The fields of theoretical and computational chemistry have come a long way since their inception in the mid-20th century. Fifty years ago, only rudimentary approximations for very simple molecules could be performed. Thanks in part to the ongoing development of very fast computers, and the efforts of theoretical chemists in developing fast and accurate quantum mechanical (QM) methods for calculating electronic energies of atoms and molecules, theoretical and computational chemistry can now give reliable geometries, energies, reactivities, and electronic properties for molecules. Such information has become indispensable in understanding and explaining experimental results that would be otherwise difficult to interpret

The artificial force induced reaction (AFIR) method in the global reaction route mapping (GRRM) strategy is an automatic approach to explore all important reaction paths of complex reactions. Most traditional methods in computational catalysis require guess reaction paths. On the other hand, the AFIR approach locates local minima (LMs) and transition states (TSs) of reaction paths without a guess, and therefore finds unanticipated as well as anticipated reaction paths. The AFIR method has been applied for multicomponent organic reactions, such as the aldol reaction, Passerini reaction, Biginelli reaction, and phase-transfer catalysis. In the presence of several reactants, many equilibrium structures are possible, leading to a number of reaction pathways. The AFIR method in the GRRM strategy determines all of the important equilibrium structures and subsequent reaction paths systematically. As the AFIR search is fully automatic, exhaustive trial-and-error and guess-and-check processes by the user can be eliminated. At the same time, the AFIR search is systematic, and therefore a more accurate and comprehensive description of the reaction mechanism can be determined. The AFIR method has been used for the study of full catalytic cycles and reaction steps in transition metal catalysis, such as cobalt-catalyzed hydroformylation and iron-catalyzed carbon–carbon bond formation reactions in aqueous media. Some AFIR applications have targeted the selectivity-determining step of transition-metal-catalyzed asymmetric reactions, including stereoselective water-tolerant lanthanide Lewis acid-catalyzed Mukaiyama aldol reactions. In terms of establishing the selectivity of a reaction, systematic sampling of the transition states is critical. In this direction, AFIR is very useful for performing a systematic and automatic determination of TSs. In the presence of a comprehensive description of the transition states, the selectivity of the reaction can be calculated more accurately. For relatively large molecular systems, the computational cost of AFIR searches can be reduced by using the ONIOM(QM:QM) or ONIOM(QM:MM) methods. In common practice, density functional theory (DFT) with a relatively small basis set is used for the high-level calculation, while a semiempirical approach or a force field description is used for the low-level calculation. After approximate LMs and TSs are determined, standard computational methods (e.g., DFT with a large basis set) are used for the full molecular system to determine the true LMs and TSs and to rationalize the reaction mechanism and selectivity of the catalytic reaction. The examples in this Account evidence that the AFIR method is a powerful approach for accurate prediction of the reaction mechanisms and selectivities of complex catalytic reactions. Therefore, the AFIR approach in the GRRM strategy is very useful for computational catalysis.