Structural degeneracy and formation of crystallographic domains in epitaxial LaFeO films revealed by machine-learning assisted 4D-STEM.

Structural domains and domain walls, inherent in single crystalline perovskite oxides, can significantly influence the properties of the material and therefore must be considered as a vital part of the design of the epitaxial oxide thin films. We employ 4D-STEM combined with machine learning (ML) to comprehensively characterize domain structures at both high spatial resolution and over a significant spatial extent. Using orthorhombic LaFeO as a model system, we explore the application of unsupervised and supervised ML in domain mapping, which demonstrates robustness against experiment uncertainties.

Strong on-Chip Microwave Photon-Magnon Coupling Using Ultralow-Damping Epitaxial YFeO Films at 2 K.

YFeO is arguably the best magnetic material for magnonic quantum information science (QIS) because of its extremely low damping. We report ultralow damping at 2 K in epitaxial YFeO thin films grown on a diamagnetic YScGaO substrate that contains no rare-earth elements. Using these ultralow damping YIG films, we demonstrate for the first time strong coupling between magnons in patterned YIG thin films and microwave photons in a superconducting Nb resonator.