Reconfigurable High‐Performance Memristors Based on Few‐Layer High‐κ Dielectric Bi ₂ SeO ₅ for Neuromorphic Computing

Abstract Memristors are pivotal for energy‐efficient artificial intelligence (AI) hardware, potentially eliminating the von Neumann bottleneck by in‐memory realizations of synaptic operations. However, the dynamic requirements of neuromorphic computing on specific electronic devices pose reliability and universality challenges, limiting progress toward more widely applicable computing platforms. Here, a 2D high‐κ dielectric‐based memristor with the desired reconfigurable resistive switching behavior is successfully demonstrated. Utilizing a few layered Bi 2 SeO 5 possessing excellent electrical insulation properties as the switching medium, the device features a low operating voltage (≈0.5 V), low operation current (10 pA), long memory retention (>10 3 s), large switching window (≈10 8 ), steep slope (<1 mV dec −1 ), fast switching speed (40 ns), and low energy…