Accurate basis set truncation for wavefunction embedding

Taylor A. Barnes, Jason D. Goodpaster, Frederick R. Manby, Thomas F. Miller*

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

62 Citations (Scopus)

Abstract

Density functional theory (DFT) provides a formally exact framework for performing embedded subsystem electronic structure calculations, including DFT-in-DFT and wavefunction theory-in-DFT descriptions. In the interest of efficiency, it is desirable to truncate the atomic orbital basis set in which the subsystem calculation is performed, thus avoiding high-order scaling with respect to the size of the MO virtual space. In this study, we extend a recently introduced projection-based embedding method [F. R. Manby, M. Stella, J. D. Goodpaster, and T. F. Miller III, J. Chem. Theory Comput. 8, 2564 (2012)] to allow for the systematic and accurate truncation of the embedded subsystem basis set. The approach is applied to both covalently and non-covalently bound test cases, including water clusters and polypeptide chains, and it is demonstrated that errors associated with basis set truncation are controllable to well within chemical accuracy. Furthermore, we show that this approach allows for switching between accurate projection-based embedding and DFT embedding with approximate kinetic energy (KE) functionals; in this sense, the approach provides a means of systematically improving upon the use of approximate KE functionals in DFT embedding. (C) 2013 AIP Publishing LLC.

Original languageEnglish
Article number024103
Number of pages11
JournalJournal of Chemical Physics
Volume139
Issue number2
DOIs
Publication statusPublished - 14 Jul 2013

Keywords

  • MANY-BODY EXPANSION
  • MOLECULAR-ORBITAL METHOD
  • GAUSSIAN-TYPE BASIS
  • WATER CLUSTERS
  • AB-INITIO
  • CORRELATION-ENERGY
  • LARGE SYSTEMS
  • DYNAMICS SIMULATIONS
  • ELECTRON-AFFINITIES
  • ORGANIC-MOLECULES

Fingerprint

Dive into the research topics of 'Accurate basis set truncation for wavefunction embedding'. Together they form a unique fingerprint.

Cite this