Organic Reactivity Made Easy and Accurate with Automated Multireference Calculations

IF 12.7 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY ACS Central Science Pub Date : 2024-03-27 DOI:10.1021/acscentsci.3c01559
Jacob J. Wardzala, Daniel S. King, Lawal Ogunfowora, Brett Savoie and Laura Gagliardi*, 
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Abstract

In organic reactivity studies, quantum chemical calculations play a pivotal role as the foundation of understanding and machine learning model development. While prevalent black-box methods like density functional theory (DFT) and coupled-cluster theory (e.g., CCSD(T)) have significantly advanced our understanding of chemical reactivity, they frequently fall short in describing multiconfigurational transition states and intermediates. Achieving a more accurate description necessitates the use of multireference methods. However, these methods have not been used at scale due to their often-faulty predictions without expert input. Here, we overcome this deficiency with automated multiconfigurational pair-density functional theory (MC-PDFT) calculations. We apply this method to 908 automatically generated organic reactions. We find 68% of these reactions present significant multiconfigurational character in which the automated multiconfigurational approach often provides a more accurate and/or efficient description than DFT and CCSD(T). This work presents the first high-throughput application of automated multiconfigurational methods to reactivity, enabled by automated active space selection algorithms and the computation of electronic correlation with MC-PDFT on-top functionals. This approach can be used in a black-box fashion, avoiding significant active space inconsistency error in both single- and multireference cases and providing accurate multiconfigurational descriptions when needed.

We introduce an approach that automates accurate calculations of hundreds of organic reactions, based on multiconfigurational pair-density functional theory.

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自动多参比计算让有机反应性变得简单准确
在有机反应性研究中,量子化学计算作为理解和机器学习模型开发的基础,发挥着举足轻重的作用。虽然密度泛函理论(DFT)和耦合簇理论(如 CCSD(T))等流行的黑箱方法极大地推动了我们对化学反应性的理解,但它们在描述多构型过渡态和中间产物方面往往存在不足。要实现更精确的描述,就必须使用多参比方法。然而,由于这些方法在没有专家输入的情况下经常预测失误,因此尚未大规模使用。在这里,我们通过自动多构型对密度泛函理论(MC-PDFT)计算克服了这一不足。我们将这种方法应用于 908 个自动生成的有机反应。我们发现这些反应中有 68% 具有显著的多构型特征,其中自动多构型方法往往能提供比 DFT 和 CCSD(T) 更准确和/或更有效的描述。这项研究首次将自动多构型方法高通量地应用于反应性研究,通过自动活性空间选择算法和 MC-PDFT 顶层函数计算电子相关性来实现。这种方法可以黑箱方式使用,在单引用和多引用情况下都能避免显著的活性空间不一致性误差,并在需要时提供精确的多配置描述。
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来源期刊
ACS Central Science
ACS Central Science Chemical Engineering-General Chemical Engineering
CiteScore
25.50
自引率
0.50%
发文量
194
审稿时长
10 weeks
期刊介绍: ACS Central Science publishes significant primary reports on research in chemistry and allied fields where chemical approaches are pivotal. As the first fully open-access journal by the American Chemical Society, it covers compelling and important contributions to the broad chemistry and scientific community. "Central science," a term popularized nearly 40 years ago, emphasizes chemistry's central role in connecting physical and life sciences, and fundamental sciences with applied disciplines like medicine and engineering. The journal focuses on exceptional quality articles, addressing advances in fundamental chemistry and interdisciplinary research.
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