Hyun Cheol Koo

Abstract Ferrimagnetic materials provide a versatile platform for high-frequency spintronic devices, combining the fast magnetic dynamics of antiferromagnets with the efficient electrical control characteristic of ferromagnets. Although the GdFeCo films studied here exhibit ferrimagnetic composition, their spin dynamics in the present regime are effectively ferromagnetic, enabling robust excitation of quantized spin-wave modes within a single layer.

Abstract Accurate prediction of emission spectra is crucial for the rational design of luminescent materials in optoelectronic devices such as phosphorescent organic light-emitting diodes (OLEDs). We present a physics-informed machine learning framework that integrates the Franck–Condon progression as a differentiable module for spectrum prediction.