4.6 Article

S66x8 noncovalent interactions revisited: new benchmark and performance of composite localized coupled-cluster methods

期刊

PHYSICAL CHEMISTRY CHEMICAL PHYSICS
卷 24, 期 41, 页码 25555-25570

出版社

ROYAL SOC CHEMISTRY
DOI: 10.1039/d2cp03938a

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资金

  1. Israel Science Foundation [1969/20]
  2. Minerva Foundation [20/05]
  3. Artificial Intelligence and Smart Materials Research Fund, in Memory of Dr Uriel Arnon, Israel
  4. Australian Research Council (ARC) Future Fellowship [FT170100373]
  5. Feinberg Graduate School (WIS)
  6. Onassis Foundation-Scholarship [FZP 052-2/2021-2022]

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The S66x8 noncovalent interactions benchmark has been re-evaluated using different methods and considering different basis sets and truncation error corrections. The study found that the LNO-CCSD(T) method performs well under very tight criteria, but struggles with complex counterpoise corrections. In contrast, the PNO-LCCSD(T) method performs best with counterpoise corrections.
The S66x8 noncovalent interactions benchmark has been re-evaluated at the sterling silver level, using explicitly correlated MP2-F12 near the complete basis set limit, CCSD(F12*)/aug-cc-pVTZ-F12, and a (T) correction from conventional CCSD(T)/sano-V{D,T}Z+ calculations. The revised reference values differ by 0.1 kcal mol(-1) RMS from the original Hobza benchmark and its revision by Brauer et al., but by only 0.04 kcal mol(-1) RMS from the bronze level data in Kesharwani et al., Aust. J. Chem., 2018, 71, 238-248. We then used these to assess the performance of localized-orbital coupled cluster approaches with and without counterpoise corrections, such as PNO-LCCSD(T) as implemented in MOLPRO, DLPNO-CCSD(T-1) as implemented in ORCA, and LNO-CCSD(T) as implemented in MRCC, for their respective Normal, Tight, and very Tight settings. We also considered composite approaches combining different basis sets and cutoffs. Furthermore, in order to isolate basis set convergence from domain truncation error, for the aug-cc-pVTZ basis set we compared PNO, DLPNO, and LNO approaches with canonical CCSD(T). We conclude that LNO-CCSD(T) with veryTight criteria performs very well for raw (CP-uncorrected), but struggles to reproduce counterpoise-corrected numbers even for veryveryTight criteria: this means that accurate results can be obtained using either extrapolation from basis sets large enough to quench basis set superposition error (BSSE) such as aug-cc-pV{Q,5}Z, or using a composite scheme such as Tight{T,Q} + 1.11[vvTight(T) - Tight(T)]. In contrast, PNO-LCCSD(T) works best with counterpoise, while performance with and without counterpoise is comparable for DLPNO-CCSD(T-1). Among more economical methods, the highest accuracies are seen for dRPA75-D3BJ, omega B97M-V, omega B97M(2), revDSD-PBEP86-D4, and DFT(SAPT) with a TDEXX or ATDEXX kernel.

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