Brain-like computing is an important direction for the development of integrated circuits in the post-Moore era, and the development of artificial synaptic devices that can simulate ideal synaptic behavior is the key to building brainlike computing chips with neuron-synapse-neuron connectivity. Ferroelectric thin film materials have unique nonvolatile polarization, and the plasticity of polarization is very similar to that of biological synapses, so ferroelectric synaptic devices have been widely concerned in recent years. In this paper, the research progress of ferroelectric synaptic devices is reviewed from two aspects, simulation of synaptic function in devices and brain-like computing applications. The results show that ferroelectric synaptic devices have two typical structures of two-terminal and three-terminal. In addition to effectively simulating biological synapse functions, ferroelectric synaptic devices also have the advantages of simple structure, low power consumption, high stability, large switching ratio, and fast programming speed. In terms of applications, a series of advances have been made in the study of ferroelectric synapse-based neural networks for image recognition; meanwhile, ferroelectric synapses have also been applied to tactile and visual bionics. Although abundant research progress has been made, ferroelectric synapses are still at the proof-of-principle stage. There are considerable challenges in the synaptic performance regulation mechanism, reliability evaluation criteria, array structure optimization design, high-density integration process, neuromorphic computing architecture design, and novel application scenario expansion, which are also the directions that need to be focused for future ferroelectric synapse research.

类脑计算是后摩尔时代集成电路发展的重要方向，开发能够模拟理想突触行为的人工突触器件是构建具有神经元-突触-神经元连通性的类脑计算芯片的关键。铁电薄膜材料具有独特的非挥发性极化，极化的可塑性与生物突触非常相似，因此铁电突触器件近年来受到广泛关注。本文从突触功能在器件中的模拟和类脑计算应用两个方面综述了铁电突触器件的研究进展。结果表明，铁电突触器件具有二端和三端两种典型结构。铁电突触器件除了能有效模拟生物突触功能外，还具有结构简单、功耗低、稳定性高、开关比大、编程速度快等优点。在应用方面，基于铁电突触的神经网络图像识别研究取得了一系列进展；同时，铁电突触也被应用于触觉和视觉仿生学。尽管已经取得了丰富的研究进展，但铁电突触仍处于原理验证阶段。在突触性能调控机制、可靠性评价标准、阵列结构优化设计、高密度集成工艺、神经拟态计算架构设计、新型应用场景扩展等方面存在相当大的挑战，