Current technological advances in computing and robotics are revolutionizing almost everything around us, from industrial manufacturing to the entertainment industry. The Pollice group seeks to implement these technological advances in the realm of organic chemistry to tackle a problem that has fascinated chemists for more than two centuries, the design of new catalysts. Our group will combine automated experimentation with computational screening and machine learning to accelerate the development of catalytic organic reactions. To achieve that, we welcome scientists from various fields to build an interdisciplinary team.

Just like a researcher documents the outcome of previous experiments and uses this information to plan subsequent ones, some of the most efficient optimization algorithms rely on continuous feedback loops using the data collected most efficiently. Hence, we interface computer algorithms tasked with finding the best catalyst for a chemical reaction with chemistry labs. Using the data that we will collect during closed-loop catalyst optimization, our group will integrate, refine, and benchmark molecular design algorithms and use them to create new molecular catalysts.