NSF Award
2420490
The NSF Center for Accelerated Photocatalysis (CAPs) is supported by the Centers for Chemical Innovation (CCI) Program of the Division of Chemistry. CAPs aims to leverage light to achieve challenging chemical transformations, enabling access to sustainable, scalable, and more efficient chemical reaction pathways. Despite the proven role of photochemistry in sustainability and pharmaceuticals, progress in this high-priority area has been slow due to labor-intensive, one-experiment-at-a-time approaches that present significant time and resource constraints. CAPs will fast-track fundamental studies of emerging photo(bio)catalysis in chemical synthesis and reaction discovery by implementing a robotic 'co-pilot.' This ‘co-pilot’ will capitalize on machine learning (ML)-assisted robotic experimentation (self-driving laboratories, SDLs) to augment human knowledge in photo(bio)catalysis. Activities will include open-source reporting for all software and data generated, as well as a Summer Boot Camp for high school students and teachers. CAPs will emphasize engaging undergrad/graduate students with physical disabilities in SDL experiments and the development of short videos and science presentations for public events.<br/><br/>Using unique multi-purpose SDLs, CAPs will establish a game-changing research program to thoroughly comprehend and accelerate fundamental studies of emerging photo(bio)catalysis for small molecules. Specific reactions to be investigated include: i) photoenzymatic alkene functionalization (ene-reductase) that departs from libraries of alkyl halides and alkenes and ii) asymmetric dual-catalyst photoreactions in parallel with iii) the accelerated discovery of high-photostability dyes and chromogenic photostabilizers using cheminformatics. The resultant photochemistry knowledge gleaned from explorations in the first research thrust will be extended to achieve hydrotrifluoromethylation using photoenzymatic conditions for the first time, along with developing regioselective arene functionalization chemistry. Baseline and quantitative photochemical parameters will be assessed to formulate reaction conditions leading to successful transformations targeting unique approaches towards preparing valuable small molecules (human-driven scientific discovery). Armed with this information, CAPs will rapidly explore/exploit the high-dimensional reaction space using the existing SDL infrastructure at NC State. Physical- and molecular-based ML scoring parameters will be implemented to quantitatively assess the large body of experimental data generated in the SDL experiments. This will provide critical feedback to the experimentalists (data-driven chemical discoveries). The robotic ‘co-pilot,’ developed and deployed in CAPs, will significantly reduce the time required to find the most suitable photocatalyst(s) and substrate scope(s) for photoenzymatic and photocatalytic transformations that could not be achieved using traditional batch experimentation approaches. In this way, photoactivated synthetic methodologies can be explored to benchmark all relevant parameters impacting autonomous robotic experimentation platforms, ultimately paving the way to newly conceived chemical transformations.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
