Controlling Switching Evolution in Lead-Free Perovskite-Inspired Chalcogenide Memristors for Neuromorphic Computing

Abstract

Memristors have emerged as key building blocks of neuromorphic computing architectures due to their ability to integrate data storage and processing. While metal halide perovskites have recently shown significant promise owing to their mixed electronic-ionic conduction and low-cost solution processability, their reliance on toxic lead and limited stability presents critical challenges. Here, we report environmentally friendly, low-toxicity AgBiS2-based solution-processable memristors exhibiting an ultra-low SET voltage of ~0.08 V and a high ON/OFF ratio of>104. First-principles calculations identify Ag interstitials as the energetically most favourable native defect and reveal low migration barriers within the Ag sublattice, for both interstitials and vacancies, facilitating ionic transport in the AgBiS2 lattice. Through interface and thickness engineering, the resistive switching behaviour can be systematically tuned from abrupt digital to gradual analog modes. Notably, thicker switching layers promote the evolution of stable conductive pathways through intermediate metastable states, revealing a controllable filament evolution process. Electrochemical impedance spectroscopy reveals pronounced negative capacitance (inductive) behaviour at low bias voltages, arising from coupled electronic-ionic dynamics. Consistent with this behaviour, pulse measurements demonstrate gradual conductance modulation under pulse trains, emulating synaptic responses relevant for neuromorphic computing. Finally, post-operando structural analysis reveals substantial morphological evolution of the switching layer driven by repeated filament formation and rupture. Linking structural dynamics to switching variability provides important design principles for achieving reliable and durable sustainable memristors.