Molecular dynamics simulation in the grand canonical ensemble

An extended system Hamiltonian is proposed to perform molecular dynamics (MD) simulation in the grand canonical ensemble. The Hamiltonian is similar to the one proposed by Lynch and Pettitt (Lynch and Pettitt, J Chem Phys 1997, 107, 8594), which consists of the kinetic and potential energies for real and fractional particles as well as the kinetic and potential energy terms for material and heat reservoirs interacting with the system. We perform a nonlinear scaling of the potential energy parameters of the fractional particle, as well as its mass to vary the number of particles dynamically. On the basis of the equations of motion derived from this Hamiltonian, an algorithm has been proposed for MD simulation at constant chemical potential. The algorithm has been tested for the ideal gas, for the Lennard-Jones fluid over a wide range of temperatures and densities, and for water. The results for the low-density Lennard-Jones fluid are compared with the predictions from a truncated virial equation of state. In the case of the dense Lennard-Jones fluid and water our predicted results are compared with the results reported using other available methods for the calculation of the chemical potential. The method is also applied to the case of vapor-liquid coexistence point predictions.     

MCM-22型分子筛中苯分子吸附行为的蒙特卡罗模 拟研究

用巨正则统计系综蒙特卡罗模拟方法研究了纯硅MCM-22型分子筛(ITQ-1)中苯分子的吸附行为。结果表明苯分子在ITQ-1型分子筛中主要存在4个吸附位点。从苯分子粒子分布云图上可以看到苯分子的扩散和吸附主要在12元环超笼内发生。在苯分子的扩散过程中,S2位置附近的苯分子分布较为集中,而S3和S4附近的苯分子分布则较为离散。苯分子通过10元环窗口的运动路径势能面的计算结果表明,苯分子在12元环超笼内可以较为自由迁移,而通过10元环窗口从一个超笼扩散到附近的超笼时则需要较高的激发能量,这个能量大约为100kJ/mol。     

Size-effects on simulations in the grand canonical ensemble

Results are presented for the effect of periodic boundary conditions on predictions made using the grand canonical ensemble for systems of limited size. A Monte Carlo study of a realistic gas-solid adsorption model and an exact study of the Tonks gas both show that it is necessary for the minor dimension of the replicated system to be 5 σ or greater if errors in the partition function equivalent to δμ > 0.2 kT are to be avoided. The heat capacity C_μ has similar requirements. However, for quantities such as the isosteric heat of adsorption, <N > and <U > even a dimension as small as 3σ does not lead to serious errors. An examination is presented of possible implications for studies of phase changes.     

Simulating prescribed particle densities in the grand canonical ensemble using iterative algorithms

We present two efficient iterative Monte Carlo algorithms in the grand canonical ensemble with which the chemical potentials corresponding to prescribed (targeted) partial densities can be determined. The first algorithm works by always using the targeted densities in the kT log(rho(i)) (ideal gas) terms and updating the excess chemical potentials from the previous iteration. The second algorithm extrapolates the chemical potentials in the next iteration from the results of the previous iteration using a first order series expansion of the densities. The coefficients of the series, the derivatives of the densities with respect to the chemical potentials, are obtained from the simulations by fluctuation formulas. The convergence of this procedure is shown for the examples of a homogeneous Lennard-Jones mixture and a NaCl-CaCl(2) electrolyte mixture in the primitive model. The methods are quite robust under the conditions investigated. The first algorithm is less sensitive to initial conditions.     

Acceleration of Monte Carlo simulations through spatial updating in the grand canonical ensemble

A new grand canonical Monte Carlo algorithm for continuum fluid models is proposed. The method is based on a generalization of sequential Monte Carlo algorithms for lattice gas systems. The elementary moves, particle insertions and removals, are constructed by analogy with those of a lattice gas. The updating is implemented by selecting points in space (spatial updating) either at random or in a definitive order (sequential). The type of move, insertion or removal, is deduced based on the local environment of the selected points. Results on two-dimensional square-well fluids indicate that the sequential version of the proposed algorithm converges faster than standard grand canonical algorithms for continuum fluids. Due to the nature of the updating, additional reduction of simulation time may be achieved by parallel implementation through domain decomposition.     

