Accounting for dispersion attraction in large-scale chemical systems: Recent advances in DFT corrections

Облік дисперсійного притягання у великомасштабних хімічних системах: останні досягнення в області коригування DFT

Roman Balabin () and Ivan Samoylenko
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Roman Balabin: BWAN - Brainware Analytics - ETH Zürich - Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich]
Ivan Samoylenko: BWAN - Brainware Analytics - ETH Zürich - Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich]

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Abstract: Dispersion attraction in its versatility can only be compared with gravity. At the same time, methods of the electron structure of the mean field – such as the Hartree-Fock method, semi-local approximations of the electron density functional, or semi-empirical theories based on molecular orbitals – do not take into account the complete electron correlation. As a result, they are not sensitive to the London dispersion interaction. At the same time, taking into account dispersion effects is mandatory for realistic calculations of massive chemical systems or the condensed state of any substance. Today we know from experience that various intramolecular phenomena, including the thermochemical properties of matter, depend significantly on the London dispersion. This report describes the theoretical foundations of a series of recent developments in the field of variance corrections to mean field methods. The emphasis is on methods that can be "regularly" used with sufficient accuracy in large-scale chemical applications. Some historical aspects of the variance correction problem are also discussed here. The economic aspects of applying the GPU to variance-adjusted methods of electronic structure of the average field will also not remain without our attention.

Keywords: Electronic correlation effects; History of chemistry; Benzene dimers; Uracil water clusters; Organic crystal; Symmetry-Adapted Perturbation Theory; Intermolecular forces; Hartree-Fock Theory; Random phase approximation RPA; Basis set error correction; Ab initio Calculations; Innovation Diffusion; Van der Waals interaction potential; London dispersion force; Petroleum industry; Asphaltene aggregation; Fullerene; Normal Alkanes; Science history; Gpu acceleration; Dispersion interaction; GPGPU computing; Economics of innovation; Density functional theory; Biomedical Computing; Crude oil; Nanoparticles (search for similar items in EconPapers)
Date: 2016-05-19
Note: View the original document on HAL open archive server: https://hal.science/hal-05672347v1
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Published in BWAN160551, University of Missouri-Kansas City, UMKC; Brainware Analytics, BWAN; Technopark Zürich. 2016, pp.144

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Persistent link: https://EconPapers.repec.org/RePEc:hal:wpaper:hal-05672347

DOI: 10.13140/RG.2.2.27542.10564

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