Integrated AI Framework for Room-Temperature Atom Manipulation in Scanning Probe Microscopy

Le résumé fourni par la source

We demonstrate an integrated artificial intelligence (AI) framework for autonomous atom manipulation of silver atoms on a Si(111)-(7 × 7) surface at room temperature. The framework combines four machine learning models that evaluate tip and surface conditions, detect Ag atoms, locate defect-free half-unit cells (HUCs), and evaluate manipulation conditions. This integration enables autonomous scanning tunneling microscopy operation with key functions including thermal drift correction, probe tip conditioning, and automated atom manipulation. The integrated AI framework demonstrated robust long-term operation, autonomously performing atom manipulation over 25 h. During this period, the system successfully executed both lateral transfer of Ag atoms between adjacent HUCs and vertical pickup operations without human intervention. While the manipulation success rate remains limited by tip stability challenges, the system demonstrates the feasibility of AI-driven autonomous operation at room temperature, providing a foundation for future high-throughput atomic-scale fabrication.

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