Literature DB >> 26619974

Electrostatically Embedded Many-Body Expansion for Simulations.

Erin E Dahlke1, Donald G Truhlar1.   

Abstract

We have applied the electrostatically embedded many-body (EE-MB) method truncated at the two-body level (also called the pairwise additive EE-MB method or the EE-PA approximation) and the three-body level (called EE-3B) to calculate the gradient of the potential energy for a simulation box containing 64 water molecules. We employed the B3LYP density functional with the 6-31+G(d,p) basis set for this test case. We found that the EE-PA method is able to reproduce the magnitude of the gradient from a B3LYP/6-31+G(d,p) calculation on the entire system to within 1.0% with a 1.3% error for the maximum component of the gradient. Furthermore, the EE-3B method is able to reproduce the magnitude of the gradient to within 0.1% with a 0.2% error for the maximum component of the gradient. The good performance of the EE-MB methods for calculating forces and the highly parallel nature of these methods make them well suited for use in molecular dynamics simulations. Furthermore, since the methods can be used for efficient and accurate calculations of forces with any level of electronic structure theory that has analytic gradients and with any electronic structure package that allows for the presence of a field of point charges, these methods can readily be used with a wide variety of density functional theory and wave function theory methods.

Entities:  

Year:  2008        PMID: 26619974     DOI: 10.1021/ct700223r

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


  4 in total

1.  Electrostatically Embedded Many-Body Expansion for Neutral and Charged Metalloenzyme Model Systems.

Authors:  Elbek K Kurbanov; Hannah R Leverentz; Donald G Truhlar; Elizabeth A Amin
Journal:  J Chem Theory Comput       Date:  2011-11-29       Impact factor: 6.006

2.  Analysis of the Errors in the Electrostatically Embedded Many-Body Expansion of the Energy and the Correlation Energy for Zn and Cd Coordination Complexes with Five and Six Ligands and Use of the Analysis to Develop a Generally Successful Fragmentation Strategy.

Authors:  Elbek K Kurbanov; Hannah R Leverentz; Donald G Truhlar; Elizabeth A Amin
Journal:  J Chem Theory Comput       Date:  2013-06-11       Impact factor: 6.006

3.  Force Field for Water Based on Neural Network.

Authors:  Hao Wang; Weitao Yang
Journal:  J Phys Chem Lett       Date:  2018-06-04       Impact factor: 6.475

4.  Automatically Constructed Neural Network Potentials for Molecular Dynamics Simulation of Zinc Proteins.

Authors:  Mingyuan Xu; Tong Zhu; John Z H Zhang
Journal:  Front Chem       Date:  2021-06-18       Impact factor: 5.221

  4 in total

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