For inhomogeneous systems with interfaces, the inclusion of long-range dispersion interactions is necessary to achieve consistency between molecular simulation calculations and experimental results. For accurate and efficient incorporation of these contributions, we have implemented a particle-particle particle-mesh Ewald solver for dispersion (r(-6)) interactions into the LAMMPS molecular dynamics package. We demonstrate that the solver's O(N log N) scaling behavior allows its application to large-scale simulations. We carefully determine a set of parameters for the solver that provides accurate results and efficient computation. We perform a series of simulations with Lennard-Jones particles, SPC/E water, and hexane to show that with our choice of parameters the dependence of physical results on the chosen cutoff radius is removed. Physical results and computation time of these simulations are compared to results obtained using either a plain cutoff or a traditional Ewald sum for dispersion.
Long-range dispersion interactions have a critical influence on physical quantities in simulations of inhomogeneous systems. However, the perceived computational overhead of long-range solvers has until recently discouraged their implementation in molecular dynamics packages. Here, we demonstrate that reducing the cutoff radius for local interactions in the recently introduced particle-particle particle-mesh (PPPM) method for dispersion [Isele-Holder et al., J. Chem. Phys., 2012, 137, 174107] can actually often be faster than truncating dispersion interactions. In addition, because all long-range dispersion interactions are incorporated, physical inaccuracies that arise from truncating the potential can be avoided. Simulations using PPPM or other mesh Ewald solvers for dispersion can provide results more accurately and more efficiently than simulations that truncate dispersion interactions. The use of mesh-based approaches for dispersion is now a viable alternative for all simulations containing dispersion interactions and not merely those where inhomogeneities were motivating factors for their use. We provide a set of parameters for the dispersion PPPM method using either ik or analytic differentiation that we recommend for future use and demonstrate increased simulation efficiency by using the long-range dispersion solver in a series of performance tests on massively parallel computers.
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