Skip to main content
Journal cover image

Efficient Implicit Solvation Method for Full Potential DFT.

Publication ,  Journal Article
Sinstein, M; Scheurer, C; Matera, S; Blum, V; Reuter, K; Oberhofer, H
Published in: Journal of chemical theory and computation
November 2017

With the advent of efficient electronic structure methods, effective continuum solvation methods have emerged as a way to, at least partially, include solvent effects into simulations without the need for expensive sampling over solvent degrees of freedom. The multipole moment expansion (MPE) model, while based on ideas initially put forward almost 100 years ago, has recently been updated for the needs of modern electronic structure calculations. Indeed, for an all-electron code relying on localized basis sets and-more importantly-a multipole moment expansion of the electrostatic potential, the MPE method presents a particularly cheap way of solving the macroscopic Poisson equation to determine the electrostatic response of a medium surrounding a solute. In addition to our implementation of the MPE model in the FHI-aims electronic structure theory code [ Blum , V. ; Comput. Phys. Commun. 2009 , 180 , 2175 - 2196 , DOI: 10.1016/j.cpc.2009.06.022 ], we describe novel algorithms for determining equidistributed points on the solvation cavity-defined as a charge density isosurface-and the determination of cavity surface and volume from just this collection of points and their local density gradients. We demonstrate the efficacy of our model on an analytically solvable test case, against high-accuracy finite-element calculations for a set of ≈140000 2D test cases, and finally against experimental solvation free energies of a number of neutral and singly charged molecular test sets [ Andreussi , O. ; J. Chem. Phys. 2012 , 136 , 064102 , DOI: 10.1063/1.3676407 ; Marenich , A. V. ; Minnesota Solvation Database , Version 2012; University of Minnesota : Minneapolis, MN, USA , 2012 . ]. In all test cases we find that our MPE approach compares very well with given references at computational overheads < 20% and sometimes much smaller compared to a plain self-consistency cycle.

Duke Scholars

Altmetric Attention Stats
Dimensions Citation Stats

Published In

Journal of chemical theory and computation

DOI

EISSN

1549-9626

ISSN

1549-9618

Publication Date

November 2017

Volume

13

Issue

11

Start / End Page

5582 / 5603

Related Subject Headings

  • Chemical Physics
  • 3407 Theoretical and computational chemistry
  • 3406 Physical chemistry
  • 0803 Computer Software
  • 0601 Biochemistry and Cell Biology
  • 0307 Theoretical and Computational Chemistry
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Sinstein, M., Scheurer, C., Matera, S., Blum, V., Reuter, K., & Oberhofer, H. (2017). Efficient Implicit Solvation Method for Full Potential DFT. Journal of Chemical Theory and Computation, 13(11), 5582–5603. https://doi.org/10.1021/acs.jctc.7b00297
Sinstein, Markus, Christoph Scheurer, Sebastian Matera, Volker Blum, Karsten Reuter, and Harald Oberhofer. “Efficient Implicit Solvation Method for Full Potential DFT.Journal of Chemical Theory and Computation 13, no. 11 (November 2017): 5582–5603. https://doi.org/10.1021/acs.jctc.7b00297.
Sinstein M, Scheurer C, Matera S, Blum V, Reuter K, Oberhofer H. Efficient Implicit Solvation Method for Full Potential DFT. Journal of chemical theory and computation. 2017 Nov;13(11):5582–603.
Sinstein, Markus, et al. “Efficient Implicit Solvation Method for Full Potential DFT.Journal of Chemical Theory and Computation, vol. 13, no. 11, Nov. 2017, pp. 5582–603. Epmc, doi:10.1021/acs.jctc.7b00297.
Sinstein M, Scheurer C, Matera S, Blum V, Reuter K, Oberhofer H. Efficient Implicit Solvation Method for Full Potential DFT. Journal of chemical theory and computation. 2017 Nov;13(11):5582–5603.
Journal cover image

Published In

Journal of chemical theory and computation

DOI

EISSN

1549-9626

ISSN

1549-9618

Publication Date

November 2017

Volume

13

Issue

11

Start / End Page

5582 / 5603

Related Subject Headings

  • Chemical Physics
  • 3407 Theoretical and computational chemistry
  • 3406 Physical chemistry
  • 0803 Computer Software
  • 0601 Biochemistry and Cell Biology
  • 0307 Theoretical and Computational Chemistry