Grant S. Heffelfinger

Diffusion in Lennard-Jones Fluids Using Dual Control-Volume Grand-Canonical Molecular-Dynamics Simulation (DCV-GCMD)

A new approach to calculating diffusivities, both transport as well as equilibrium, is presented. The dual control volume grand canonical molecular dynamics (or DCV‐GCMD) method employs two local control volumes for chemical potential control via particle creation/destruction as in grand canonical Monte Carlo (GCMC) simulations. The control volumes are inserted in a standard NVT molecular dynamics simulation yielding a simulation with stochastic chemical potential control that may be thought of as a hybrid GCMC‐MD approach. The geometrical control of the chemical potential enables a steady state chemical potential gradient to be established in the system. By measuring the density profile and flux, Fick’s law is used to determine the diffusivity. An example calculation is presented for a simple Lennard‐Jones system.

Parallel Atomistic Simulations

Algorithms developed to enable the use of atomistic molecular simulation methods with parallel computers are reviewed. Methods appropriate for bonded as well as non-bonded (and charged) interactions are included. While strategies for obtaining parallel molecular simulations have been developed for the full variety of atomistic simulation methods, molecular dynamics and Monte Carlo have received the most attention. Three main types of parallel molecular dynamics simulations have been developed, the replicated data decomposition, the spatial decomposition, and the force decomposition. For Monte Carlo simulations, parallel algorithms have been developed which can be divided into two categories, those which require a modified Markov chain and those which do not. Parallel algorithms developed for other simulation methods such as Gibbs ensemble Monte Carlo, grand canonical molecular dynamics, and Monte Carlo methods for protein structure determination are also reviewed and issues such as how to measure parallel efficiency, especially in the case of parallel Monte Carlo algorithms with modified Markov chains are discussed.

Direct molecular simulation of gradient-driven diffusion

Recent work in the active area of grand canonical molecular dynamics methods is first briefly reviewed followed by an overview of the dual control volume grand canonical molecular dynamics (DCV-GCMD) method, designed to enable the dynamic simulation of a system with a steady-state chemical potential gradient. A short review of the methods and systems used to prototype the DCV-GCMD method and its parallel implementation follows. Finally a new, novel implementation of the DCV-GCMD method that enables the establishment of a steady-state chemical potential gradient in a multicomponent system without having to insert or delete one of the components is presented and discussed.

Transport diffusion of liquid water and methanol through membranes

In this work, we carried out dual-control-volume grand canonical molecular dynamics simulations of the transport diffusion of liquid water and methanol to vacuum under a fixed chemical potential gradient through a slit pore consisting of Au(111) surfaces covered by −CH3 or −OH terminated self-assembled monolayers (SAMs). Methanol and water are selected as model fluid molecules because water represents a strongly polar molecule while methanol is intermediate between nonpolar and strongly polar molecules. Surface hydrophobicity is adjusted by varying the terminal group of −CH3 (hydrophobic) or −OH (hydrophilic) of SAMs. We observed for the first time from simulations the convex and concave interfaces of fluids transporting across the slit pores. Results show that the characteristics of the interfaces are determined by the interactions between fluid molecules and surfaces. The objective of this work is to provide a fundamental understanding of how these interactions affect transport diffusion.In this work, we carried out dual-control-volume grand canonical molecular dynamics simulations of the transport diffusion of liquid water and methanol to vacuum under a fixed chemical potential gradient through a slit pore consisting of Au(111) surfaces covered by −CH3 or −OH terminated self-assembled monolayers (SAMs). Methanol and water are selected as model fluid molecules because water represents a strongly polar molecule while methanol is intermediate between nonpolar and strongly polar molecules. Surface hydrophobicity is adjusted by varying the terminal group of −CH3 (hydrophobic) or −OH (hydrophilic) of SAMs. We observed for the first time from simulations the convex and concave interfaces of fluids transporting across the slit pores. Results show that the characteristics of the interfaces are determined by the interactions between fluid molecules and surfaces. The objective of this work is to provide a fundamental understanding of how these interactions affect transport diffusion.

