Currently available solar cells based on crystalline semiconductors such as silicon can harvest solar power efficiently, but the installed cost of these modules is still too high to be cost-competitive with legacy fossil fuels. Solution-processed materials, such as colloidal quantum dots (CQDs) and lead halide perovskites are alternative materials that approach silicon in performance, at a fraction of cost, or can complement and enhance the available silicon modules.

PbS colloidal quantum dots and lead halide perovskites are the most successful recent examples, achieving high photovoltaic efficiencies. They have also been successfully employed in LEDs, photodetectors, and lasers. Understanding their fundamental properties at the atomic level and suggesting new ways to modulate these properties was at the heart of such progress and relied heavily on computational modeling using the density functional theory, manybody physics, and kinetic models.

I will discuss how modeling helped us describe bulk and surface defects on atomic level for structures containing thousands of atoms, understand the material growth and stability depending on many additives utilized experimentally, derive the excitonic and lasing properties of our materials, and use high-throughput screening to explore new materials combinations.