Simple and Efficient Truncation of Virtual Spaces in Embedded Wave Functions via Concentric Localization

Daniel Claudino, Nicholas J. Mayhall

Research output: Contribution to journalArticlepeer-review

32 Scopus citations

Abstract

We present a strategy to generate "concentrically local orbitals" for the purpose of decreasing the computational cost of wave function-in-density functional theory (WF-in-DFT) embedding. The concentric localization is performed for the virtual orbitals by first projecting the virtual space onto atomic orbitals centered on the embedded atoms. Using a one-particle operator, these projected orbitals are then taken as a starting point to iteratively span the virtual space, recursively creating virtual orbital "shells" with consecutively decreasing correlation energy recovery at each iteration. This process can be repeated to convergence, allowing for tunable accuracy. Assessment of the proposed scheme is performed by application to the potential energy diagram of the Menshutkin reaction of chloromethane and ammonia inside a segment of a carbon nanotube and the torsional potential of a simplified version of the retinal chromophore.

Original languageEnglish
Pages (from-to)6085-6096
Number of pages12
JournalJournal of Chemical Theory and Computation
Volume15
Issue number11
DOIs
StatePublished - Nov 12 2019
Externally publishedYes

Funding

The authors are grateful for financial support provided by the U.S. Department of Energy (Award No. DE-SC0018326) and computational infrastructure from the Advanced Research Computing at Virginia Tech. The authors thank Dr. Ashutosh Kumar and Dr. Andrew James for helping with changes in the Psi4 source code. The authors are grateful for financial support provided by the U.S. Department of Energy (Award No. DE-SC0018326) and computational infrastructure from the Advanced Research Computing at Virginia Tech. The authors thank Dr. Ashutosh Kumar and Dr. Andrew James for helping with changes in the Psi4 source code.

FundersFunder number
Advanced Research Computing at Virginia Tech
U.S. Department of EnergyDE-SC0018326

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