The Lopez group uses quantum mechanical and machine learning techniques to identify next-generation organic materials for applications in renewable energy and photomedicine. Organic materials are of great interest because they are highly abundant, low cost, and flexible. Our computational approach is combined with the experimental expertise of our collaborators, which establishes a powerful experiment-theory feedback loop that accelerates discoveries.
We are interested in improving the sustainability of modern transition-metal-catalyzed organic reactions by invoking photocatalysis and mild reaction conditions. As such, the reaction mechanisms of key organic reactions (i.e. C–H activation reactions, strained ring opening, and rearrangement reactions) are the focus of this fundamental research with high-impact applications described below:
Photodynamic Therapy (PDT) is a minimally disruptive cancer treatment. However, few drugs are currently approved for this purpose. We perform high-throughput virtual screening of candidates and use the results to rationally design potential drugs with visible and near-IR light absorption. Target compounds are then subjected to more complex calculations to evaluate their excited state properties and predict new reactivity modes.
Our group uses quantum mechanical calculations and molecular dynamics simulations to describe the relative crystallinity of organic semiconducting materials, which is known to substantially affect fundamental electronic processes in organic solar cells. We extend these calculations to provide atomistic descriptions of buried, donor-acceptor interfaces. Chemical intuition is used to fine-tune molecular interactions to ultimately control local interfacial disorder for highly effective, low-cost organic solar cells.