Explicitly correlated PNO-MP2 and PNO-CCSD and their application to the S66 set and large molecular systems

文献情報

出版日 2014-09-03

DOI 10.1039/C4CP03502J

インパクトファクター 3.676

著者

Gunnar Schmitz, Christof Hättig, David P. Tew

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要旨

We present our current progress on the combination of explicit electron correlation with the pair natural orbital (PNO) representation. In particular we show cubic scaling PNO-MP2-F12, and PNO-CCSD[F12] implementations. The PNOs are constructed using a hybrid scheme, where the PNOs are generated in a truncated doubles space, spanned by orbital specific virtuals obtained using an iterative eigenvector algorithm. We demonstrate the performance of our implementation through calculations on a series of glycine chains. The accuracy of the local approximations is assessed using the S66 benchmark set, and we report for the first time explicitly correlated CCSD results for the whole set and improved estimates for the CCSD/CBS limits. For several dimers the PNO-CCSD[F12] calculations are more accurate than the current reference values. Additionally, we present pilot applications of our PNO-CCSD[F12] code to host–guest interactions in a cluster model for zeolite H-ZSM-5 and in a calix[4]arene–water complex.

掲載誌

Physical Chemistry Chemical Physics

CiteScore: 5.5

自己引用率: 10.3%

年間論文数: 3036

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.