Multiple Switching Modes of NiO_x Memristors for Memory-Driven Multifunctional Device Applications

Abstract

Multiple building components with a variety of switching capabilities are required to implement memory-driven parallel computing architecture and multifunctional device applications. In this regard, there is a high demand for implementing multiple switching modes based on only one active material in a simple device form. In this study, we demonstrated the ability of a solution-processable two-terminal Ag (or Al)/NiO x /ITO memristor that exhibits triple-switching characteristics depending on the different voltage regimes. Notably, the device exhibits an analog bipolar switching behavior under a low programming voltage (≤1.0 V), enabling essential synaptic functions, as well as a high recognition accuracy of 87.42% in a single-layer neural network. After the electroforming process to form the oxygen vacancy-based conductive filament in the NiO x layer, the device concurrently exhibited digital bipolar switching and unipolar threshold switching behaviors at different voltage regimes without compliance current. These three switching characteristics are related to the transition of dominant switching mechanisms depending on the operating scheme, which is investigated using various material and chemical characterization techniques during switching, including cross-sectional scanning transmission electron microscopy, atomic force microscopy, ultraviolet photoelectron spectroscopy, and X-ray photoelectron spectroscopy.

Enhancing memristor fundamentals through instrumental characterization and understanding reliability issues

“…Transmission electron microscopy (TEM) is widely employed to obtain plan-view or cross-sectional images, featuring highresolution microstructures, crystallographic information, and chemical elemental mapping often together with EDX. [32][33][34][35][36][37][38][39] In addition, a wide range of in situ investigation capabilities are available in vacuum or environmental conditions, from which time-resolved evolution of materials structure and response to the stimuli such as temperature and bias can be recorded. [40][41][42] Therefore, as a characterization approach to identifying materials and device behaviors for memristors, TEM is highly beneficial in not only ex situ structure analysis but also in visualizing the dynamic evolution of filaments in situ.…”

“…Park et al reported such an investigation on NiO x -based memristors. 39 XPS analyses were carried out for the four following cases: (i) non-cleaned NiO x , (ii) cleaned (by ion beam) NiO x , (iii) NiO x at LRS, and (iv) NiO x at HRS. Fig.…”

“…Hence, the fundamental study on memristor at single device level remains of paramount importance. If researchers do not have access to crossbar fabrication, or prefer to work on optimizing performance at single device level, one can simulate the image processing performance like recognizing handwriting numbers for a single device level of memristor study by using an in-house software or simulator such as CrossSim 39,[128][129][130][131][132][133].…”

Bio-inspired Artificial synapse for neuromorphic computing based on NiO nanoparticle thin film

“…The binary oxide NiO-based thin film devices have been studied extensively for resistance switching. A detailed model for the conduction mechanism in the RRAM cells using NiO has been extensively discussed [34][35][36] . There are various conduction mechanisms possible in oxide-based memristor devices.…”

“…The solution processed NiO x nanoparticles have been successfully used for efficient hole transport layer in organic optoelectronic devices 41 . There are few reports on NiO thin film-based resistive switching devices and few attempts in using NiO thin film devices for synaptic applications [34][35][36]42 . A modified Ebbinghaus forgetting curve has been established for NiO thin film memristor with conductance decreasing with time 43 .…”