Abstract

The validation of reaction mechanisms, usually combining electronic structure calculations and transition-state theory, stands as one of the most powerful examples of computational chemistry in action, routinely used to rationalize catalytic mechanisms, design new catalytic species, explain stereochemical outcomes and derive macroscopic rate laws.

But how do we proceed if a reaction mechanism is unknown? In such cases, automated reaction discovery tools are rapidly emerging as a powerful computational approach to complement and support experimental mechanistic investigations.

In this talk, I will highlight my group’s recent work in the field of automated reaction discovery, and show how the challenge of proposing valid reaction mechanisms can be cast as a problem in discrete optimization. Using recent examples from homogeneous catalysis, combustion chemistry and astrochemistry, I will show how our optimization approach can generate large reaction-mechanism datasets which can be sifted using electronic structure theory to identify candidate mechanistic proposals; I will also highlight remaining challenges and possible solutions.