DOI: 10.1002/advs.78461 ISSN: 2198-3844

Highly Linear Perovskite Synapses for Neuromorphic Computing

Zhongwen Sun, Boyu Wan, Zifan Zhang, Zhikai Wang, Xuan Zhao, Haonan Si, Qingliang Liao, Yue Zhang

ABSTRACT

Neuromorphic computing offers a compelling route to data‐intensive applications with boosted computing power and energy efficiency. However, its accuracy for edge vision tasks is critically bottlenecked by the inherent non‐linearity and asymmetry of conductance updates in analog memristive synapses. Here, we report a highly linear memristive synapse based on vertically aligned alternating cations in the interlayer space phase halide perovskite. A synergistic regulation strategy involving additive engineering and solvent atmosphere annealing is introduced to fabricate GAMA 5 Pb 5 I 16 halide perovskite films with vertical crystal orientation. The resulting films facilitate controllable ion migration, allowing the fabricated devices to achieve an ultra‐low energy consumption of 5.5 aJ alongside 100 discrete conductance states with non‐linearity as low as 0.027 and 0.064 and asymmetry of 0.037. These attributes enable the synapses to perform object detection tasks with an mAP50 of 57.6%, retaining 98.1% of the floating‐point baseline performance. This work provides a promising biomimetic solution for efficient visual perception in intelligent transportation, paving the way for high‐precision neuromorphic systems.

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