With this project, researchers are conducting a large-scale computational campaign to discover and design new materials and interfaces that will advance the efficiency of organic and hybrid solar cells. To do so, the team is developing first-principles approaches, based on density functional theory and many-body perturbation theory, to describe materials and interfaces on the most fundamental level at which solar energy conversion takes place and at which structure-function relationships are established. By combining massively parallel quantum-mechanical calculations with modern machine learning techniques and optimization algorithms, they aim to predict and design new advanced functional photovoltaic materials and hetero-structures.

Ultimately, this research will enable transformative advances in the understanding of organic and hybrid photovoltaic materials, and the technology needed to harness their power for affordable, large-scale solar cells. The project’s methodological advances will produce a general, broadly applicable first principles framework for structure search and computational design of functional materials that will broaden the community of researchers capable of using leadership computing resources to advance materials science for energy applications.