Computational Organometallic Catalysis: Where We Are, Where We Are Going

This essay gives my personal perspective of the current stage of computational methods applied to modeling organometallic catalysis, as well as the new directions the field is taking. The first part of the essay deals with what I consider the state-of-the-art to build up energy profiles, regarding both chemical and computational models. With a proper choice of the chemical model and computational methods, quantum mechanical calculations are nowadays able to provide accurate energy profiles of organometallic reactions in solution involving closed-shell species. However, in most cases they are still used to predict the past, providing after-the-fact explanations and missing out the full potential of contemporary simulation techniques. Simulations are mature enough to be incorporated at the design stage and to guide the experimental exploration. The new directions the field is taking, incorporating automated exploration methods and combined with extensive data analysis and machine learning algorithms, approach the holy grail of catalyst discovering.

Automated summary

Quantum mechanical calculations can provide accurate energy profiles of organometallic reactions, but are often used to predict the past rather than tapping into the full potential of current simulation techniques. New directions include automated exploration methods and machine learning algorithms, getting closer to the ultimate goal of catalyst discovery.