Projection-Based Correlated Wave Function in Density Functional Theory Embedding for Periodic Systems

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Abstract

We present a level shift projection operator-based embedding method for systems with periodic boundary conditions - where the "active" subsystem can be described using either density functional theory (DFT) or correlated wave function (WF) methods and the "environment" is described using DFT. Our method allows for k-point sampling, is shown to be exactly equal to the canonical DFT solution of the full system under the limit that we use the full system basis to describe each subsystem, and can treat the active subsystem either with periodic boundary conditions - in what we term "periodic-in-periodic" embedding - or as a molecular cluster - in "cluster-in-periodic" embedding. We explore each of these methods and show that cluster WF-in-periodic DFT embedding can accurately calculate the absorption energy of CO on to a Si(100)-2×1 surface.

Original languageEnglish (US)
Pages (from-to)1928-1942
Number of pages15
JournalJournal of Chemical Theory and Computation
Volume14
Issue number4
DOIs
StatePublished - Apr 10 2018

Bibliographical note

Funding Information:
This research was carried out within the Nanoporous Materials Genome Center, which is supported by the U.S. Department of Energy, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences under Award DE-FG02-12ER16362. The authors acknowledge the Minnesota Supercomputing Institute (MSI) at the University of Minnesota and the National Energy Research Scientific Computing Center (NERSC), a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231, for providing resources that contributed to the results reported within this paper.

Funding Information:
This research was carried out within the Nanoporous Materials Genome Center, which is supported by the U.S. Department of Energy, Office of Basic Energy Sciences, Division of Chemical Sciences Geosciences, and Biosciences under Award DE-FG02-12ER16362. The authors acknowledge the Minnesota Supercomputing Institute (MSI) at the University of Minnesota and the National Energy Research Scientific Computing Center (NERSC), a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231, for providing resources that contributed to the results reported within this paper.

Publisher Copyright:
© 2018 American Chemical Society.

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