DIRECT MOLECULAR SIMULATION OF GRADIENT-DRIVEN DIFFUSION OF LARGE MOLECULES USING CONSTANT PRESSURE

Dual control volume grand canonical molecular dynamics (DCV-GCMD) is a boundary-driven nonequilibrium molecular-dynamics technique for simulating gradient-driven diffusion in multicomponent systems. Two control volumes are established at opposite ends of the simulation box. Constant temperature and chemical potential of diffusing species are imposed in the control volumes (i.e., constant-μ1⋯μn−1μnVT). This results in stable chemical potential gradients and steady-state diffusion fluxes in the region between the control volumes. We present results and detailed analysis for a new constant-pressure variant of the DCV-GCMD method in which one of the diffusing species for which a steady-state diffusion flux exists does not have to be inserted or deleted. Constant temperature, pressure, and chemical potential of all diffusing species except one are imposed in the control volumes (i.e., constant-μ1⋯μn−1NnPT). The constant-pressure method can be applied to situations in which insertion and deletion of large molec...

A comparison between two massively parallel algorithms for Monte Carlo computer simulation: An investigation in the grand canonical ensemble

We present a comparison between two different approaches to parallelizing the grand canonical Monte Carlo simulation technique (GCMC) for classical fluids: a spatial decomposition and a time decomposition. The spatial decomposition relies on the fact that for short‐ranged fluids, such as the cut and shifted Lennard‐Jones potential used in this work, atoms separated by a greater distance than the reach of the potential act independently, and thus different processors can work concurrently in regions of the same system which are sufficiently far apart. The time decomposition is an exactly parallel approach which employs simultaneous (GCMC) simulations, one per processor, identical in every respect except the initial random number seed, with the thermodynamic output variables averaged across all processors. While scaling characteristics for the spatial decomposition are presented for 8–1024 processor systems, the comparison between the two decompositions is limited to the 8–128 processor range due to the warm‐up time and memory imitations of the time decomposition. Using a combination of speed and statistical efficiency, the two algorithms are compared at two different state points. While the time decomposition reaches a given value of standard error in the systems potential energy more quickly than the spatial decomposition for both densities, the warm‐up time demands of the time decomposition quickly become insurmountable as the system size increases.

Parallel genehunter: implementation of a linkage analysis package for distributed-memory architectures

We present a parallel algorithm for performing multipoint linkage analysis of genetic marker data on large family pedigrees. The algorithm effectively distributes both the computation and memory requirements of the analysis. We discuss an implementation of the algorithm in the Genehunter linkage analysis package (version 2.1), enabling Genehunter to run on distributed-memory platforms for the first time. Our preliminary benchmarks indicate reasonable scalability of the algorithm even for fixed-size problems, with parallel efficiencies of 75% or more on up to 128 processors. In addition, we have extended the hard-coded limit of 16 non-founding individuals in Genehunter 2.1 to a new limit of 32 non-founding individuals.

Scalable parallel molecular dynamics on MIMD supercomputers

Presents two parallel algorithms suitable for molecular dynamics simulations over a wide range of sizes, from a few hundred to millions of atoms. One of the algorithms is optimally scalable, offering performance proportional to N/P where N is the number of atoms (or molecules) and P is the number of processors. Their implementation on three MIMD parallel computers (nCUBE2, Intel Gamma, and Intel Delta) and performance on a standard benchmark problem as compared to vector and SIMD implementations is discussed. The authors also briefly describe the integration of one of the algorithms into a widely-used code appropriate for modeling defect dynamics in metals via the embedded atom method.<<ETX>>

Cell multipole method for molecular simulations in bulk and confined systems

One of the bottlenecks in molecular simulations is to treat large systems involving electrostatic interactions. Computational time in conventional molecular simulation methods scales with O(N{sup 2}), where N is the number of atoms. With the emergence of the cell multipole method (CMM) and massively parallel supercomputers, simulations of 10 million atoms have been performed. In this work, the optimal hierarchy cell level and the algorithm for Taylor expansion were recommended for fast and accurate molecular dynamics (MD) simulations of three-dimensional (3D) systems. CMM was then extended to treat quasi-two-dimensional (2D) systems, which is very important for condensed matter physics problems. In addition, CMM was applied to grand canonical ensemble Monte Carlo (GCMC) simulations for both 3D and 2D systems. Under the optimal conditions, the results show that computational time is approximately linear with N for large systems, average error in total potential energy is less than {approx}1%, and RMS force is about 0.015 for 3D and 2D systems when compared with the Ewald summation.

Molecular Dynamics Computer Simulations of Diffusion in Porous Silicates

In this work a newly developed dual control volume grand canonical molecular dynamics technique simulates the diffusion of gas in a cylindrical pore. This allows spatial variation of chemical potential and hence an accurate simulation of steady state pressure driven diffusion. The molecular sieving nature of imicroporous imogolite models and the Knudsen effect are discussed and compared with experimental data.