Inducing Tunable Volatile Analog Switching in Nanocomposite-Based MAPbBr3 Perovskite Memristors for Synaptic Emulation

Abstract

Metal halide perovskites (MHPs) are promising candidates for memristive applications owing to their mixed ionic-electronic conductivity, yet their inherent instability and tendency toward abrupt resistive switching remain critical barriers to neuromorphic implementations. Here, we present a nanocomposite strategy in which MAPbBr3 nanocrystals are synthesized in situ within a nickel acetate matrix through a one-step, annealing-free, and glovebox-free process, enabling ambient-stable memristive devices. By modulating the perovskite volume fraction, the ionic-electronic dynamics are tuned, inducing a transition from abrupt, nonvolatile digital switching in polycrystalline MAPbBr3 to gradual, volatile analog switching in the nanocomposite. Impedance spectroscopy and photophysical analyses attribute this transition to a shift from ion migration-driven switching in the bulk material to interfacial charge trapping and detrapping in the nanocomposite. The resulting volatile memristors emulate key synaptic functionalities, including short- and long-term plasticity, paired-pulse facilitation, and spike-dependent weight modulation, with stable performance over 1000 cycles under ambient conditions. Exploited in a reservoir computing framework, the nanocomposite memristor achieves ∼89% classification accuracy on noisy digit patterns with a linear readout, rising to 98% with a deeper network. This scalable, solution-processed approach offers a viable route to analog memristors for neuromorphic and edge computing.