Memristor-based neuromorphic computing is promising for artificial intelligence. However, most of the reported memristors have limited linear computing states and consume large operation energy which hinder their applications. Herein, we report a memristor based on ionic two-dimensional CuInP₂S₆ (2D CIPS), in which up to 1350 linear conductance states are achieved by controlling the migration of internal Cu ions in CIPS. In addition, the device shows a low operation current of ∼100 pA. Cu ions are proven to move along the electric field by in-situ scanning electron microscopy and energy dispersive spectroscopy measurements. Furthermore, complex signal transport among multiple neurons in the brain is imitated by 2D CIPS-based memristor arrays. Our results offer a new platform to fabricate high-performance memristors based on ion transport in 2D materials for neuromorphic computing.

基于忆阻器的神经拟态计算在人工智能方面很有前景。然而，大多数报道的忆阻器的线性计算状态有限，并且消耗大量的运行能量，这阻碍了它们的应用。在此，我们报道了一种基于离子二维CuInP ₂ S ₆ (2D CIPS)的忆阻器，其中通过控制CIPS中内部Cu离子的迁移实现了高达1350个线性电导状态。此外，该器件的工作电流低至 ∼100 pA。原位扫描电子显微镜和能量色散谱证明铜离子沿着电场移动测量。此外，基于 2D CIPS 的忆阻器阵列可以模拟大脑中多个神经元之间的复杂信号传输。我们的研究结果提供了一个新的平台来制造基于二维材料中离子传输的高性能忆阻器，用于神经形态计算。