%AZhuo, Ye [Department of Electrical and Computer Engineering University of Southern California Los Angeles CA 90089 USA]%AMidya, Rivu [Department of Electrical and Computer Engineering University of Massachusetts Amherst MA 01003 USA]%ASong, Wenhao [Department of Electrical and Computer Engineering University of Southern California Los Angeles CA 90089 USA]%AWang, Zhongrui [Department of Electrical and Computer Engineering Texas A&,M University College Station TX 77843 USA]%AAsapu, Shiva [Department of Electrical and Computer Engineering University of Massachusetts Amherst MA 01003 USA]%ARao, Mingyi [Department of Electrical and Computer Engineering University of Massachusetts Amherst MA 01003 USA]%ALin, Peng [Department of Electrical and Computer Engineering University of Massachusetts Amherst MA 01003 USA]%AJiang, Hao [Department of Electrical and Computer Engineering University of Massachusetts Amherst MA 01003 USA]%AXia, Qiangfei [Department of Electrical and Computer Engineering University of Massachusetts Amherst MA 01003 USA]%AWilliams, R. [Department of Electrical and Computer Engineering Texas A&,M University College Station TX 77843 USA]%AYang, J. [Department of Electrical and Computer Engineering University of Southern California Los Angeles CA 90089 USA, Department of Electrical and Computer Engineering University of Massachusetts Amherst MA 01003 USA]%BJournal Name: Advanced Electronic Materials; Journal Volume: 8; Journal Issue: 8; Related Information: CHORUS Timestamp: 2023-08-23 12:10:35 %D2021%IWiley Blackwell (John Wiley & Sons) %JJournal Name: Advanced Electronic Materials; Journal Volume: 8; Journal Issue: 8; Related Information: CHORUS Timestamp: 2023-08-23 12:10:35 %K %MOSTI ID: 10370008 %PMedium: X %TA Dynamical Compact Model of Diffusive and Drift Memristors for Neuromorphic Computing %XAbstract

Different from nonvolatile memory applications, neuromorphic computing applications utilize not only the static conductance states but also the switching dynamics for computing, which calls for compact dynamical models of memristive devices. In this work, a generalized model to simulate diffusive and drift memristors with the same set of equations is presented, which have been used to reproduce experimental results faithfully. The diffusive memristor is chosen as the basis for the generalized model because it possesses complex dynamical properties that are difficult to model efficiently. A data set from statistical measurements on SiO2:Ag diffusive memristors is collected to verify the validity of the general model. As an application example, spike‐timing‐dependent plasticity is demonstrated with an artificial synapse consisting of a diffusive memristor and a drift memristor, both modeled with this comprehensive compact model.

%0Journal Article