Intelligent materials with adaptive response to external stimulation lay foundation to integrate functional systems at the material level. Here, with experimental observation and numerical simulation, we report a delicate nano-electro-mechanical-opto-system naturally embedded in individual multiwall tungsten disulfide nanotubes, which generates a distinct form of in-plane van der Waals sliding ferroelectricity from the unique combination of superlubricity and piezoelectricity. The sliding ferroelectricity enables programmable photovoltaic effect using the multiwall tungsten disulfide nanotube as photovoltaic random-access memory. A complete “four-in-one” artificial vision system that synchronously achieves full functions of detecting, processing, memorizing, and powering is integrated into the nanotube devices. Both labeled supervised learning and unlabeled reinforcement learning algorithms are executable in the artificial vision system to achieve self-driven image recognition. This work provides a distinct strategy to create ferroelectricity in van der Waals materials, and demonstrates how intelligent materials can push electronic system integration at the material level.

对外部刺激具有自适应响应的智能材料为材料层面的功能系统集成奠定了基础。在这里，通过实验观察和数值模拟，我们报告了一种精致的纳米机电光学系统，该系统自然嵌入单个多壁二硫化钨纳米管中，该系统通过独特的组合产生独特形式的面内范德华滑动铁电性。超润滑性和压电性。滑动铁电性使用多壁二硫化钨纳米管作为光伏随机存取存储器来实现可编程光伏效应。纳米管器件中集成了完整的“四合一”人工视觉系统，同步实现检测、处理、记忆和供电的全部功能。有标记的监督学习和无标记的强化学习算法都可以在人工视觉系统中执行，以实现自驱动的图像识别。这项工作提供了一种在范德华材料中产生铁电性的独特策略，并展示了智能材料如何在材料层面推动电子系统集成。