High-Performance Artificial Synapse Device Based on Cs <sub>3</sub> Bi <sub>2</sub> Br <sub>9</sub> /NiO Heterostructure for Bio-Inspired Neuromorphic Computing
Xiuqing Cao, Wenfei Li, Qingqing Zheng, Juan Meng, Leilei Yang, L. B. Wang, Yuyang Huang, Shoulei Xu, Wen Deng
Abstract
The development of energy-efficient and biocompatible artificial synapses is essential to advance neuromorphic computing. Bismuth-based perovskites are promising candidates to replace toxic lead-based perovskites in resistive switching devices owing to their exceptional optoelectronic properties, high environmental friendliness, and stability. Here, we present a lead-free Cs 3 Bi 2 Br 9 /NiO heterostructure memristor capable of mimicking biological synaptic functions with exceptional robustness. By engineering a heterostructure with a NiO layer, ion migration in Cs 3 Bi 2 Br 9 is spatially confined, achieving a resistance switching change rate of less than 7.37% between cycles and enhanced long-term stability in ambient air (60 days). This Cs 3 Bi 2 Br 9 /NiO memristor exhibits excellent stability, impressive memory retention time (>7 × 10 3 s), durability (>100 cycles), good on/off ratio, and basic synaptic behavior. Furthermore, the training results of 200 data achieved an accuracy rate of 95.46% in the MNIST handwritten digit recognition task, which was superior to traditional analog neural networks. This work not only highlights the significant potential of lead-free perovskites for sustainable neuromorphic hardware but also provides a scalable preparation path for biocompatible electronics.