Integrated In Silico Design of Catalysts and Processes based on Quantum Chemistry

Abstract

Most chemical processes rely on suitable catalysts. Thus, selecting the right catalyst for a process is an important task in chemical process design. However, searching new catalysts can be very tedious. Therefore, computer-aided molecular design (CAMD) methods are very desirable to identify promising candidate catalysts in silico and thereby minimize experimental effort. However, methods for computational catalyst design are still in their infancy and often focus on the catalyst turnover number and frequency only while the best catalyst is the one that maximizes the overall process performance. In this work, we therefore propose a method for computer-aided molecular and process design (CAMPD) of catalysts and the corresponding process. A key element is the efficient but accurate prediction of reaction kinetics with advanced quantum chemical methods. We demonstrate the design method for catalytic carbamate cleavage and show that only the integrated catalyst and process design identifies the catalysts that maximize process performance.