Won June Kim

1. Introduction Click to copy section linkSection link copied! The development of artificial intelligence caused a paradigm shift in prediction and design of crystal materials. (1) The traditional methods of characterization and design of crystal materials often rely on laborious trial-and-error experimentation, guided by intuition and high-throughput computational screening using density functional theory (DFT).

First principles investigations of the optical selectivity of titanium carbide-based materials for concentrating solar power applications To improve the efficiency of concentrated solar power devices and to reach a high conversion rate of the solar energy into heat, a rational design of new high temperature absorber materials is a challenge of prime importance.

Materials design increasingly relies on first-principles calculations for screening important candidates and for understanding quantum mechanisms. Density functional theory (DFT) is by far the most popular first-principles approach due to its efficiency and accuracy. However, to accurately predict structures and thermodynamics, DFT must be paired with a van der Waals (vdW) dispersion correction. Therefore, such corrections have been the subject of intense scrutiny in recent years.