Presentation Information
[17a-S4_201-10]An Automated System for Atomic-Scale Patterning Using Scanning Tunneling Microscope Lithography
Kensho Tsukuda1, 〇Jo Onoda2, Zhuo Diao1, Hayato Yamashita1, Masayuki Abe1 (1.Univ. Osaka, 2.Univ. Teacher Edu. Fukuoka)
Keywords:
scanning tunneling microscope,STM lithography,AI automation
We have investigated scanning tunneling microscope (STM) lithography as a nanoscale fabrication technique and previously reported the formation of isolated regions of approximately 10 nm² on Si(111)-(7×7) surfaces, together with I/V measurements inside and outside these regions. In STM lithography, a tunnel current orders of magnitude larger than that used for conventional imaging (e.g., 300 nA) is required, which frequently induces changes in the tip apex condition and necessitates repeated tip conditioning. In addition, thermal drift at room temperature causes gradual shifts of the lithography position, requiring continuous position correction during experiments. As a result, STM lithography strongly depends on the skill and experience of the operator. In this study, we report the development of an automated STM lithography system that performs lithography without human intervention. The system is based on our previously developed AI-assisted automation frameworks for room-temperature atomic manipulation and STS measurements, and has been extended specifically for STM lithography. It automatically executes a sequence of operations essential for STM lithography, including thermal drift correction, tip repair, lithography execution, evaluation of lithography success, and switching of amplifier gain depending on imaging or lithography modes. Using template matching, the system can automatically identify lithographed regions on Si(111)-(7×7) surfaces. These results demonstrate a platform for stable and reproducible STM lithography under room-temperature conditions.