Machine Learning for Materials Design

First-principles electronic transport properties


We use advanced simulation methods, such as time-dependent density functional theory, to model how electrons in materials respond to optical laser light. This enables us to predict important material properties, including response functions and electronic transport behavior, which are essential for designing next-generation photonic and nanoelectronic devices.

Research Highlight: Electron dynamics in titanium dioxide

We have studied the electron dynamics in titanium dioxide when exposed to ultrashort and high-intensity laser fields using real-time time-dependent density functional theory.

Our investigation includes both perturbative and non-perturbative responses exhibited by titanium dioxide when exposed to 30 femtosecond laser pulses at different optical wavelengths.

This study allowed us to elucidate the underlying mechanisms of energy transfer, nonlinear refractive index, and laser-induced material damage.

Our results can guide further exploration of laser parameters and structural defect engineering of titanium dioxide thin films with tailored properties for specific applications in nonlinear photonic devices.