The development of transformative, next-generation quantum devices will require breakthrough innovation in molecular materials. Nature has evolved the sophisticated ability to organize chromophores and pigments to harness quantum mechanical properties for powerful capabilities, including solar energy harvesting, nanoscale energy transport, and energy conversion. Replicating these quantum capabilities of nature using synthetic materials remains a significant goal of rational materials design and fabrication.

To overcome the bottlenecks that are intrinsic to modern materials design efforts, including costly and time-consuming synthesis and experimental characterization, the project will develop a machine learning-guided, high-throughput in silico screening platform to accelerate the discovery of functional chromophore- and qubit-DNA assemblies. The research team seeks to achieve predictive control over electronic state evolution in molecular systems organized using designer DNA assemblies.

Realizing this control will enable the design of revolutionary materials and devices for various applications in quantum science and technology, including next-generation photovoltaic coatings, quantum sensors, quantum simulators, and biological imaging agents.