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使用人工力诱导反应方法的计算催化。

Computational Catalysis Using the Artificial Force Induced Reaction Method.

机构信息

Fukui Institute for Fundamental Chemistry, Kyoto University , Kyoto 606-8103, Japan.

Department of Chemistry, Hokkaido University , Sapporo 060-0810, Japan.

出版信息

Acc Chem Res. 2016 Apr 19;49(4):763-73. doi: 10.1021/acs.accounts.6b00023. Epub 2016 Mar 29.

Abstract

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.

摘要

人工力诱导反应 (AFIR) 方法是全局反应路线映射 (GRRM) 策略中的一种自动方法,用于探索复杂反应的所有重要反应路径。大多数传统的计算催化方法都需要猜测反应路径。另一方面,AFIR 方法可以在不猜测的情况下定位反应路径的局部最小值 (LM) 和过渡态 (TS),从而找到预期和非预期的反应路径。AFIR 方法已应用于多组分有机反应,如醛醇反应、Passerini 反应、Biginelli 反应和相转移催化。在存在多种反应物的情况下,可能存在多个平衡结构,从而导致多个反应途径。GRRM 策略中的 AFIR 方法可以系统地确定所有重要的平衡结构和随后的反应路径。由于 AFIR 搜索是完全自动的,因此可以消除用户的全面尝试和错误以及猜测和检查过程。同时,AFIR 搜索是系统的,因此可以更准确和全面地确定反应机制。AFIR 方法已用于研究过渡金属催化中的全催化循环和反应步骤,如钴催化的醛醇加成反应和铁催化的水相碳-碳键形成反应。一些 AFIR 应用针对过渡金属催化不对称反应的选择性决定步骤,包括立体选择性水稳定镧系元素路易斯酸催化 Mukaiyama 醛醇反应。在建立反应的选择性方面,过渡态的系统采样至关重要。在这方面,AFIR 非常有助于对 TS 进行系统和自动确定。在对过渡态进行全面描述的情况下,可以更准确地计算反应的选择性。对于相对较大的分子系统,可以使用 ONIOM(QM:QM) 或 ONIOM(QM:MM) 方法降低 AFIR 搜索的计算成本。在实际应用中,通常使用相对较小基组的密度泛函理论 (DFT) 进行高级计算,而使用半经验方法或力场描述进行低级计算。在确定近似的 LM 和 TS 之后,使用标准计算方法(例如,具有较大基组的 DFT)对整个分子系统进行计算,以确定真正的 LM 和 TS,并对催化反应的反应机制和选择性进行合理化。本账户中的示例证明,AFIR 方法是准确预测复杂催化反应反应机制和选择性的有力方法。因此,GRRM 策略中的 AFIR 方法对于计算催化非常有用。

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