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An efficient algorithm for classical density functional theory in three dimensions: ionic solutions.

Matthew G Knepley1, Dmitry A Karpeev, Seth Davidovits

  • 1Computation Institute, University of Chicago, Chicago, Illinois 60637, USA. knepley@ci.uchicago.edu

The Journal of Chemical Physics
|April 8, 2010
PubMed
Summary
This summary is machine-generated.

An efficient numerical scheme for classical density functional theory (DFT) of inhomogeneous fluids of charged, hard spheres is presented. This method uses fast Fourier transforms (FFTs) and Picard iteration for O(N log N) scaling, enabling 3D system analysis.

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Area of Science:

  • Computational physics
  • Statistical mechanics
  • Physical chemistry

Background:

  • Classical density functional theory (DFT) is crucial for analyzing inhomogeneous fluids.
  • Limited numerical solution algorithms exist for 3D DFT systems.
  • Efficient computation is vital for large-scale simulations.

Purpose of the Study:

  • To develop an efficient numerical scheme for 3D DFT of charged, hard sphere fluids.
  • To enable analysis of complex inhomogeneous fluid systems.
  • To compare different numerical approaches for DFT solvers.

Main Methods:

  • Developed an O(N log N) operation and O(N) memory algorithm using fast Fourier transforms (FFTs).
  • Employed Picard (iterative substitution) iteration with line search to solve DFT Euler-Lagrange equations.
  • Utilized fundamental measure theory for hard-sphere DFT and two electrostatic DFT functionals (bulk-fluid and RFD).

Main Results:

  • The FFT/Picard method achieves efficient O(N log N) scaling for 3D systems.
  • A bulk-fluid electrostatic DFT functional algorithm with O(N log N) operations was implemented.
  • A more accurate reference fluid density (RFD) functional algorithm was developed, requiring O(N^2) operations.

Conclusions:

  • The presented FFT/Picard scheme significantly enhances the computational feasibility of 3D DFT for charged hard sphere fluids.
  • The choice between bulk-fluid and RFD functionals involves a trade-off between accuracy and computational cost.
  • This work provides a valuable tool for studying complex fluid systems with unprecedented efficiency.