journal article·2022-06-28

Manipulating the Resistive Switching in Epitaxial SrCoO2.5 Thin-Film-Based Memristors by Strain Engineering

Xuepeng Xiang, Jingjing Rao, Chaesung Lim, Qicheng Huang, Shijun Zhao, Zhen Fan, Jeong Woo Han, Yan Chen

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Abstract

Diverse synaptic and neuronal functionalities often require different switching dynamics for memristors. Here, we demonstrate an effective approach to modulating the switching dynamics in epitaxial thin-film-based memristors by using strain engineering. We apply 0 and −2.74% compressive strains to the brownmillerite SrCoO2.5 (BM-SCO) thin films by epitaxially growing them on (001)-oriented SrTiO3 (STO) and LaAlO3 (LAO) substrates, with Au and La0.7Sr0.3MnO3 (LSM) acting as top and bottom electrodes, respectively. When applying multiple DC voltage sweeps, the Au/BM-SCO/LSM/LAO memristor with compressive strain displays small yet narrowly distributed ON/OFF ratios (averaged at ∼3.5 with a cycle-to-cycle fluctuation of ∼17%), while the Au/BM-SCO/LSM/STO memristor with zero strain exhibits larger ON/OFF ratios distributed in a wider range (averaged at ∼15.5 with a cycle-to-cycle fluctuation of ∼33%). In the retention tests, the Au/BM-SCO/LSM/LAO memristor exhibits relatively stable high and low resistance states (HRSs and LRSs, respectively). By contrast, for the Au/BM-SCO/LSM/STO memristor, while the HRS remains stable, the LRS relaxes first and eventually converts to a stable intermediate state. Such significant differences in ON/OFF ratio and retention between the two memristors may be associated with the epitaxial strain-mediated oxygen vacancy generation and migration, which effectively modulated the filament growth and rupture dynamics. Therefore, strain engineering represents a rational route for modulating memristor performance for various neuromorphic applications.
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Research context

OpenAlex topics: Advanced Memory and Neural Computing · Ferroelectric and Negative Capacitance Devices · Neuroscience and Neural Engineering

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

Affiliations

School of Environment and Energy, South China University of Technology, Guangzhou 510006, China

Institute for Advanced Materials and Guangdong Provincial Key Laboratory of Optical Information Materials and Technology, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, China

Computational Catalysis and Emerging Materials Laboratory, Pohang University of Science and Technology, Pohang, Gyeongbuk 37673, South Korea

Department of Mechanical Engineering, City University of Hong Kong, Kowloon 999077, Hong Kong, China

Funding

Guangzhou Science, Technology and Innovation Commission · National Natural Science Foundation of China · Natural Science Foundation of Guangdong Province · Guangdong Province

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