Superior rectification self-rectifying memristors with self-recovery capabilities enabled by GaOx/InOx heterostructures

Abstract

Memristors are poised to revolutionize neuromorphic computing and next-generation memory, yet persistent challenges, including stochastic conductance control, limited endurance, and poor scalability, impede their practical adoption. Here, we report a self-rectifying memristor leveraging a GaOx/InOx heterostructure to overcome these barriers. The device demonstrates an ultrahigh rectification ratio and nonlinearity (>107), effectively suppressing sneak currents in passive crossbar arrays. Robust multi-level conductance modulation and cycling stability exceeding 106 cycles are achieved, alongside minimal inter-device variability (σ/μ < 10%) in a 6 × 6 passive array. Critically, it demonstrates dynamic tunability between short-term and long-term plasticity, modulated via pulse number/amplitude, a cornerstone for biologically inspired learning. By implementing the one-bitline pull-up scheme, the design achieves an integration density of 125.1 Tb at a 10% read margin, outperforming state-of-the-art resistive memories. This work establishes oxide heterostructures as a scalable platform for high-density neuromorphic systems, bridging the gap between functional material innovation and hardware-driven machine intelligence.