Tunable Resistive Switching in CsPbBr₃ Nanocrystal‐Based Memristors for Artificial Synapse and Neuromorphic Applications

Abstract The growing demand for energy‐efficient, brain‐inspired computing has driven interest in memristors for neuromorphic hardware. All‐inorganic halide perovskite cesium lead bromide (CsPbBr₃) is a promising material for memristor‐based artificial synapses due to its mixed ionic‐electronic conductivity, low activation energy of bromide vacancy, and superior defect tolerance. This study demonstrates tunable resistive switching properties of a forming‐free memristor with CsPbBr₃ nanocrystals, achieving both digital (abrupt) and analog (gradual) switching for neuromorphic applications. The fabricated device exhibits stable non‐volatile digital switching behavior with an ON/OFF ratio of 10³, endurance of 500 cycles, and a high retention time of 4000 s with relatively low SET and RESET voltage, along with displaying gradual conductance states with appropriate voltage pulses. The device replicates various key biological synaptic functionalities, including short‐term plasticity, long‐term plasticity, and paired‐pulse facilitation, spike rate‐dependent plasticity, which can be controlled by the amplitude and duration of the applied bias. The potentiation and depression characteristics are utilized to train an artificial neural network, achieving 93.2% classification accuracy for handwritten digit recognition. This work highlights a reliable method to control switching dynamics in CsPbBr₃ nanocrystal‐based memristors, making them suitable for data storage and in‐memory computing applications.