Memristive synapse based on perovskite Cs3Cu2I5 for reservoir computing
Abstract
Perovskite memristors have attracted considerable attention for their potential in emulating artificial synapses. However, the widespread use of the toxic lead-based perovskites poses significant challenges to futural application. In this work, we developed a lead-free memristor with an Ag/PMMA/Cs3Cu2I5/ITO architecture, in which the Cs3Cu2I5 halide perovskites functional layer was fabricated by physical vapor deposition. The memristor demonstrated a data retention time of 104 s and stable resistive switching behavior over 100 cycles under electrical pulses stimulation. Furthermore, it emulated a range of biologically relevant synaptic functions, including paired-pulse facilitation, short-term plasticity, long-term plasticity, spike-amplitude-dependent plasticity, spike-number-dependent plasticity, and spike-duration-dependent plasticity. Capitalizing on its nonlinear dynamics and short-term memory characteristics, the device was further integrated into a reservoir computing (RC) system. The RC system demonstrated strong recognition performance and robustness when tested with distorted digital image datasets. These results suggest that the Cs3Cu2I5-based memristor provides a promising, environmentally friendly platform for next-generation artificial intelligence hardware.
Article Details
Journal Info
Applied Physics Letters
American Institute of Physics
Authors (7)
Bin Li
Yao Meng
Center for Systems and Control
Zheng Yin
Jinwen Lin
Guangdong Engineering Research Center of School of Electronic Science and Engineering (School of Microelectronics), South China Normal University 2 , Foshan 528225,
Jiang Wu
Hong Zhou
Shanghai Collaborative Innovation Center of Agri-Seeds, School of Agriculture and Biology, Shanghai Jiao Tong University
Xinman Chen
Guangdong Engineering Research Center of School of Electronic Science and Engineering (School of Microelectronics), South China Normal University 2 , Foshan 528225,