title: A refined cluster-in-molecule local correlation approach for predicting the relative energies of large systems.
abstract: A refined cluster-in-molecule (CIM) method for local correlation calculations of large molecules is presented. In the present work, two new strategies are introduced to further improve the CIM approach: (1) Some medium-range electron correlation energies, which are neglected in the previous CIM approach, are taken into account. (2) A much simpler procedure using only a distance threshold is used to construct various clusters. To cover the medium-range correlation effect as much as possible, some two-atom-centered clusters are built, in addition to one-atom-centered clusters. Our test calculations at the second order perturbation theory (MP2) level show that the refined CIM method can recover about 99.9% of the conventional MP2 correlation energy using an appropriate distance threshold. The accuracy of the present CIM method is capable of providing reliable relative energies of medium-sized systems such as polyalanines with 10 residues, and water molecules with 50 water molecules. For polyalanines with up to 30 residues, we have demonstrated that the computational cost of the CIM-MP2 calculation increases linearly with the molecular size, but the required memory and disc-space do not need to increase for large systems. The improved CIM method has been used to compute the relative energy of ice-like (H(2)O)(96) clusters (with 2400 basis functions) and to predict the dimerization energy of a double-helical foldamer (with 2330 basis functions). The present CIM method is expected to be a practical local correlation method for describing the relative energies of large systems.
authors.affiliation: School of Chemistry and Chemical Engineering, Key Laboratory of Mesoscopic Chemistry of Ministry of Education, Institute of Theoretical and Computational Chemistry, Nanjing University, Nanjing, 210093, PR China.
authors.forename: Wei
authors.initials: W
authors.lastname: Li
authors.forename: Yang
authors.initials: Y
authors.lastname: Guo
authors.forename: Shuhua
authors.initials: S
authors.lastname: Li