PACS. 05.40−a -Fluctuation phenomena, random processes, noise, and Brownian motion. PACS. 02.70Ns -Molecular dynamics and particle methods. PACS. 66.20+d -Viscosity of liquids; diffusive momentum transport.Abstract. -We describe a simulation method based on combining the ideas behind Andersen's thermostat and dissipative particle dynamics (DPD). The result is a Galilean invariant thermostat that conserves momentum and enhances viscosity. It therefore displays the same characteristics as DPD. Our method differs primarily in that it satisfies detailed balance by construction. If a simple scheme is used to solve the equations of motion the thermostat does not disturb the equilibrium properties of the system, regardless of the time step. We illustrate the properties of the model by describing the results of various tests on the analogous system to the dissipative ideal gas. We show that with an appropriate choice of parameters it is practical to make the viscosity orders of magnitude greater than the diffusion coefficient. This is a criterion that should be satisfied if one is interested in studying the dynamics of mesoscopic systems.Complex liquids, such as polymer solutions, micellular systems and colloidal suspensions, generally possess mesoscopic length scales-length scales that are small by everyday standards but large by atomic standards. Studying these systems with fully atomistic Molecular Dynamics (MD) is difficult, precisely because of the atomically long time and length scales involved. An alternative approach is to construct a more "course grained" model that mimics the behaviour of the atomistic system on the mesoscopic scale. One such technique is dissipative particle dynamics (DPD) [1]. This method has the main advantage over its rivals that it does not involve discretizing space. Particles representing the mesoscopic system move continuously. This is particularly useful where, for instance, interfaces or macromolecular systems are involved. Since its introduction, a complete understanding of DPD's strengths and weaknesses has only slowly emerged. We begin with a brief description of the method and a summary of what it does that is useful.Dissipative particle dynamics, as the name implies, describes a system in terms of N particles with mass m, whose positions r i and velocities v i evolve in time according toc EDP Sciences
The influence of flexible walls on the self-diffusion of CH 4 in an isolated single walled carbon nanotube, as an example, is studied by molecular dynamics simulations. By simulating the carbon nanotube as a flexible framework we demonstrate that the flexibility has a crucial influence on selfdiffusion at low loadings. We show how this influence can be incorporated in a simulation of a rigid nanotube by using a Lowe-Andersen thermostat which works on interface-fluid collisions. The reproduction of the results of a flexible carbon nanotube by a rigid nanotube simulation is excellent. DOI: 10.1103/PhysRevLett.95.044501 PACS numbers: 47.55.Mh, 66.30.Pa, 83.10.Rs Carbon nanotubes (CNTs) can be aligned in a polymer film to form a well-ordered nanoporous membrane structure [1] which can be incorporated in a macroscopic structure [2] for separation devices. It is therefore of practical interest to understand the diffusive behavior of molecules adsorbed in these materials [3][4][5][6][7]. A particularly interesting observation is the remarkable increase of the diffusion coefficient of simple molecules at low densities observed by Skoulidas et al. [3]. These molecular simulations predict a diffusion coefficient higher than the corresponding gas phase value, resulting in fluxes that are orders of magnitude greater than in crystalline zeolitic membranes [3]. These results have subsequently been reproduced by other groups [8,9] and are explained in terms of the smoothness of the nanotube [3].From a computational point of view, simulations at the low density limit are surprisingly expensive; one needs an increasingly long nanotube to reach the low density limit. This poses no difficulty if one assumes a rigid substrate. However, if one has a material in which the flexibility cannot be ignored and a full atom simulation of the material is required, the calculation becomes many orders of magnitude more expensive and is completely dominated by the substrate. Therefore, most simulation studies use a rigid lattice.A novel algorithm that takes the most important aspects of flexibility into account at a fraction of the costs of a fully flexible CNT simulation is presented, resulting in effectively the same diffusivities and other effects as obtained from the flexible CNT simulations. This algorithm can be applied to other confined systems (zeolites, ion channels, membranes, etc.).Interestingly, whether or not it is reasonable to assume a rigid lattice in adsorption [10] or diffusion studies [11] is far from being understood. An obvious hypothesis would be that only in the case of narrow passages is flexibility very important, while in the case of gas molecules in carbon nanotubes, or other nanoporous materials, a rigid lattice is a very reasonable assumption. As we will show in this Letter, this assumption is the explanation of the remarkable increase of the diffusion coefficient at low loading. Molecular dynamics simulations of a fully flexible nanotube give a diffusion coefficient that is more than 1 order of magnitude lower ...
Poiseuille flow to measure the viscosity of particle model fluids.Backer, J.A.; Lowe, C.P.; Hoefsloot, H.C.J.; Iedema, P.D. General rightsIt is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). Disclaimer/Complaints regulationsIf you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. The most important property of a fluid is its viscosity, it determines the flow properties. If one simulates a fluid using a particle model, calculating the viscosity accurately is difficult because it is a collective property. In this article we describe a new method that has a better signal to noise ratio than existing methods. It is based on using periodic boundary conditions to simulate counter-flowing Poiseuille flows without the use of explicit boundaries. The viscosity is then related to the mean flow velocity of the two flows. We apply the method to two quite different systems. First, a simple generic fluid model, dissipative particle dynamics, for which accurate values of the viscosity are needed to characterize the model fluid. Second, the more realistic Lennard-Jones fluid. In both cases the values we calculated are consistent with previous work but, for a given simulation time, they are more accurate than those obtained with other methods.
The Lowe-Andersen thermostat is a momentum conserving and Galilean invariant analog of the Andersen thermostat. Like the Andersen thermostat it has the advantage of being local. We show that by using a minimal thermostat interaction radius in a molecular dynamics simulation, it perturbs the system dynamics to a far lesser extent than the Andersen method. This alleviates a well known drawback of the Andersen thermostat by allowing high thermostatting rates without the penalty of significantly suppressed diffusion in the system.
We describe results obtained from a new implementation of Hockney's Particle-Particle Particle-Mesh (PPPM) method for evaluation of Coulomb energies and forces in simulations of charged particles. Rather than taking the usual approach, solving Poisson's equation by means of a Fourier transformation, we use an iterative Poisson solver. In a molecular dynamics (MD) simulation the solution from the previous time-step provides a good starting point for the next solution. This reduces the number of iterations per time-step to acceptable values. The iterative scheme has a complexity U(N), and, in contrast with the Fourier transform based approach, it is easily implemented on a parallel architecture with a minimum of communication overhead.We examine the origin of the errors in the algorithm and find that reasonable accuracies in the Coulomb interaction can best be attained by making the charge density profile as smooth as possible. This involves spreading the particle charges over a large number of grid points. Assigning these charges then becomes the most time consuming part of the algorithm. We show how we can then gain a considerable saving in computing time by employing a diffusion equation as a charge spreading mechanism.The effect of employing the algorithm with an accuracy less than that typically tolerated in an Ewald summation is studied by computing, from an MD simulation of silica, quantities that are sensitive to the long range part of the Coulomb interaction. These results are compared to full Ewald sum reference simulations and found to be within the statistical error.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.