Computation and Experiment: A Powerful Combination to Understand and Predict Reactivities

Area of Science:

• Computational chemistry
• Organic chemistry
• Organometallic chemistry

Background:

• Computational chemistry is a vital tool for understanding chemical phenomena and molecular properties.
• Advances in theory, hardware, and software enable accurate and rapid molecular process calculations.
• This field is crucial for studying organic and organometallic reactivities.

Purpose of the Study:

• To highlight the broad applications of computational chemistry in organic and organometallic reactivities.
• To showcase the synergistic interplay between computational and experimental methods.
• To demonstrate how computational chemistry can rationalize and predict chemical reactivities.

Main Methods:

• Review of computational chemistry applications in catalysis (NHC-, Cu-, Pd-, Ni-catalyzed) and noncatalytic reactions.
• Emphasis on the combined approach of computation and experimentation.
• Analysis of mechanistic features, stereoselectivity, ligand effects, and active catalytic species.

Main Results:

• Computational chemistry successfully rationalizes mechanisms (e.g., radical vs. polar) and stereoselectivity in NHC-catalyzed reactions.
• Ligand effects on catalytic activity and selectivity in Pd- and Ni-catalyzed reactions were elucidated.
• Identification of active catalytic species in Pd-catalyzed cross-coupling reactions and exploration of dinuclear Pd(I) cycles.
• Factors controlling C-H vs. C-C activation in Cu-catalyzed oxidations and Ni-catalyzed trifluoromethylthiolations were detailed.

Conclusions:

• The synergistic interplay of computation and experiments provides deeper insights than isolated techniques.
• This integrated approach inspires novel chemical pathways and aids in reaction development.
• Computational predictions, when experimentally verified, accelerate the design of new catalysts and reaction conditions.