Rotational spectra and equilibrium structures of H2SiS and Si2S

2011 ◽  
Vol 134 (3) ◽  
pp. 034306 ◽  
Author(s):  
Michael C. McCarthy ◽  
Carl A. Gottlieb ◽  
Patrick Thaddeus ◽  
Sven Thorwirth ◽  
Jürgen Gauss
Keyword(s):  
Rotational Spectra ◽  
Equilibrium Structures

Rotational spectra of 1-chloro-2-fluoroethylene. II. Equilibrium structures of the cis and trans isomer

2006 ◽  
Vol 125 (5) ◽  
pp. 054307 ◽  
Author(s):  
Cristina Puzzarini ◽  
Gabriele Cazzoli ◽  
Alberto Gambi ◽  
Jürgen Gauss
Keyword(s):  
Trans Isomer ◽  
Rotational Spectra ◽  
Equilibrium Structures ◽  
Cis And Trans

Rotational Spectra of CH2DCCH and CH3CCD: Experimental and ab Initio Equilibrium Structures of Propyne

1993 ◽  
Vol 160 (2) ◽  
pp. 471-490 ◽  
Author(s):  
M. Leguennec ◽  
J. Demaison ◽  
G. Wlodarczak ◽  
C.J. Marsden
Keyword(s):  
Ab Initio ◽  
Rotational Spectra ◽  
Equilibrium Structures

ChemInform Abstract: Rotational Spectra of CH2DCCH and CH3CCD: Experimental and ab initio Equilibrium Structures of Propyne.

ChemInform ◽  
2010 ◽  
Vol 24 (44) ◽  
pp. no-no
Author(s):  
M. LE GUENNEC ◽  
J. DEMAISON ◽  
G. WLODARCZAK ◽  
C. J. MARSDEN
Keyword(s):  
Ab Initio ◽  
Rotational Spectra ◽  
Equilibrium Structures

scholarly journals Molecular polymorphism: microwave spectra, equilibrium structures, and an astronomical investigation of the HNCS isomeric family

2016 ◽  
Vol 18 (32) ◽  
pp. 22693-22705 ◽  
Author(s):  
Brett A. McGuire ◽  
Marie-Aline Martin-Drumel ◽  
Sven Thorwirth ◽  
Sandra Brünken ◽  
Valerio Lattanzi ◽  
...  
Keyword(s):  
Molecular Polymorphism ◽  
Rotational Spectra ◽  
Microwave Spectra ◽  
Equilibrium Structures

The rotational spectra of four isomers of the [H, S, C, N] isomeric family are obtained by FTMW spectroscopy, enabling an astronomical search for these species.

THE ROTATIONAL SPECTRA OF CYANOACETYLENE DIMER, H-C-C-C-N ••• H-C-C-C-N

2016 ◽  
Author(s):  
Philip Davis ◽  
Stewart Novick ◽  
Stephen Kukolich ◽  
Adam Daly ◽  
Kexin Li ◽  
...  
Keyword(s):  
Rotational Spectra

BAND NN: A Deep Learning Framework For Energy Prediction and Geometry Optimization of Organic Small Molecules

2019 ◽  
Author(s):  
Siddhartha Laghuvarapu ◽  
Yashaswi Pathak ◽  
U. Deva Priyakumar
Keyword(s):  
Machine Learning ◽  
Density Functional ◽  
Computational Cost ◽  
Geometry Optimization ◽  
Dft Methods ◽  
Energy Prediction ◽  
Machine Learning Model ◽  
Equilibrium Structures ◽  
High Level ◽  
Non Equilibrium

Recent advances in artificial intelligence along with development of large datasets of energies calculated using quantum mechanical (QM)/density functional theory (DFT) methods have enabled prediction of accurate molecular energies at reasonably low computational cost. However, machine learning models that have been reported so far requires the atomic positions obtained from geometry optimizations using high level QM/DFT methods as input in order to predict the energies, and do not allow for geometry optimization. In this paper, a transferable and molecule-size independent machine learning model (BAND NN) based on a chemically intuitive representation inspired by molecular mechanics force fields is presented. The model predicts the atomization energies of equilibrium and non-equilibrium structures as sum of energy contributions from bonds (B), angles (A), nonbonds (N) and dihedrals (D) at remarkable accuracy. The robustness of the proposed model is further validated by calculations that span over the conformational, configurational and reaction space. The transferability of this model on systems larger than the ones in the dataset is demonstrated by performing calculations on select large molecules. Importantly, employing the BAND NN model, it is possible to perform geometry optimizations starting from non-equilibrium structures along with predicting their energies.

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