MP2.5 and MP2.X: Approaching CCSD(T) Quality Description of Noncovalent Interaction at the Cost of a Single CCSD Iteration
Abstract
The performance of the second-order MOllerPlesset perturbation theory MP2.5 and MP2.X methods, tested on the S22, S66, X40, and other benchmark datasets is briefly reviewed. It is found that both methods produce highly accurate binding energies for the complexes contained in these data sets.
Both methods also provide reliable potential energy curves for the complexes in the S66 set. Among the routinely used wavefunction methods, the only other technique that consistently produces lower errors, both for stabilization energies and geometry scans, is the spin-component-scaled coupled-clusters method covering iterative single- and double-electron excitations, which is, however, substantially more computationally intensive.
The structures originated from full geometrical gradient optimizations at the MP2.5 and MP2.X level of theory were confirmed to be the closest to the CCSD(T)/CBS (coupled clusters covering iterative single- and double-electron excitations and perturbative triple-electron excitations performed at the complete basis set limit) geometries among all the tested methods (e.g. MP3, SCS(MI)-MP2, MP2, M06-2X, and DFT-D method evaluated with the TPSS functional).
The MP2.5 geometries for the tested complexes deviate from the references almost negligibly. Inclusion of the scaled third-order correlation energy results in a substantial improvement of the ability to accurately describe noncovalent interactions.
The results shown here serve to support the notion that MP2.5 and MP2.X are reasonable alternative methods for benchmark calculations in cases where system size or (lack of) computational resources preclude the use of CCSD(T)/CBS computations. MP2.X allows for the use of smaller basis sets (i.e. 6-31G*) with results that are nearly identical to those of MP2.5 with larger basis sets, which dramatically decreases computation times and makes calculations on much larger systems possible.