Embedded mean-field theory

Mark E. Fornace, Joonho Lee, Kaito Miyamoto, Frederick R. Manby*, Thomas F. Miller

*Corresponding author for this work

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

85 Citations (Scopus)
31 Downloads (Pure)

Abstract

We introduce embedded mean-field theory (EMFT), an approach that flexibly allows for the embedding of one mean-field theory in another without the need to specify or fix the number of particles in each subsystem. EMFT is simple, is well-defined without recourse to parameters, and inherits the simple gradient theory of the parent mean-field theories. In this paper, we report extensive benchmarking of EMFT for the case where the subsystems are treated using different levels of Kohn-Sham theory, using PBE or B3LYP/6-31G∗ in the high-level subsystem and LDA/STO-3G in the low-level subsystem; we also investigate different levels of density fitting in the two subsystems. Over a wide range of chemical problems, we find EMFT to perform accurately and stably, smoothly converging to the high-level of theory as the active subsystem becomes larger. In most cases, the performance is at least as good as that of ONIOM, but the advantages of EMFT are highlighted by examples that involve partitions across multiple bonds or through aromatic systems and by examples that involve more complicated electronic structure. EMFT is simple and parameter free, and based on the tests provided here, it offers an appealing new approach to a multiscale electronic structure.

Original languageEnglish
Pages (from-to)568-580
Number of pages13
JournalJournal of Chemical Theory and Computation
Volume11
Issue number2
DOIs
Publication statusPublished - 9 Jan 2015

Fingerprint

Dive into the research topics of 'Embedded mean-field theory'. Together they form a unique fingerprint.

Cite this