AI-Driven Scanning Probe Microscopy for Atomic Engineering at Room Temperature
Date: 2026-05-19
Time: 15:33
Venue: Tencent Meeting
Speaker: Dr. Zhuo Diao, University of Osaka
Tencent Meeting ID：105-523-450
Password：0527
Host: 蔡云麒 副研究员
Contact: 傅 琦 (fuqi@iphy.ac.cn)
Abstract:
The concept of atomic engineering, originally proposed by K. Eric Drexler in the 1990s, envisioned the programmable construction of matter through atom-by-atom manipulation. Scanning probe microscopy (SPM) has emerged as one of the most important scientific tools for realizing this vision, integrating atomic-scale characterization and manipulation within a single experimental platform. Such atomic assembly technologies are expected to play a key role in ultimate-scale manufacturing, potentially enabling breakthroughs in advanced electronic devices and functional materials. However, current atom manipulation techniques still rely heavily on cryogenic environments and manual operation, resulting in low experimental throughput, poor reproducibility, and limited scalability toward practical manufacturing. In this talk, I will present our recent efforts to establish an AI-driven autonomous experimental framework for room-temperature atomic-scale characterization and manipulation.
The presentation covers digitally programmable SPM instrumentation, high-throughput imaging methods, locally deployed LLM agents, and autonomous optimization systems for thermal drift correction and probe recovery. Using this framework, we demonstrate unattended atomic-resolution characterization, automated atomic spectroscopy, and AI-guided atom manipulation at room temperature.
Brief CV of Dr. Zhuo Diao:
Zhuo Diao received his Ph.D. degree in Engineering from the University of Osaka in 2024. He is currently an Assistant Professor at the Graduate School of Engineering Science, The University of Osaka. During his research career, his work has focused on measurement informatics, integrating data science and algorithms into scientific instrumentation to enable deeper insights into physical phenomena. His research has been applied to self-driving laboratories (SDLs) for scanning probe microscopy (SPM) and intelligent control systems for memristor devices.