A High‐Performance Memristor Device and Its Filter Circuit Application
Chao Gao, Hong Wang, Zhiping Zhu, Lei Zhang, Yongqiang Yang, Gang Cao, Xiaobing Yan
Abstract
With the onset of the era of big data, memristors have been extensively studied for applications in nonvolatile neuromorphic computing due to their fast switching speed and low switching power ability and the complementary metal–oxide–semiconductor (CMOS) compatibility. In particular, their adjustable cutoff frequency for filtering applications is a significant advantage. However, for circuit applications, memristors are still in their early simulated stage. Herein, Ag/HfO 2 /graphene oxide quantum dot (GOQD)/Pt structure memristor devices are fabricated, where GOQDs are used as a stability boost, with biosynapse simulation achieved and numerical recognition performed at an accuracy of 90.91%. A circuit‐based filter is designed based on the memristor and STM32 microcontroller chip controlling, in which low‐pass, high‐pass, and band‐pass filter circuits are all realized. By changing the output signal of the control circuit of the resistance value of the memristor, the cutoff frequency of the filter is successfully adjusted. This work, therefore, paves a new way to obtain filter circuit applications of memristors for electronic systems; the overall performance of the GOQD‐inserted memristor is further optimized and its function in filtering realized, creating opportunities for further application of the memristor in information processing.