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通过自动多参考计算轻松准确地实现有机反应活性

Organic Reactivity Made Easy and Accurate with Automated Multireference Calculations.

作者信息

Wardzala Jacob J, King Daniel S, Ogunfowora Lawal, Savoie Brett, Gagliardi Laura

机构信息

Department of Chemistry,University of Chicago, Chicago, Illinois 60637, United States.

Davidson School of Chemical Engineering, Purdue University, West Lafayette, Indiana 47906, United States.

出版信息

ACS Cent Sci. 2024 Mar 27;10(4):833-841. doi: 10.1021/acscentsci.3c01559. eCollection 2024 Apr 24.

DOI:10.1021/acscentsci.3c01559
PMID:38680571
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11046455/
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.

摘要

在有机反应活性研究中,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关键作用。虽然像密度泛函理论(DFT)和耦合簇理论(如CCSD(T))这样的普遍黑箱方法极大地推进了我们对化学反应活性的理解,但它们在描述多构型过渡态和中间体方面常常存在不足。要实现更准确的描述就需要使用多参考方法。然而,由于缺乏专家输入时这些方法的预测往往有误,它们尚未得到大规模应用。在这里,我们通过自动多构型对密度泛函理论(MC-PDFT)计算克服了这一缺陷。我们将此方法应用于908个自动生成的有机反应。我们发现其中68%的反应呈现出显著的多构型特征,在这些反应中,自动多构型方法通常比DFT和CCSD(T)提供更准确和/或更高效的描述。这项工作展示了自动多构型方法在反应活性方面的首次高通量应用,这得益于自动活性空间选择算法以及基于MC-PDFT泛函的电子相关计算。这种方法可以以黑箱方式使用,避免在单参考和多参考情况下出现显著的活性空间不一致误差,并在需要时提供准确的多构型描述。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4706/11046455/5cbb86f840a8/oc3c01559_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4706/11046455/0e4f130a3dfa/oc3c01559_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4706/11046455/0c54b291dca8/oc3c01559_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4706/11046455/c6399040261c/oc3c01559_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4706/11046455/c30d717a0fc5/oc3c01559_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4706/11046455/5cbb86f840a8/oc3c01559_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4706/11046455/0e4f130a3dfa/oc3c01559_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4706/11046455/0c54b291dca8/oc3c01559_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4706/11046455/c6399040261c/oc3c01559_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4706/11046455/c30d717a0fc5/oc3c01559_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4706/11046455/5cbb86f840a8/oc3c01559_0005.jpg

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