Closely following the rapid development of artificial intelligence, studies of the human brain and neurobiology are focusing on the biological mechanisms of neurons and synapses. Herein, a memory system employing a nanoporous double-layer structure for simulation of synaptic functions is described. The sponge-like double-layer porous (SLDLP) oxide stack of Pt/porous LiCoO₂/porous SiO₂/Si is designed as presynaptic and postsynaptic membranes. This bionic structure exhibits high ON–OFF ratios up to 10⁸ during the stability test, and data can be maintained for 10⁵ s despite a small read voltage of 0.5 V. Typical synaptic functions, such as nonlinear transmission characteristics, spike-timing-dependent plasticity, and learning-experience behaviors, are achieved simultaneously with this device. Based on the hydrodynamic transport mechanism of water molecules in porous sponges and the principle of water storage, the synaptic behavior of the device is discussed. The SLDLP oxide memristor is very promising due to its excellent synaptic performance and potential in neuromorphic computing.

紧随人工智能的迅速发展，人类大脑和神经生物学的研究集中在神经元和突触的生物学机制上。在此，描述了采用纳米多孔双层结构来模拟突触功能的存储系统。Pt /多孔LiCoO ₂ /多孔SiO ₂ / Si的海绵状双层多孔（SLDLP）氧化物堆叠被设计为突触前和突触后膜。在稳定性测试期间，这种仿生结构显示出高达10 ^8的高开/关比，并且可以保持10 ^5的数据 尽管读取电压为0.5 V，但仍能保持s的正常状态。使用该设备可同时实现典型的突触功能，例如非线性传输特性，与尖峰时序有关的可塑性和学习经验行为。基于多孔海绵中水分子的水动力传输机理和储水原理，讨论了该装置的突触行为。SLDLP氧化物忆阻器由于其出色的突触性能和在神经形态计算中的潜力而非常有前途。