Water 26-mers drawn from bulk simulations: Benchmark binding energies for unprecedentedly large water clusters and assessment of the electrostatically embedded three-body and pairwise additive approximations

Joachim Friedrich, Haoyu Yu, Hannah R. Leverentz, Peng Bai, J. Ilja Siepmann, Donald G. Truhlar

Research output: Contribution to journalArticlepeer-review

50 Scopus citations

Abstract

It is important to test methods for simulating water, but small water clusters for which benchmarks are available are not very representative of the bulk. Here we present benchmark calculations, in particular CCSD(T) calculations at the complete basis set limit, for water 26-mers drawn from Monte Carlo simulations of bulk water. These clusters are large enough that each water molecule participates in 2.5 hydrogen bonds on average. The electrostatically embedded three-body approximation with CCSD(T) embedded dimers and trimers reproduces the relative binding energies of eight clusters with a mean unsigned error (MUE, kcal per mole of water molecules) of only 0.009 and 0.015 kcal for relative and absolute binding energies, respectively. Using only embedded dimers (electrostatically embedded pairwise approximation) raises these MUEs to 0.038 and 0.070 kcal, and computing the energies with the M11 exchange-correlation functional, which is very economical, yields errors of only 0.029 and 0.042 kcal.

Original languageEnglish (US)
Pages (from-to)666-670
Number of pages5
JournalJournal of Physical Chemistry Letters
Volume5
Issue number4
DOIs
StatePublished - Feb 20 2014

Keywords

  • CCSD(T)
  • correlation energy
  • density functional theory
  • explicitly correlated
  • fragment-based electronic structure methods
  • many-body expansion
  • overlapping fragments

Fingerprint

Dive into the research topics of 'Water 26-mers drawn from bulk simulations: Benchmark binding energies for unprecedentedly large water clusters and assessment of the electrostatically embedded three-body and pairwise additive approximations'. Together they form a unique fingerprint.

Cite this