在扫描探头显微镜中进行室温原子操纵的集成AI框架.
Junya Okuyama1, Zhuo Diao1, Hayato Yamashita1
1Graduate School of Engineering Science, The University of Osaka, 1-3 Machikaneyama, Toyonaka, Osaka 560-8531, Japan.
Nano letters
|December 16, 2025
概括
本研究介绍了一种人工智能 (AI) 框架,用于在室温下在表面对银原子进行自主原子操纵. 在没有人类干预的情况下,人工智能系统成功地进行了25个多小时的复杂原子操纵.
科学领域:
- 材料科学 材料科学 材料科学
- 人工智能的人工智能
- 表面科学是一门学科.
背景情况:
- 原子操纵对于原子规模的制造至关重要.
- 目前的方法通常需要手动控制和特定条件.
- 开发自主系统可以提高效率和精度.
研究的目的:
- 为自主原子操纵开发一个集成的人工智能框架.
- 为了实现室温操作,在Si{111) -{7 × 7}上进行银原子操纵.
- 为高通量原子规模制造奠定基础.
主要方法:
- 一个集成的AI框架,结合了四个机器学习模型.
- 模型评估尖端/表面条件,检测银原子,定位无缺陷的半单元细胞 (HUC),并评估操纵参数.
- 自主扫描道显微镜 (STM) 操作,包括热漂移校正和探头调节.
主要成果:
- 证明了强大,长期自主运行超过25小时.
- 成功地在HUC之间执行了横向和垂直的银原子转移.
- 在室温下实现AI驱动的自主原子操纵.
结论:
- 集成的AI框架显示了在室温下自主原子操纵的可行性.
- 提示稳定仍然是一个影响成功率的挑战.
- 这项工作为未来使用人工智能的高通量原子规模制造奠定了基础.
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