M. Samrat

Machine learning based prediction of optical properties in two-dimensional Mo-W-S-Se-Te transition-metal dichalcogenide alloys through physics-informed sampling

This work combined ab initio optical-property calculations with a tabular foundation-model regression to predict the real and imaginary components of the frequency-dependent dielectric function for Mo-W-S-Se-Te TMD alloys, and predicted derived optical quantities, including refractive index, extinction coefficient, and absorption coefficient.