Artificial Force Induced Reaction Research Articles

Exploring Potential Energy Surfaces of Large Systems with Artificial Force Induced Reaction Method in Combination with ONIOM and Microiteration

Development of efficient methods for finding chemical reaction pathways has been one of the central subjects of theoretical chemistry. Recently, the artificial force induced reaction (AFIR) method enabled automated search for associative reaction pathways between multiple reactant molecules and has been applied to reactions involving a few tens of atoms. To expand its applicability to large systems, we combined it with the geometrical microiteration technique. With this extension, full optimization of transition state structures of enzymatic reactions in the protein became possible within the QM/MM framework. Performance of the microiteration-AFIR method was tested for a single water catalyzed Aldol reaction in (H2O)299 cluster and for an enzymatic reaction of the isopenicillin N synthase, where the potential energy surfaces were calculated by the ONIOM(QM/MM) method. These numerical tests demonstrated that the present method is promising in predicting reaction pathways that take place within an active site (consisting of tens of atoms) in a very large environment such as protein and solution.

Toward Predicting Full Catalytic Cycle Using Automatic Reaction Path Search Method: A Case Study on HCo(CO)3-Catalyzed Hydroformylation

Toward systematic prediction of reaction pathways in complex chemical reaction systems by quantum chemical calculations, a new automatic reaction path search approach has been proposed on the basis of the artificial force induced reaction (AFIR) method [J. Chem. Theory Comput.2011, 7, 2335-2345.]. We demonstrate in this Letter that this approach enabled semiautomatic determination of the full catalytic cycle of the HCo(CO)3-catalyzed hydroformylation. The search was fully systematic; no initial guess was required concerning the entire reaction mechanism as well as each transition-state structure. This approach opens the door to nonempirical prediction of complex reaction mechanisms involving multiple steps in multiple pathways, such as full cycles of catalytic reactions.

Finding Reaction Pathways of Type A + B → X: Toward Systematic Prediction of Reaction Mechanisms

In these five decades, many useful tools have been developed for exploring quantum chemical potential energy surfaces. The success in theoretical studies of chemical reaction mechanisms has been greatly supported by these tools. However, systematic prediction of reaction mechanisms starting only from given reactants and catalysts is still very difficult. Toward this goal, we describe the artificial force induced reaction (AFIR) method for automatically finding reaction paths of type A + B → X (+ Y). By imposing an artificial force to given reactants and catalysts, the method can find the reactive sites very efficiently. Further pressing by the artificial force provides approximate transition states and product structures, which can be easily reoptimized to the corresponding true ones. This procedure can be executed very efficiently just by minimizing a single function called the AFIR function. All important reaction paths can be found by repeating this cycle starting from many initial orientations. We also discuss perspectives of automated reaction path search methods toward the above goal.

Finding Minimum Structures on the Seam of Crossing in Reactions of Type A + B → X: Exploration of Nonadiabatic Ignition Pathways of Unsaturated Hydrocarbons.

A new theoretical approach is proposed for finding automatically minimum structures on the seam of crossing (MSX) in reactions of type A + B → X, where the artificial-force-induced reaction (AFIR) method is combined with the seam model function (SMF) approach. Its application to reactions between triplet dioxygen and unsaturated hydrocarbons provided many MSX structures. In addition to known ignition pathways, we discovered a pathway through a new type of MSX in the reaction of dioxygen with aromatic hydrocarbons; for benzene, this new pathway requires a lower energy than those of three known ignition pathways and is likely to be the most important. This demonstrates that the AFIR-SMF approach has the ability to discover unknown/unexpected MSX structures without prejudice for presumed pathways or mechanisms.