scholarly journals Local energy decomposition of coupled‐cluster interaction energies: Interpretation, benchmarks, and comparison with symmetry‐adapted perturbation theory

2020 ◽  
Vol 121 (3) ◽  
Author(s):  
Ahmet Altun ◽  
Róbert Izsák ◽  
Giovanni Bistoni
2019 ◽  
Vol 21 (22) ◽  
pp. 11569-11577 ◽  
Author(s):  
Qing Lu ◽  
Frank Neese ◽  
Giovanni Bistoni

The coupled-cluster-based local energy decomposition (LED) analysis is used to elucidate the nature of the TM–alkane interaction in alkane σ-complexes.


ChemPhysChem ◽  
2014 ◽  
Vol 15 (15) ◽  
pp. 3270-3281 ◽  
Author(s):  
Milica Andrejić ◽  
Ulf Ryde ◽  
Ricardo A. Mata ◽  
Pär Söderhjelm

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Alexander G. Donchev ◽  
Andrew G. Taube ◽  
Elizabeth Decolvenaere ◽  
Cory Hargus ◽  
Robert T. McGibbon ◽  
...  

AbstractAdvances in computational chemistry create an ongoing need for larger and higher-quality datasets that characterize noncovalent molecular interactions. We present three benchmark collections of quantum mechanical data, covering approximately 3,700 distinct types of interacting molecule pairs. The first collection, which we refer to as DES370K, contains interaction energies for more than 370,000 dimer geometries. These were computed using the coupled-cluster method with single, double, and perturbative triple excitations [CCSD(T)], which is widely regarded as the gold-standard method in electronic structure theory. Our second benchmark collection, a core representative subset of DES370K called DES15K, is intended for more computationally demanding applications of the data. Finally, DES5M, our third collection, comprises interaction energies for nearly 5,000,000 dimer geometries; these were calculated using SNS-MP2, a machine learning approach that provides results with accuracy comparable to that of our coupled-cluster training data. These datasets may prove useful in the development of density functionals, empirically corrected wavefunction-based approaches, semi-empirical methods, force fields, and models trained using machine learning methods.


1999 ◽  
Vol 111 (24) ◽  
pp. 10815-10826 ◽  
Author(s):  
Marcel Nooijen

Author(s):  
Aleksander Jaworski ◽  
Niklas Hedin

Methane has been successfully encapsulated within cages of C60 fullerene, and it is an appropriate model system to study confinement effects. Its chemistry and physics is also relevant for theoretical...


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