Machine Learning Approach to Characterize Ferromagnetic La0.7Sr0.3MnO3 Thin Films via Featurization of Surface Morphology

Sanghyeok Ryou*, Jihyun Lim*, Minwoo Jang, Kitae Eom, Sunwoo Lee*, Hyungwoo Lee*

Advanced Science, 2025

This work applies an ensemble machine learning approach that featurizes LSMO thin-film surface morphology to capture nonlinear correlations with electronic and magnetic properties, classifying films into five representative types and demonstrating surface morphology as an efficient, non-invasive probe of the strongly correlated properties in ferromagnetic perovskite oxides.

BibTeX

@article{ryou2025machine,
  title={Machine learning approach to characterize ferromagnetic La0. 7Sr0. 3MnO3 thin films via featurization of surface morphology},
  author={Ryou, Sanghyeok and Lim, Jihyun and Jang, Minwoo and Eom, Kitae and Lee, Sunwoo and Lee, Hyungwoo},
  journal={Advanced Science},
  volume={12},
  number={23},
  pages={2417811},
  year={2025},
  publisher={Wiley Online Library}
}