journal article·2024-04-17

Reconfigurable Resistive Switching in VO2/La0.7Sr0.3MnO3/Al2O3 (0001) Memristive Devices for Neuromorphic Computing

Sundar Kunwar, Nicholas Cucciniello, Alessandro R. Mazza, Di Zhang, Luis Santillan, Ben Freiman, Pinku Roy, Quanxi Jia, Judith L. MacManus-Driscoll, Haiyan Wang, Wanyi Nie, Aiping Chen

ACS Applied Materials & Interfaces· Volume 16· Issue 15
Publisher page

Abstract

The coexistence of nonvolatile and volatile switching modes in a single memristive device provides flexibility to emulate both neuronal and synaptic functions in the brain. Furthermore, such a device structure may eliminate the need for additional circuit elements such as transistor-based selectors, enabling low-power consumption and high-density device integration in fully memristive spiking neural networks. In this work, we report dual resistive switching (RS) modes in VO 2 /La 0.7 Sr 0.3 MnO 3 (LSMO) bilayer memristive devices. Specifically, the nonvolatile RS is driven by the movement of oxygen vacancies (V o ) at the VO 2 /LSMO interface and requires a higher biasing voltage, whereas the volatile RS is controlled by the metal–insulator transition (MIT) of VO 2 under a lower biasing voltage. The simple device structure is electrically driven between the two RS modes and thus can operate as a one selector–one resistor (1S1R) cell, which is a desirable feature in memristive crossbar arrays to avoid the sneak-path current issue. The RS modes are found to be stable and repeatable and can be reconfigured by exploiting the interfacial and phase transition properties, and thus, they hold great promise for applications in memristive neural networks and neuromorphic computing.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced Memory and Neural Computing · Transition Metal Oxide Nanomaterials · Gas Sensing Nanomaterials and Sensors

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Center for Integrated Nanotechnologies (CINT), Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States

Department of Materials Design and Innovation, University at Buffalo - The State University of New York, Buffalo, New York 14260, United States

Materials Science and Technology Division, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, United States

Department of Materials Science and Metallurgy, University of Cambridge, 27 Charles Babbage Road, Cambridge CB3 0FS, U.K.

School of Materials Engineering, Purdue University, West Lafayette, Indiana 47907, United States

Funding

Office of Science · National Nuclear Security Administration · CINT Users Program

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