Work

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

Year: 2025

Type: article

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 Sr 2 Nb 3 O 10 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 >10 3 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.

Source: Advanced Science

DOI: 10.1002/advs.202517588