Multifunctional Ag–In–Zn–S/Cs<sub>3</sub>Cu<sub>2</sub>Cl<sub>5</sub>‐Based Memristors with Coexistence of Non‐Volatile Memory and Volatile Threshold Switching Behaviors for Neuroinspired Computing
Nan He, Fan Ye, Jun Liu, Tianlong Sun, Xinpeng Wang, Wenjie Hou, Weijing Shao, Xiang Wan, Yi Tong, Feng Xu, Yang Sheng
Abstract
Abstract Lead‐free all‐inorganic Cs 3 Cu 2 Cl 5 perovskites, a member of the metal‐metal halide material family, have attracted pronounced attention owing to their low toxicity, facile fabrication strategies, considerable ambient stability, and intriguing photoelectric properties. However, the application of environmentally friendly copper‐based Cs 3 Cu 2 Cl 5 in memristors has been rarely reported to the authors’ knowledge. Herein, multifunctional memristors with the coexistence of non‐volatile memory (MS) and volatile threshold switching (TS) behaviors are introduced based on an innovative Ag–In–Zn–S/Cs 3 Cu 2 Cl 5 heterostructure. The inserted Ag–In–Zn–S quantum dots layer may provide an effective method for guiding the formation of the dominant metallic Ag filaments, resulting in considerably stable and controllable multiple switching behaviors. Additionally, the heterostructure memristor is capable of imitating some essential biological synaptic functions, including long‐term potentiation (LTP), long‐term depression (LTD), and the short‐term memory (STM) to long‐term memory (LTM) transition. Furthermore, the famous conditioning Pavlov's dog experiment corresponding to associative learning is electronically simulated by the studied device. Moreover, utilizing the devices’ LTP and LTD properties, relatively high recognition accuracies for small and large digits datasets are achieved through a three‐layer artificial neural network, revealing the feasibility of implementing neuromorphic computation using heterostructure memristors.