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Dual-mode α-FAPbI3 Perovskite Memristors with Volatile and Nonvolatile Switching for Neuromorphic Computing and Handwritten Digit Recognition

Authors: Bowen Jiang; Yang Xiong; Xuepeng Liu; Yingjian Shi; Wentao Zhao; Guokun Ma; Jun Zhang; Houzhao Wan; Li Tao; Hao Wang

DOI: 10.1007/s40843-025-3575-4Status: Verified Translated Edition
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Key Findings in This Report

• • Dual-mode α-FAPbI3 perovskite memristors achieve switchable volatile/nonvolatile states via engineered SnO2 ETLs, with volatile devices exceeding 500 switching cycles and nonvolatile devices surpassing 1000 cycles, both maintaining a high on/off ratio of ~10^3, enabling reliable multi-state operation for memory and neuromorphic applications. • • Molecular interface optimization using Z14 and PNL yields exceptional device stability, critical for industrial deployment where operational endurance and reproducibility are paramount. • • Volatile mode replicates four nociceptor characteristics (threshold, relaxation, sensitization, no adaptation), while nonvolatile mode demonstrates synaptic plasticity (PPF, STDP), providing a hardware platform for biomimetic sensing and learning. • • A spiking neural network (SNN) built on these dual-mode devices achieves 93% accuracy in handwritten digit recognition, demonstrating the potential of perovskite memristors for neuromorphic computing at scale.