for Nociceptive and Leaky-Integrate and Fire Neuron Simulation

“…20 The threshold voltage (V th ) signifies the critical point at which an abrupt change in the device's resistance occurs (SET process), resulting from the formation of conductive paths. 21 This phenomenon is analogous to the threshold of membrane potential in biological neurons. 22 This capability renders TS memristors significantly important in the construction of neuromorphic hardware, paving the way for advancements in neuromorphic computing systems.…”

“…A diverse range of CF-based TS memristors have been proposed to effectively emulate the LIF behavior of neurons . The threshold voltage ( V th ) signifies the critical point at which an abrupt change in the device’s resistance occurs (SET process), resulting from the formation of conductive paths . This phenomenon is analogous to the threshold of membrane potential in biological neurons .…”

Indium turns tellurium into an ovonic threshold switching selector via a stabilizing amorphous network

“…6–8 Based on their switching mechanisms, TS devices can be categorized into three types: chalcogenide-based ovonic threshold switching (OTS), metal-insulator transition (MIT), and conductive bridge threshold switching (CBTS). 9–13 Among these, OTS selectors have gained commercial attraction, finding application in various systems such as 3D XPoint. 14…”