Abstract

AbstractA crossbar array using resistive switching random‐access memory requires a selector device to prevent leakage current. However, the high current flow during the electroforming and first reset process (switching from a low resistance state to a high resistance state) can degrade the selector device. Ruthenium dioxide, a conducting oxide electrode with low oxygen affinity preventing excess oxygen vacancy in a dielectric, is used as a selector electrode to acquire a TiO2‐based nonlinear selector that endures a high current flow. The selector shows high nonlinearity (≈7 × 104), high forward and reverse current ratio (≈5.5 × 102), and sufficient endurance (>107) in the one selector‐one resistive switching memory (1S1R) structure, where the HfO2 comprises the resistive switching memory. 9 × 9 crossbar array composed of the 1S1R device is used as neuromorphic hardware to classify simple characters by offline supervised learning. Further classification simulation of the rescaled Modified National Institute of Standards and Technology dataset shows 95.77% accuracy with achievable array structure.

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