20104 Phys. Chem. Chem. Phys., 2011, 13, 20104–20107 This journal is c the Owner Societies 2011 Cite this: Phys. Chem. Chem. Phys., 2011, 13, 20104–20107 DSD-PBEP86: in search of the best double-hybrid DFT with spin-component scaled MP2 and dispersion correctionsw Sebastian Kozuch* a and Jan M. L. Martin* ab Received 11th August 2011, Accepted 27th September 2011 DOI: 10.1039/c1cp22592h Spin-component scaled double hybrids including dispersion correction were optimized for many exchange and correlation functionals. Even DSD-LDA performs surprisingly well. DSD-PBEP86 emerged as a very accurate and robust method, approaching the accuracy of composite ab initio methods at a fraction of their computational cost. Double hybrid (DH) DFT has shown to be a successful method for the accurate energy estimation of small and medium sized molecules. 1–6 DH-DFT in its more typical formulation mixes an exact exchange term (‘‘HF-like’’) with the DFT exchange functional as simple hybrids, but adds a perturbational correlation term (‘‘MP2-like’’) to the DFT correlation in the basis of the Kohn–Sham orbitals. 7 The first DH of this form was the B2-PLYP of Grimme, 3 with other examples being the general purpose B2GP-PLYP 2 and the long-range corrected oB97X-2. 5 Some additional flexibility can be provided by setting a different weight to the same-spin and opposite-spin MP2, in the spin-component-scaled MP2 method (SCS-MP2). 8 Same- spin MP2 reflects mostly long range correlation, while the opposite-spin is related to short range interactions. 1,8 It is possible (and advisable) to add a dispersion correction to DFT methods, as typically they do not account for long range interactions. 9 In the case of DH-DFT this is less critical, as the MP2 term does account for those interactions (at least partially); 2 nevertheless, the accuracy expected for DHs cannot be attainable for non-bonding interactions without a dispersion add-on. When the SCS distinction and a dispersion term are included, we obtain the DSD-DFT (Dispersion corrected, Spin-component scaled Double Hybrid). 1 The total exchange– correlation term is then expressed as (see eqn (1)): E XC =c X E X DFT + (1 À c X )E X HF +c C E C DFT +c O E O MP2 +c S E S MP2 +s 6 E D (1) where c X is the amount of DFT exchange, c C that of DFT correlation, c O and c S of opposite and same-spin MP2, and s 6 of the D2 dispersion correction. In this form (eqn (1)) we have already presented the DSD-BLYP functional, which had a remarkable performance. 1,4,6,10 Herein we will seek for the best combination of exchange– correlation functional for the DSD-DFT method. The different functionals were selected from the ‘‘Popularity Poll of Density Functionals’’, 11 with some choices of our own added. The parametrization procedure is virtually the same as the one discussed in our previous DSD-BLYP paper. 1 (Further technical details are relegated to the electronic supporting information.) Six training sets were used to optimize the parameters of eqn (1): W4-08 (atomization energies), 12 DBH24 (reaction kinetics), 13 Pd (oxidative additions on a bare Pd atom), 14 Grubbs (olefin metathesis with a Ru catalyst), 15 Grimme’s ‘‘Mindless benchmark’’ (quasi-random main group reactions), 16 and S22 (for van der Waals forces and H-bonds). 17,18 These training sets cover thermochemistry and kinetics of main group and transition metals, plus long range interactions. Fig. 1 presents the overall error statistics over our training sets for the different functional combinations. Table 1 shows the parameters of selected combinations (detailed error statistics over all the subsets are reported in the ESIw). Perhaps the most stunning result to the present investigators is the surprisingly good performance of the DSD-SVWN5 (that is, DSD-LDA) functional, with an average error of just 1.83 kcal/mol. Even though all double hybrids are, strictly speaking, on the 5th rung of the ‘‘Jacob’s Ladder’’, 19 we can climb the underlying ‘‘sub-ladder’’ functional. For DSD-PBE (2nd sub-rung, a GGA) this is improved to 1.75 kcal/mol, while DSD-TPSS (3rd sub-rung, a meta-GGA) actually does worse at 2.09 kcal/mol. Essentially all of the improvement for DSD-PBE derives from a 25% drop in the RMSD for the ‘‘mindless benchmark’’. Returning to the DSD-LDA result, we note that replace- ment by a GGA of either the exchange part (DSD-BVWN5, DSD-PBEVWN5) or the correlation part (DSD-SLYP, DSD- SPBE, or DSD-SP86) leads to a very significant deterioration. Perhaps this is not surprising as the performance of LDA itself, such as it is, would be even worse were it not for an error compensation between underestimated exchange and excess correlation. a Department of Organic Chemistry, Weizmann Institute of Science, IL-76100 Rechovot, Israel. E-mail: sebastian.kozuch@weizmann.ac.il b Center for Advanced Scientific Computing and Modeling (CASCAM), Department of Chemistry, University of North Texas, Denton, TX 76203-5017, USA. E-mail: gershom@unt.edu w Electronic supplementary information (ESI) available: Complete statistical errors of the training and validation sets, detailed theoretical methods, plus guidelines to run DSD-PBEP86 with various software packages. See DOI: 10.1039/c1cp22592h PCCP Dynamic Article Links www.rsc.org/pccp COMMUNICATION Downloaded by University of North Texas on 16 November 2011 Published on 12 October 2011 on http://pubs.rsc.org | doi:10.1039/C1CP22592H View Online / Journal Homepage / Table of Contents for this issue