2025-11-26 シカゴ大学（UChicago）
The “self-driving” lab system. Photo by John Zich
＜関連情報＞
- https://news.uchicago.edu/story/fully-automated-lab-system-learns-grow-materials-its-own
- https://www.nature.com/articles/s41524-025-01805-0
サンプル固有の決定を即座に行う自動運転物理蒸着システム A self-driving physical vapor deposition system making sample-specific decisions on the fly
Yuanlong Bill Zheng,Connor Blake,Layla Mravac,Fengxue Zhang,Yuxin Chen & Shuolong Yang
npj Computational Materials Published:05 November 2025
DOI:https://doi.org/10.1038/s41524-025-01805-0
Abstract
We present an autonomous physical vapor deposition system that integrates hardware automation, in-situ optical spectroscopy, and Bayesian machine learning into a complete self-driving laboratory framework making decisions on the fly. Using silver thin films as a model material, our platform efficiently navigates a complex parameter space through active learning. By introducing a thin physical layer denoted as calibration layer, the machine learning models adapt to sample-specific conditions on the fly and reliably predict the deposition conditions to achieve user-specified optical properties. Moreover, from the high-throughput experimental data, the algorithm systematically captures the complex parameter-property relationships that are challenging to deduce by conventional trial-and-error methods. This study demonstrates the potential of self-driving laboratories for both reducing human labor and gaining new understanding of materials, providing a streamlined approach to enable self-driving physical vapor deposition systems.
