Molecular dynamics extended for fluctuating networks: application to water.

Molecular simulation models are increasingly important tools in efforts to understand the role that water plays in biochemical processes. However, existing models of water have limited capacity to deal with the characteristics of hydrogen bond networks. This article proposes a new fluctuating network (FN) algorithm as an extension of the standard molecular dynamics algorithm. The new algorithm allows for the simulation of a molecular system based on an underlying network, such as the hydrogen bond network in water. This algorithm distinguishes strong from weak network connections, applying a potential that best describes the specific connection behavior. We model liquid water with this new technique using a single-site, isotropic, short-range potential. We successfully reproduce liquid water's signature molecular spacing (as represented by the radial distribution function) and characterize its dynamic properties including the exponential hydrogen bond lifetime distribution, diffusion rate, and average hydrogen bonds per molecule. The FN algorithm allows exploration of the behavior of networked systems where explicit coordination limits are required. As such it could also be used to model covalent interactions, reaction dynamics, and applied to simulation of cellular networks.

Accelerating molecular simulations by reversible mapping between local minima.

A new framework is presented for performing Monte Carlo simulations of condensed matter based on a recently developed bijective mapping between local energy minima. The framework is used to implement a range of new multiparticle Monte Carlo moves, which are investigated by simulating atomic Lennard-Jones fluids in the canonical and grand canonical ensembles. Important aspects of the simulation protocol and their effect on performance are analyzed in detail. Using the mapping accelerates the simulations by many orders of magnitude when compared to the equivalent moves without the mapping, and leads to particularly efficient configurational sampling at low temperatures and high densities. The method appears to be suitable for adapting to quantitative simulations of more complex molecular systems over long effective time scales.

A molecular dynamics study of monolayers of nonionic poly(ethylene oxide) based surfactants.

Molecular dynamics simulations of monolayers of nonionic, poly(ethylene oxide) based surfactants are reported. Specifically, alcohol ethoxylates and alkylphenol ethoxylates are compared in terms of the varying architecture of the molecules for the development of a structure-behavior relationship. Interfacial density profiles are used to assess the structure of the monolayers, the penetration of water and oil into the monolayers, and the solvation of the hydrophiles and hydrophobes. Chain conformational descriptors are used to examine the molecular structure of the surfactants. The simulations revealed that monolayers of alcohol ethoxylates are considerably more diffuse than their alkylphenol counterparts, with the packing being governed by the size of the hydrophile. With the exception of the branched alcohol ethoxylate, the intermixing of the bulk phases within monolayers of alcohol ethoxylates increases with increasing hydrophile length. By comparison, the packing of alkylphenol ethoxylates within the monolayer is governed by the aromatic nucleus in the molecule. No specific interaction is observed between the aromatic rings of neighboring molecules. Monolayers of alkylphenol ethoxylates are more compact than their alcohol counterparts, resulting in more effective separation of the bulk water and oil phases.