The FADE mass-stat: a technique for inserting or deleting particles in molecular dynamics simulations.

The emergence of new applications of molecular dynamics (MD) simulation calls for the development of mass-statting procedures that insert or delete particles on-the-fly. In this paper we present a new mass-stat which we term FADE, because it gradually "fades-in" (inserts) or "fades-out" (deletes) molecules over a short relaxation period within a MD simulation. FADE applies a time-weighted relaxation to the intermolecular pair forces between the inserting/deleting molecule and any neighbouring molecules. The weighting function we propose in this paper is a piece-wise polynomial that can be described entirely by two parameters: the relaxation time scale and the order of the polynomial. FADE inherently conserves overall system momentum independent of the form of the weighting function. We demonstrate various simulations of insertions of atomic argon, polyatomic TIP4P water, polymer strands, and C60 Buckminsterfullerene molecules. We propose FADE parameters and a maximum density variation per insertion-instance that restricts spurious potential energy changes entering the system within desired tolerances. We also demonstrate in this paper that FADE compares very well to an existing insertion algorithm called USHER, in terms of accuracy, insertion rate (in dense fluids), and computational efficiency. The USHER algorithm is applicable to monatomic and water molecules only, but we demonstrate that FADE can be generally applied to various forms and sizes of molecules, such as polymeric molecules of long aspect ratio, and spherical carbon fullerenes with hollow interiors.

[1]  Duncan A. Lockerby,et al.  Fluid simulations with atomistic resolution: a hybrid multiscale method with field-wise coupling , 2013, J. Comput. Phys..

[2]  Yonghao Zhang,et al.  Dynamics of nanoscale droplets on moving surfaces. , 2013, Langmuir : the ACS journal of surfaces and colloids.

[3]  Duncan A. Lockerby,et al.  Water transport through carbon nanotubes with defects , 2012 .

[4]  Dimitris Drikakis,et al.  A hybrid molecular continuum method using point wise coupling , 2012, Adv. Eng. Softw..

[5]  David J Huggins,et al.  Correlations in liquid water for the TIP3P-Ewald, TIP4P-2005, TIP5P-Ewald, and SWM4-NDP models. , 2012, The Journal of chemical physics.

[6]  Carlos Vega,et al.  Simulating water with rigid non-polarizable models: a general perspective. , 2011, Physical chemistry chemical physics : PCCP.

[7]  Duncan A. Lockerby,et al.  Water transport through (7,7) carbon nanotubes of different lengths using molecular dynamics , 2011, Microfluidics and Nanofluidics.

[8]  O. Hess,et al.  The initial flow dynamics of light atoms through carbon nanotubes , 2011 .

[9]  J. Reese,et al.  Controllers for imposing continuum-to-molecular boundary conditions in arbitrary fluid flow geometries , 2010 .

[10]  J. Reese,et al.  Molecular dynamics in arbitrary geometries: Parallel evaluation of pair forces , 2008 .

[11]  Matej Praprotnik,et al.  Transport properties controlled by a thermostat: An extended dissipative particle dynamics thermostat. , 2007, Soft matter.

[12]  P. Attard Non-periodic boundary conditions for molecular simulations of condensed matter , 2006 .

[13]  C. Vega,et al.  A general purpose model for the condensed phases of water: TIP4P/2005. , 2005, The Journal of chemical physics.

[14]  Rafael Delgado-Buscalioni,et al.  Hybrid molecular-continuum fluid models: implementation within a general coupling framework , 2005, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[15]  P. Koumoutsakos,et al.  Hybrid atomistic-continuum method for the simulation of dense fluid flows , 2005 .

[16]  Gianni De Fabritiis,et al.  Energy controlled insertion of polar molecules in dense fluids. , 2004, The Journal of chemical physics.

[17]  Xiaobo Nie,et al.  A continuum and molecular dynamics hybrid method for micro- and nano-fluid flow , 2004, Journal of Fluid Mechanics.

