Nowadays, memristors are extremely similar to biological synapses and can achieve many basic functions of biological synapses, making them become a new generation of research hotspots for brain-like neurocomputing. In this work, we prepare a memristor based on two-dimensional α-In₂Se₃ nanosheets, which exhibits excellent electrical properties, faster switching speeds, and continuous tunability of device conduction. Meanwhile, most basic bio-synapse functions can be implemented faithfully, such as short-term memory (STM), long-term memory (LTM), four different types of spike-timing-dependent plasticity (STDP), and paired-pulse facilitation (PPF). More importantly, we systematically study three effective methods to achieve LTM, in which the reinforcement learning can be faithfully simulated according to the Ebbinghaus forgetting curve. Therefore, we believe this work will promote the development of learning functions for brain-like computing and artificial intelligence.

如今，忆阻器与生物突触极为相似，可以实现生物突触的许多基本功能，使其成为新一代类脑神经计算的研究热点。在这项工作中，我们制备了基于二维 α-In ₂ Se _{3的忆阻器}纳米片具有优异的电性能、更快的开关速度和器件传导的连续可调性。同时，大多数基本的生物突触功能都可以忠实地实现，例如短期记忆（STM）、长期记忆（LTM）、四种不同类型的脉冲时间依赖性可塑性（STDP）和双脉冲促进。 （PPF）。更重要的是，我们系统地研究了实现 LTM 的三种有效方法，其中强化学习可以忠实地根据艾宾浩斯遗忘曲线进行模拟。因此，我们相信这项工作将促进类脑计算和人工智能学习功能的发展。