SYVA: A program to analyze symmetry of molecules based on vector algebra

Gyevi-Nagy, László; Tasi, Gyula

doi:10.1016/j.cpc.2017.01.019

Cited by 14 publications

(4 citation statements)

References 22 publications

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“…Training datasets for our machine-learning model can be easily enriched using the point group symmetries. To extract the point group symmetries and the corresponding transformation matrices we used the SYVA software package 95 . Consequently, we can multiply the size of the training set by the number of point group symmetries without performing any additional quantum chemical calculations simply by applying the point group transformations on our existing data.…”

Section: Methodsmentioning

confidence: 99%

Quantum chemical accuracy from density functional approximations via machine learning

et al. 2020

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Kohn-Sham density functional theory (DFT) is a standard tool in most branches of chemistry, but accuracies for many molecules are limited to 2-3 kcal ⋅ mol−1 with presently-available functionals. Ab initio methods, such as coupled-cluster, routinely produce much higher accuracy, but computational costs limit their application to small molecules. In this paper, we leverage machine learning to calculate coupled-cluster energies from DFT densities, reaching quantum chemical accuracy (errors below 1 kcal ⋅ mol−1) on test data. Moreover, density-based Δ-learning (learning only the correction to a standard DFT calculation, termed Δ-DFT ) significantly reduces the amount of training data required, particularly when molecular symmetries are included. The robustness of Δ-DFT is highlighted by correcting “on the fly” DFT-based molecular dynamics (MD) simulations of resorcinol (C6H4(OH)2) to obtain MD trajectories with coupled-cluster accuracy. We conclude, therefore, that Δ-DFT facilitates running gas-phase MD simulations with quantum chemical accuracy, even for strained geometries and conformer changes where standard DFT fails.

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Section: Methodsmentioning

confidence: 99%

Quantum chemical accuracy from density functional approximations via machine learning

et al. 2020

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“…A harmonic frequency analysis was also performed to verify a stationary local minimum for all the optimized structures. The punctual group for each cluster was determined using the SYVA program [ 39 ] and the symmetry analyser module included in the Python Materials Genomics library [ 40 ].…”

Section: Methodology and Computational Detailsmentioning

confidence: 99%

Structural and optical properties of the Ag _n –tyrosine complexes ( n = 3−12): a density functional theory study

Balan,

Morato-Márquez,

Torres-Torres

et al. 2023

R. Soc. open sci.

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We study the optical properties of Ag n ( n = 3–12) neutral clusters and their coordination with a tyrosine (Tyr) molecule. A global search strategy coupled with density functional theory (DFT) computations explored the potential energy surface. Adsorption energy calculations predicted that Tyr coordination stabilizes the metal clusters, favouring the Ag n −Tyr complexes with an even number of silver atoms. For the Ag n low-lying isomers, the general shape and the major transitions of the calculated time dependent-DFT (TD-DFT) absorption spectra align with those of previous reports measured in an argon environment. We use the analysis of non-covalent interactions to identify the specific interactions between each silver cluster and functional groups of Tyr. The TD-DFT absorption spectra for the Ag n −Tyr complexes showed that Tyr significantly modifies the optical properties of the coordinated silver clusters and affects the smaller systems to a greater extent. The optical absorption results of the bare Ag n clusters and the Ag n −Tyr complexes are compared and discussed in detail.

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“…Upon termination of the constrained geometry optimization, the point-group symmetry of the cSP is identified with the SYVA (SYmmetry analyzer using Vector Algebra) code in an automated way (the distortion tolerance parameter , is set to 2 mÅ). After recognition of the highest point group, the analyzed geometry is symmetrized by SYVA and replaces that obtained by .…”

Section: The Codementioning

confidence: 99%

“…Comparison of Selected Quantum-Chemical Quantities Characterizing the Global Minimum, WW 1 , of the Water Dimer, Obtained via Different Approaches ab SYmmetry analyzer using Vector Algebra 63 )62 code in an automated way (the distortion tolerance parameter62,63 is set to 2 mÅ). After recognition of the highest point group, the analyzed geometry is symmetrized by SYVA and replaces that obtained by oligoCGO.…”

mentioning

confidence: 99%

Normal-Mode Vibrational Analysis of Weakly Bound Oligomers at Constrained Stationary Points of Arbitrary Order

Tóbiás

Árendás

Császár

2022

J. Chem. Theory Comput.

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Following the full realization of the importance of noncovalent interactions, finding and characterizing stationary points (SP), of various order, for weakly bound oligomers have become important tasks for computational chemists. An efficient algorithm and an associated computer code, called oligoCGO, are described, facilitating constrained geometry optimization of oligomers of arbitrary structure and complexity and normal-mode vibrational analysis at nonstationary geometries. To minimize the adverse effects of nonzero forces on harmonic vibrational analyses at constrained stationary points (cSP), two residual gradient correction (RGC) schemes are proposed. RGC 1 , for which a rigorous justification is given, is based on ignoring the remaining forces in internal-coordinate space. RGC 2 modifies the geometry of the cSP in a single Newton step and recalculates the Cartesian Hessian at this updated geometry. As demonstrated by 10 examples related to the water−water, water− methane, and methane−methane dimers as well as the methane trimer, without RGC the harmonic analysis of cSPs may result in even qualitatively incorrect results when compared to reference values obtained at the nearby unconstrained SPs (uSP). Both RGC protocols work exceedingly well, and the corrected harmonic wavenumbers of the cSPs are very close to their uSP counterparts.

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SYVA: A program to analyze symmetry of molecules based on vector algebra

Cited by 14 publications

References 22 publications

Quantum chemical accuracy from density functional approximations via machine learning

Quantum chemical accuracy from density functional approximations via machine learning

Structural and optical properties of the Ag _n –tyrosine complexes ( n = 3−12): a density functional theory study

Normal-Mode Vibrational Analysis of Weakly Bound Oligomers at Constrained Stationary Points of Arbitrary Order

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SYVA: A program to analyze symmetry of molecules based on vector algebra

Cited by 14 publications

References 22 publications

Quantum chemical accuracy from density functional approximations via machine learning

Quantum chemical accuracy from density functional approximations via machine learning

Structural and optical properties of the Ag n –tyrosine complexes ( n = 3−12): a density functional theory study

Normal-Mode Vibrational Analysis of Weakly Bound Oligomers at Constrained Stationary Points of Arbitrary Order

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Structural and optical properties of the Ag _n –tyrosine complexes ( n = 3−12): a density functional theory study