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Title: An Interface‐Type Memristive Device for Artificial Synapse and Neuromorphic Computing

Interface‐type (IT) metal/oxide Schottky memristive devices have attracted considerable attention over filament‐type (FT) devices for neuromorphic computing because of their uniform, filament‐free, and analog resistive switching (RS) characteristics. The most recent IT devices are based on oxygen ions and vacancies movement to alter interfacial Schottky barrier parameters and thereby control RS properties. However, the reliability and stability of these devices have been significantly affected by the undesired diffusion of ionic species. Herein, a reliable interface‐dominated memristive device is demonstrated using a simple Au/Nb‐doped SrTiO3(Nb:STO) Schottky structure. The Au/Nb:STO Schottky barrier modulation by charge trapping and detrapping is responsible for the analog resistive switching characteristics. Because of its interface‐controlled RS, the proposed device shows low device‐to‐device, cell‐to‐cell, and cycle‐to‐cycle variability while maintaining high repeatability and stability during endurance and retention tests. Furthermore, the Au/Nb:STO IT memristive device exhibits versatile synaptic functions with an excellent uniformity, programmability, and reliability. A simulated artificial neural network with Au/Nb:STO synapses achieves a high recognition accuracy of 94.72% for large digit recognition from MNIST database. These results suggest that IT resistive switching can be potentially used for artificial synapses to build next‐generation neuromorphic computing.

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Award ID(s):
1809520 2016453 1902644 1902623
Author(s) / Creator(s):
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Publisher / Repository:
Wiley Blackwell (John Wiley & Sons)
Date Published:
Journal Name:
Advanced Intelligent Systems
Medium: X
Sponsoring Org:
National Science Foundation
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