van der Waals Ferroelectric Halide Perovskite Artificial Synapse
Yao Cai, Yang Hu, Zhizhong Chen, Jie Jiang, Lifu Zhang, Yuwei Guo, Saloni Pendse, Ru Jia, Jiahe Zhang, Xiaolong Ma, Chengliang Sun, Jian Shi
Abstract
Ferroelectricity is promising in emulating the synaptic characteristics of human brains. Utilizing ferroelectricity for brain-inspired computing is proposed as a feasible route to address technical challenges in memory and computing. Here, we demonstrate the use of a ferroelectric van der Waals (vdW) halide perovskite for synaptic emulation. The two-terminal ferroelectric synapse based on the vdW material (R)-(\ensuremath{-})-1-cyclohexylethylammonium)${\mathrm{PbI}}_{3}$ (R-CYHEA${\mathrm{PbI}}_{3}$) exhibits voltage-pulse-dependent weight modulation with a total on:off ratio of 50 and good endurance up to ${10}^{7}$ cycles. The energy consumption per synaptic operation for both short-term plasticity and long-term plasticity reaches the picojoule level. The device also shows reasonable write linearity and small cycle-to-cycle variation, as well as promising spike-timing-dependent plasticity and a paired-pulse-facilitation function. Numerical simulations with the R-CYHEA${\mathrm{PbI}}_{3}$-synapse-based neural network suggest the potential of R-CYHEA${\mathrm{PbI}}_{3}$ synapses for pattern recognition. Ferroelectric vdW halide perovskites provide opportunities for exploiting their dimensionality, superior optoelectronic properties, and mild material-processing conditions for engineering of the synaptic device performance.