Diao Zhuo, Ueda Keiichi, Hou Linfeng, Li Fengxuan, Yamashita Hayato, Abe Masayuki
Graduate School of Engineering Science, Osaka University, 1-3 Machikaneyama-Cho, Toyonaka, Osaka, 560-8531, Japan.
Tokyo Metropolitan Industrial Technology, Research Institute, 2-4-10 Aomi, Koto-Ku, Tokyo, 135-0064, Japan.
Small Methods. 2025 Jan;9(1):e2400813. doi: 10.1002/smtd.202400813. Epub 2024 Sep 6.
An advanced scanning probe microscopy system enhanced with artificial intelligence (AI-SPM) designed for self-driving atomic-scale measurements is presented. This system expertly identifies and manipulates atomic positions with high precision, autonomously performing tasks such as spectroscopic data acquisition and atomic adjustment. An outstanding feature of AI-SPM is its ability to detect and adapt to surface defects, targeting or avoiding them as necessary. It is also designed to overcome typical challenges such as positional drift and tip apex atomic variations due to the thermal effects, ensuring accurate, site-specific surface analysis. The tests under the demanding conditions of room temperature have demonstrated the robustness of the system, successfully navigating thermal drift and tip fluctuations. During these tests on the Si(111)-(7 × 7) surface, AI-SPM autonomously identified defect-free regions and performed a large number of current-voltage spectroscopy measurements at different adatom sites, while autonomously compensating for thermal drift and monitoring probe health. These experiments produce extensive data sets that are critical for reliable materials characterization and demonstrate the potential of AI-SPM to significantly improve data acquisition. The integration of AI into SPM technologies represents a step toward more effective, precise and reliable atomic-level surface analysis, revolutionizing materials characterization methods.
本文介绍了一种增强型扫描探针显微镜系统,即人工智能扫描探针显微镜(AI-SPM),该系统专为自动驾驶原子尺度测量而设计。该系统能够高精度地识别和操纵原子位置,自主执行光谱数据采集和原子调整等任务。AI-SPM的一个突出特点是能够检测并适应表面缺陷,必要时对其进行定位或避开。它还旨在克服诸如由于热效应导致的位置漂移和针尖顶端原子变化等典型挑战,确保进行准确的、特定位置的表面分析。在室温苛刻条件下的测试证明了该系统的稳健性,成功应对了热漂移和针尖波动。在对Si(111)-(7×7)表面进行的这些测试中,AI-SPM自主识别出无缺陷区域,并在不同吸附原子位置进行了大量电流-电压光谱测量,同时自主补偿热漂移并监测探针状态。这些实验产生了大量数据集,对于可靠的材料表征至关重要,并证明了AI-SPM显著改善数据采集的潜力。将人工智能集成到扫描探针显微镜技术中代表着朝着更有效、精确和可靠的原子级表面分析迈出了一步,彻底改变了材料表征方法。