Coupled-cluster and density functional theory studies of the electronic excitation spectra of trans-1,3-butadiene and trans-2-propeniminium

2009 ◽  
Vol 131 (2) ◽  
pp. 024301 ◽  
Author(s):  
Olli Lehtonen ◽  
Dage Sundholm ◽  
Robert Send ◽  
Mikael P. Johansson
Keyword(s):  
Density Functional Theory ◽  
Density Functional ◽  
Electronic Excitation ◽  
Coupled Cluster ◽  
Excitation Spectra ◽  
Functional Theory

Coupled-cluster and density functional theory studies of the electronic 0–0 transitions of the DNA bases

2014 ◽  
Vol 16 (15) ◽  
pp. 6931-6941 ◽  
Author(s):  
Vasily A. Ovchinnikov ◽  
Dage Sundholm
Keyword(s):  
Density Functional Theory ◽  
Linear Response ◽  
Density Functional ◽  
Electronic Excitation ◽  
Dna Bases ◽  
Coupled Cluster ◽  
Excitation Spectra ◽  
Functional Theory

The 0–0 transitions of the electronic excitation spectra of the lowest tautomers of the four nucleotide (DNA) bases have been studied using linear-response approximate coupled-cluster singles and doubles (CC2) calculations.

scholarly journals A computational study for the reaction mechanism of metal-free cyanomethylation of aryl alkynoates with acetonitrile

RSC Advances ◽  
2021 ◽  
Vol 11 (30) ◽  
pp. 18246-18251
Author(s):  
Selçuk Eşsiz
Keyword(s):  
Density Functional Theory ◽  
Reaction Mechanism ◽  
Density Functional ◽  
Computational Study ◽  
Coupled Cluster ◽  
Functional Theory ◽  
Metal Free ◽  
Coupled Cluster Methods ◽  
High Level ◽  
Cluster Methods

A computational study of metal-free cyanomethylation and cyclization of aryl alkynoates with acetonitrile is carried out employing density functional theory and high-level coupled-cluster methods, such as [CCSD(T)].

Excitation Spectra in the Time-Dependent Density-Functional Theory with Gradient Correction

1999 ◽  
Vol 579 ◽  
Author(s):  
Naoto Uimezawa ◽  
Susumu Saito
Keyword(s):  
Density Functional Theory ◽  
Density Functional ◽  
Local Density ◽  
Oscillator Strengths ◽  
Time Dependent ◽  
Basis Set ◽  
Excitation Spectra ◽  
Functional Theory ◽  
Gradient Correction ◽  
Dependent Density

ABSTRACTWe study tile optical absorption spectra of Na clusters using the time-dependent density-functional theory with gradient correction. A jellium-sphere background model, which is free from basis-set incompleteness error and is suitable for the comparison of various theoretical methods, is adopted. For energies of surface-plasinon excitations governing profiles of photoabsorption spectra with huge oscillator strengths., the gradient correction by van Leeiiwen and Baerends with correct asymptotic behavior of the effective potential is found to show considerable improvement over the time-dependent local-density approximation.

scholarly journals The ANI-1ccx and ANI-1x Data Sets, Coupled-Cluster and Density Functional Theory Properties for Molecules

2020 ◽  
Author(s):  
Justin S. Smith ◽  
Roman Zubatyuk ◽  
Benjamin T. Nebgen ◽  
Nicholas Lubbers ◽  
Kipton Barros ◽  
...  
Keyword(s):  
Density Functional Theory ◽  
Potential Energy Surfaces ◽  
Density Functional ◽  
Atomic Charge ◽  
Density Functional Theory Calculations ◽  
Coupled Cluster ◽  
Data Sets ◽  
Data Set ◽  
Functional Theory ◽  
Energy Surfaces

<p>Maximum diversification of data is a central theme in building generalized and accurate machine learning (ML) models. In chemistry, ML has been used to develop models for predicting molecular properties, for example quantum mechanics (QM) calculated potential energy surfaces and atomic charge models. The ANI-1x and ANI-1ccx ML-based eneral-purpose potentials for organic molecules were developed through active learning; an automated data diversification process. Here, we describe the ANI-1x and ANI-1ccx data sets. To demonstrate data set diversity, we visualize them with a dimensionality reduction scheme, and contrast against existing data sets. The ANI-1x data set contains multiple QM properties from 5M density functional theory calculations, while the ANI-1ccx data set contains 500k data points obtained with an accurate CCSD(T)/CBS extrapolation. Approximately 14 million CPU core-hours were expended to generate this data. Multiple QM properties from density functional theory and coupled cluster are provided: energies, atomic forces, multipole moments, atomic charges, and more. We provide this data to the community to aid research and development of ML models for chemistry.</p>

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