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使用含时密度泛函理论和动力学路径积分方法预测有机小分子磷光速率。

Predicting Phosphorescence Rates of Light Organic Molecules Using Time-Dependent Density Functional Theory and the Path Integral Approach to Dynamics.

机构信息

Departmento de Química , Universidade Federal de Santa Catarina , Florianópolis , Santa Catarina 88040-900 , Brazil.

Max-Planck-Institut für Kohlenforschung , Mülheim an der Ruhr 45470 , Germany.

出版信息

J Chem Theory Comput. 2019 Mar 12;15(3):1896-1904. doi: 10.1021/acs.jctc.8b00841. Epub 2019 Feb 15.

DOI:10.1021/acs.jctc.8b00841
PMID:30721046
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6728062/
Abstract

In this work, we present a general method for predicting phosphorescence rates and spectra for molecules using time-dependent density functional theory (TD-DFT) and a path integral approach for the dynamics that relies on the harmonic oscillator approximation for the nuclear movement. We first discuss the theory involved in including spin-orbit coupling (SOC) among singlet and triplet excited states and then how to compute the corrected transition dipole moments and phosphorescence rates. We investigate the dependence of these rates on some TD-DFT parameters, such as the nature of the functional, the number of roots, and the Tamm-Dancoff approximation. After that, we evaluate the effect of different SOC integral schemes and show that our best method is applicable to a large number of systems with different excited state characters.

摘要

在这项工作中,我们提出了一种使用含时密度泛函理论(TD-DFT)和基于核运动的谐振子近似的路径积分方法来预测分子磷光速率和光谱的通用方法。我们首先讨论了在单重态和三重态激发态之间包含自旋轨道耦合(SOC)的理论,然后讨论了如何计算修正的跃迁偶极矩和磷光速率。我们研究了这些速率对一些 TD-DFT 参数的依赖性,例如泛函的性质、根的数量和 Tamm-Dancoff 近似。之后,我们评估了不同 SOC 积分方案的影响,并表明我们的最佳方法适用于具有不同激发态特性的大量系统。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b758/6728062/8ea033ba1ff0/ct-2018-00841a_0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b758/6728062/c331a1ce401e/ct-2018-00841a_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b758/6728062/12bfff7b027b/ct-2018-00841a_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b758/6728062/cafb3cbee554/ct-2018-00841a_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b758/6728062/378c8b3e7d91/ct-2018-00841a_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b758/6728062/de508069b675/ct-2018-00841a_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b758/6728062/8ea033ba1ff0/ct-2018-00841a_0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b758/6728062/c331a1ce401e/ct-2018-00841a_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b758/6728062/12bfff7b027b/ct-2018-00841a_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b758/6728062/cafb3cbee554/ct-2018-00841a_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b758/6728062/378c8b3e7d91/ct-2018-00841a_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b758/6728062/de508069b675/ct-2018-00841a_0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b758/6728062/8ea033ba1ff0/ct-2018-00841a_0006.jpg

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