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Wave‐function frozen‐density embedding: Approximate analytical nuclear ground‐state gradients
Author(s) -
Heuser Johannes,
Höfener Sebastian
Publication year - 2016
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.24301
Subject(s) - density functional theory , computation , embedding , ground state , function (biology) , coupled cluster , physics , molecule , chemistry , computational physics , statistical physics , algorithm , molecular physics , quantum mechanics , mathematics , computer science , artificial intelligence , evolutionary biology , biology
We report the derivation of approximate analytical nuclear ground‐state uncoupled frozen density embedding (FDEu) gradients for the resolution of identity (RI) variant of the second‐order approximate coupled cluster singles and doubles (RICC2) as well as density functional theory (DFT), and an efficient implementation thereof in the KOALA program. In order to guarantee a computationally efficient treatment, those gradient terms are neglected which would require the exchange of orbital information. This approach allows for geometry optimizations of single molecules surrounded by numerous molecules with fixed nuclei at RICC2‐in‐RICC2, RICC2‐in‐DFT, and DFT‐in‐DFT FDE level of theory using a dispersion correction, required due to the DFT‐based treatment of the interaction in FDE theory. Accuracy and applicability are assessed by the example of two case studies: (a) the Watson‐Crick pair adenine‐thymine, for which the optimized structures exhibit a maximum error of about 0.08 Å for our best scheme compared to supermolecular reference calculations, (b) carbon monoxide on a magnesium oxide surface model, for which the error amount up to 0.1 Å for our best scheme. Efficiency is demonstrated by successively including environment molecules and comparing to an optimized conventional supermolecular implementation, showing that the method is able to outperform conventional RICC2 schemes already with a rather small number of environment molecules, gaining significant speed up in computation time. © 2016 Wiley Periodicals, Inc.