Literature DB >> 31091102

Analytical Energy Gradients for the Cluster-in-Molecule MP2 Method and Its Application to Geometry Optimizations of Large Systems.

Zhigang Ni1,2, Yuqi Wang1, Wei Li1, Peter Pulay2, Shuhua Li1.   

Abstract

An efficient analytical energy gradient algorithm for the cluster-in-molecule (CIM) second order Møller-Plesset perturbation theory (MP2) method is presented. In our algorithm, the gradient contributions from the nonseparable term of the two-body density matrix on a given atom is extracted from calculations on a cluster constructed for this atom. The other terms in the CIM-MP2 energy gradient expression are evaluated by constructing the density matrices of the whole system with the contributions from all clusters constructed. For basis sets with diffuse functions, tight CIM parameters are necessary to obtain accurate gradients. Benchmark calculations show that the CIM-MP2 method can accurately reproduce the conventional MP2 gradients and geometries for larger systems. The optimized structure of a 174-atom oligopeptide using the CIM-MP2 method with the cc-pVDZ basis set is in good agreement with the corresponding crystal structure. The present CIM-MP2 gradient program can be used for optimizing the geometries of large systems with hundreds of atoms on ordinary workstations.

Entities:  

Year:  2019        PMID: 31091102      PMCID: PMC6827198          DOI: 10.1021/acs.jctc.9b00259

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


  56 in total

1.  Three complete turns of a 3(10)-helix at atomic resolution: the crystal structure of Z-(Aib)11-OtBu.

Authors:  Renate Gessmann; Hans Brückner; Kyriacos Petratos
Journal:  J Pept Sci       Date:  2003 Nov-Dec       Impact factor: 1.905

2.  An efficient atomic orbital based second-order Møller-Plesset gradient program.

Authors:  Svein Saebø; Jon Baker; Krzysztof Wolinski; Peter Pulay
Journal:  J Chem Phys       Date:  2004-06-22       Impact factor: 3.488

3.  The orbital-specific-virtual local coupled cluster singles and doubles method.

Authors:  Jun Yang; Garnet Kin-Lic Chan; Frederick R Manby; Martin Schütz; Hans-Joachim Werner
Journal:  J Chem Phys       Date:  2012-04-14       Impact factor: 3.488

4.  A natural linear scaling coupled-cluster method.

Authors:  N Flocke; Rodney J Bartlett
Journal:  J Chem Phys       Date:  2004-12-08       Impact factor: 3.488

5.  Approximate ab initio energies by systematic molecular fragmentation.

Authors:  Vitali Deev; Michael A Collins
Journal:  J Chem Phys       Date:  2005-04-15       Impact factor: 3.488

6.  Local correlation calculations using standard and renormalized coupled-cluster approaches.

Authors:  Wei Li; Piotr Piecuch; Jeffrey R Gour; Shuhua Li
Journal:  J Chem Phys       Date:  2009-09-21       Impact factor: 3.488

7.  The Laplace transformed divide-expand-consolidate resolution of the identity second-order Møller-Plesset perturbation (DEC-LT-RIMP2) theory method.

Authors:  Thomas Kjærgaard
Journal:  J Chem Phys       Date:  2017-01-28       Impact factor: 3.488

8.  The orbital-specific virtual local triples correction: OSV-L(T).

Authors:  Martin Schütz; Jun Yang; Garnet Kin-Lic Chan; Frederick R Manby; Hans-Joachim Werner
Journal:  J Chem Phys       Date:  2013-02-07       Impact factor: 3.488

9.  Improved cluster-in-molecule local correlation approach for electron correlation calculation of large systems.

Authors:  Yang Guo; Wei Li; Shuhua Li
Journal:  J Phys Chem A       Date:  2014-07-03       Impact factor: 2.781

10.  Sparse maps—A systematic infrastructure for reduced-scaling electronic structure methods. I. An efficient and simple linear scaling local MP2 method that uses an intermediate basis of pair natural orbitals.

Authors:  Peter Pinski; Christoph Riplinger; Edward F Valeev; Frank Neese
Journal:  J Chem Phys       Date:  2015-07-21       Impact factor: 3.488

View more
  1 in total

Review 1.  Computational and data driven molecular material design assisted by low scaling quantum mechanics calculations and machine learning.

Authors:  Wei Li; Haibo Ma; Shuhua Li; Jing Ma
Journal:  Chem Sci       Date:  2021-11-08       Impact factor: 9.825

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.