Evaluating the Performance of the Exact Integral Simplified Time-Dependent Density Functional Theory (XsTD-DFT) to Compute One- and Two-Photon Absorption
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https://figshare.com/articles/dataset/Evaluating_the_Performance_of_the_Exact_Integral_Simplified_Time-Dependent_Density_Functional_Theory_XsTD-DFT_to_Compute_One-_and_Two-Photon_Absorption/29973620
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资源简介:
Computing one-photon absorption and
two-photon absorption (1PA
and 2PA) of large molecular systems using an all-atom quantum mechanical
(AQM) methodology presents significant computational challenges. This
study evaluates the performance of the exact integral simplified time-dependent
density functional theory (XsTD-DFT) method, a new recently introduced
simplified quantum chemistry (sQC) approach that can be used as a
key ingredient for AQM workflows to compute 1PA and 2PA. The reliability, robustness, and computational
efficiency of the XsTD-DFT scheme are assessed against RI-CC2
reference calculations as well as with respect to TD-DFT results for
a set of 91 organic molecules that includes systems from the QUEST
database, medium-sized push–pull molecules, and small microhydrated
clusters. The impact of various exchange–correlation functionals,
basis sets, and the single energy threshold used to truncate the CIS
space in the XsTD-DFT procedure is investigated. Results show that
the XsTD-DFT method provides a substantial computational speed-up
compared to TD-DFT, up to 3 orders of magnitude in CPU time with an
energy threshold of 9 eV. The method robustly reproduces TD-DFT trends
for excitation energies, oscillator strengths, and 2PA strengths.
XsTD-DFT demonstrates reliability in capturing structure–property
relationships and is reliable for nonequilibrium geometries as well
as microhydrated systems. Comparisons with respect to experimental
1PA and 2PA spectra recorded in solution show similar agreements for
the XsTD-DFT scheme than for TD-DFT. Guidelines for using the XsTD-DFT
method in the context of 1PA and 2PA are provided. This study concludes
that XsTD-DFT is a reliable, robust, and computationally efficient method to compute
1PA and 2PA, making it well-suited as a key ingredient for AQM workflows
to treat realistic systems.
创建时间:
2025-08-23



