Materials informatics exploiting machine learning techniques, e.g., Bayesian optimization (BO), have the potential to reduce the number of thin-film growth runs for optimization of thin-film growth conditions. Here, we demonstrate BO-based molecular beam epitaxy (MBE) of SrRuO3. As a result, high-crystalline-quality SrRuO3 film exhibiting a high residual resistivity ratio of over 50 as well as strong perpendicular magnetic anisotropy was developed in only 24 MBE growth runs.

Y. K. Wakabayashi*, et al.
APL Materials 7, 101114 (2019).