Predictive catalysis: a valuable step towards machine learning

Abstract

As physical chemistry transitioned to computational chemistry, a new growth occurred in the field with the advent of predictive catalysis, making it a key player in the optimization and development of catalytic processes. Predictive catalysis refers to the use of computational and theoretical methods to predict the properties and behavior of chemical systems and, more specifically, their catalytic activity and selectivity. In this analysis, we take a look at what predictive catalysis has done to date and build a picture of how far it can go in the future, while also outlining the challenges that need to be resolved to make it a powerful tool of general applicability