[18]  P. Attard,et al.  Grand canonical molecular dynamics , 2003 .

[19]  K. Kremer,et al.  Dissipative particle dynamics: a useful thermostat for equilibrium and nonequilibrium molecular dynamics simulations. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[20]  P. Coveney,et al.  USHER: An algorithm for particle insertion in dense fluids , 2003, cond-mat/0303366.

[21]  P. Coveney,et al.  Continuum-particle hybrid coupling for mass, momentum, and energy transfers in unsteady fluid flow. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[22]  Geri Wagner,et al.  Coupling molecular dynamics and continuum dynamics , 2002 .

[23]  S. Hess,et al.  Rheological evidence for a dynamical crossover in polymer melts via nonequilibrium molecular dynamics , 2000, Physical review letters.

[24]  A. Thompson,et al.  Direct molecular simulation of gradient-driven diffusion of large molecules using constant pressure , 1999 .

[25]  D. Smith,et al.  Molecular dynamics simulations in the grand canonical ensemble: Formulation of a bias potential for umbrella sampling , 1999 .

[26]  Anthony T. Patera,et al.  Heterogeneous Atomistic-Continuum Methods for Dense Fluid Systems , 1997 .

[27]  A. Patera,et al.  Heterogeneous Atomistic-Continuum Representations for Dense Fluid Systems , 1997 .

[28]  M.G.B. Drew,et al.  The art of molecular dynamics simulation , 1996 .

[29]  O'Connell,et al.  Molecular dynamics-continuum hybrid computations: A tool for studying complex fluid flows. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[30]  J. MacElroy Nonequilibrium molecular dynamics simulation of diffusion and flow in thin microporous membranes , 1994 .

[31]  Grant S. Heffelfinger,et al.  Diffusion in Lennard-Jones Fluids Using Dual Control Volume Grand Canonical Molecular Dynamics Simulation (DCV-GCMD) , 1994 .

[32]  Miroslav Grmela,et al.  Viscometric functions for FENE and generalized Lennard-Jones dumbbell liquids in Couette flow: molecular dynamics study , 1993 .

[33]  John A. Zollweg,et al.  The Lennard-Jones equation of state revisited , 1993 .

[34]  Sun,et al.  Molecular-dynamics simulation of compressible fluid flow in two-dimensional channels. , 1992, Physical review. A, Atomic, molecular, and optical physics.

[35]  B. Montgomery Pettitt,et al.  Dynamic simulations of water at constant chemical potential , 1992 .

[36]  J. Banavar,et al.  Computer Simulation of Liquids , 1988 .

[37]  Denis J. Evans,et al.  The Nose–Hoover thermostat , 1985 .

[38]  M. Karplus,et al.  Active site dynamics in protein molecules: A stochastic boundary molecular‐dynamics approach , 1985, Biopolymers.

[39]  H. Berendsen,et al.  Molecular dynamics with coupling to an external bath , 1984 .

[40]  M. Karplus,et al.  Stochastic boundary conditions for molecular dynamics simulations of ST2 water , 1984 .

[41]  M. Karplus,et al.  Deformable stochastic boundaries in molecular dynamics , 1983 .

[42]  J. Mccammon,et al.  Molecular dynamics with stochastic boundary conditions , 1982 .

[43]  H. C. Andersen Molecular dynamics simulations at constant pressure and/or temperature , 1980 .

[44]  B. Widom,et al.  Some Topics in the Theory of Fluids , 1963 .

[45]  Duncan A. Lockerby,et al.  A multiscale method for micro/nano flows of high aspect ratio , 2013, J. Comput. Phys..

[46]  Petros Koumoutsakos,et al.  Hydrophobic hydration of C60 and carbon nanotubes in water , 2004 .

[47]  B. Montgomery Pettitt,et al.  Molecular dynamics with a variable number of molecules , 1991 .