研制具有生物神经元信息功能的柔性电子器件对于发展智能穿戴技术具有重要意义。传统阈值型忆阻器可模仿神经元信息整合功能, 但因缺乏本征柔韧性, 难以满足应用需求。本工作制备了一种基于本征可拉伸阈值型忆阻器的柔性人工神经元, 它由银纳米线-聚氨酯复合介质薄膜和液态金属电极构成。在外加电压下, 器件呈现良好的阈值电阻转变特性, 这归因于银纳米线间形成非连续银导电细丝的动态通断。该器件可模仿生物神经元的信息整合-发放及脉冲强度和脉冲间隔调制的尖峰放电功能。在20%拉伸应变下, 器件工作参数基本保持稳定, 性能未发生明显退化。本工作为发展可拉伸柔性人工神经元及下一代智能穿戴设备提供重要材料和技术参考。

With rapid advancement and deep integration of artificial intelligence and the internet-of-things, artificial intelligence of things has emerged as a promising technology changing people’s daily life. Massive growth of data generated from the devices challenges the AIoT systems from information collection, storage, processing and communication. In the review, we introduce volatile threshold switching memristors, which can be roughly classified into three types: metallic conductive filament-based TS devices, amorphous chalcogenide-based ovonic threshold switching devices, and metal-insulator transition based TS devices. They play important roles in high-density storage, energy efficient computing and hardware security for AIoT systems. Firstly, a brief introduction is exhibited to describe the categories (materials and characteristics) of volatile TS devices. And then, switching mechanisms of the three types of TS devices are discussed and systematically summarized. After that, attention is focused on the applications in 3D cross-point memory technology with high storage-density, efficient neuromorphic computing, hardware security (true random number generators and physical unclonable functions), and others (steep subthreshold slope transistor, logic devices,etc.). Finally, the major challenges and future outlook of volatile threshold switching memristors are presented.