Dual Bipolar Resistive Switching in Wafer-Scalable 2D Perovskite Oxide Nanosheets-Based Memristor

Abstract

Memristors based on 2D materials are promising for compact and energy-efficient neuromorphic hardware. However, conventional devices require paired elements to implement bidirectional weight updates, such as spike-timing-dependent plasticity (STDP) and anti-STDP for supervised spiking neural networks (SNN) such as the remote supervised method. Here, an Au/Ti/2D Sr2Nb3O10 perovskite-oxide nanosheet (SNO PON)/Pt memristor is demonstrated that exhibits dual bipolar resistive switching, supporting clockwise (interface) and counter-clockwise (filament) switching. Ultrathin (≈5 nm) SNO PONs, fabricated over wafer-scale areas by Langmuir–Blodgett deposition, serve as dynamic reservoirs for oxygen ions and vacancies. Voltage-induced redox reactions at the Ti electrode are accompanied by the formation of oxygen vacancies in the SNO, as confirmed through cross-sectional transmission electron microscopy and electron energy-loss spectroscopy. The memristor exhibits stable resistance states with >103 s retention and <0.2 V set variation across 30 cells. Bidirectional plasticity under dual-polarity pulse trains replicates STDP/anti-STDP rules, enabling a 3 × 3 array to encode pixel patterns with opposite-polarity pulses. A leaky integrate-and-fire SNN model achieves 86.4 % accuracy on the MNIST dataset using identical pre- and post-synaptic spike waveforms. These findings establish dual bipolar 2D memristors as scalable and efficient components for high-density, simplified supervised SNN hardware.