翻译以下内容为英语--扫描隧道显微镜STM是探测实空间内样品表面电子态分布的重要科研平台。然而STM的高质量成像需要操作者的经验抬高了使用门槛。且在低温、高真空、强磁场等非高静态环境中STM的准备及测量都是耗时费力的。本项目针对以上问题提出将扫描过程智能化的想法阐明了STM与深度学习融合进而实现全流程智能化所面对的问题并陈述了有效的解决方案。本项目拟在现有工作基础上构建一套适用于室温大气环境的全流程智能化STM进行图像质量验证其核心技术包括：针尖分类模块、针尖修复模块、自动扫描模块、上下位控制系

Scanning tunneling microscopy (STM) is an important scientific research platform for detecting the distribution of electronic states on the surface of samples in real space. However, high-quality imaging with STM requires a lot of experience from the operator, raising the threshold for use. Moreover, preparation and measurement with STM in non-static environments such as low temperature, high vacuum, and strong magnetic fields are time-consuming and laborious. This project proposes the idea of intelligent scanning to address these issues, explaining the problems faced by the integration of STM and deep learning to achieve full-process intelligence, and stating effective solutions. Based on existing work, this project aims to build a fully intelligent STM suitable for room temperature atmospheric environments to verify image quality. Its core technologies include tip classification modules, tip repair modules, automatic scanning modules, upper and lower control systems, high-rigidity large-thrust motors, high-rigidity axis-symmetric scanning heads, and high-sensitivity STM detection circuits. This microscope can automatically optimize probes, replace samples, switch scanning areas, and automatically save high-quality images, achieving fully intelligent high-quality imaging in the entire process, which undoubtedly represents a significant breakthrough in the efficiency and convenience of STM use.