Dissipative particle dynamics simulations of polymer melts. I. Building potential of mean force for polyethylene and cis-polybutadiene

We present the derivation of coarse-grained force fields for two types of polymers, polyethylene (PE), and cis-polybutadiene (cis-PB), using the concept of potential of mean force. Coarse-grained force fields were obtained from microscopic simulations for several coarse-graining levels, i.e., different number of monomers lambda per mesoscopic unit called "bead." These force fields are then used in dissipative particle dynamics (DPD) simulations to study structural and dynamical properties of polymer melts of PE and cis-PB. The radial distribution functions g(R), the end-to-end distance R0, the end-to-end vector relaxation time tau, and the chain center of mass self-diffusion D(CM), are computed for different chain lengths at different coarse-graining factor lambda. Scaling laws typical of the Rouse regime are obtained for both polymers for chain lengths ranging from 6 to 50 beads. It is found that the end-to-end distance R0 obtained from DPD simulations agree well with values obtained from both microscopic simulations and experiments. The dependence of the friction coefficient used in DPD simulations versus the coarse-graining level is discussed in view of the overall scaling of the dynamical properties.     

Molecular simulations of confined liquids: an alternative to the grand canonical Monte Carlo simulations

Commonly, the confinement effects are studied from the grand canonical Monte Carlo (GCMC) simulations from the computation of the density of liquid in the confined phase. The GCMC modeling and chemical potential (μ) calculations are based on the insertion/deletion of the real and ghost particle, respectively. At high density, i.e., at high pressure or low temperature, the insertions fail from the Widom insertions while the performing methods as expanded method or perturbation approach are not efficient to treat the large and complex molecules. To overcome this problem we use a simple and efficient method to compute the liquid's density in the confined medium. This method does not require the precalculation of μ and is an alternative to the GCMC simulations. From the isothermal-isosurface-isobaric statistical ensemble we consider the explicit framework/liquid external interface to model an explicit liquid's reservoir. In this procedure only the liquid molecules undergo the volume changes while the volume of the framework is kept constant. Therefore, this method is described in the Np(n)AV(f)T statistical ensemble, where N is the number of particles, p(n) is the normal pressure, V(f) is the volume of framework, A is the surface of the solid/fluid interface, and T is the temperature. This approach is applied and validated from the computation of the density of the methanol and water confined in the mesoporous cylindrical silica nanopores and the MIL-53(Cr) metal organic framework type, respectively.     

Conserving the linear momentum in stochastic dynamics: Dissipative particle dynamics as a general strategy to achieve local thermostatization in molecular dynamics simulations

Stochastic dynamics is a widely employed strategy to achieve local thermostatization in molecular dynamics simulation studies; however, it suffers from an inherent violation of momentum conservation. Although this short‐coming has little impact on structural and short‐time dynamic properties, it can be shown that dynamics in the long‐time limit such as diffusion is strongly dependent on the respective thermostat setting. Application of the methodically similar dissipative particle dynamics (DPD) provides a simple, effective strategy to ensure the advantages of local, stochastic thermostatization while at the same time the linear momentum of the system remains conserved. In this work, the key parameters to employ the DPD thermostats in the framework of periodic boundary conditions are investigated, in particular the dependence of the system properties on the size of the DPD‐region as well as the treatment of forces near the cutoff. Structural and dynamical data for light and heavy water as well as a Lennard–Jones fluid have been compared to simulations executed via stochastic dynamics as well as via use of the widely employed Nose–Hoover chain and Berendsen thermostats. It is demonstrated that a small size of the DPD region is sufficient to achieve local thermalization, while at the same time artifacts in the self‐diffusion characteristic for stochastic dynamics are eliminated. © 2016 Wiley Periodicals, Inc.     

The dependence on and continuity of the energy and other molecular properties with respect to the number of electrons

It was recently shown that the size consistency of the energy implies that, for any system with a rational number of electrons, the energy is given by the weighted average of the two systems with the nearest integer numbers of electrons. Specifically, E[N+P/Q] = (1−P/Q)E[N] + (P/Q)E[N+1]. This paper extends that analysis, showing that the same result holds for irrational numbers of electrons. This proves that the energy is a continuous function of the number of electrons, and justifies differentiation with respect to electron number, providing a rigorous justification or the density-functional theoretic approaches to chemical concepts like the electronegativity and the Fukui function. Similar results hold for properties other than the energy. Specific emphasis is placed on molecular response properties associated with the density-functional theory of chemical reactivity.     

Enabling grand‐canonical Monte Carlo: Extending the flexibility of GROMACS through the GromPy python interface module

We report on a python interface to the GROMACS molecular simulation package, GromPy (available at https://github.com/GromPy ). This application programming interface (API) uses the ctypes python module that allows function calls to shared libraries, for example, written in C. To the best of our knowledge, this is the first reported interface to the GROMACS library that uses direct library calls. GromPy can be used for extending the current GROMACS simulation and analysis modes. In this work, we demonstrate that the interface enables hybrid Monte‐Carlo/molecular dynamics (MD) simulations in the grand‐canonical ensemble, a simulation mode that is currently not implemented in GROMACS. For this application, the interplay between GromPy and GROMACS requires only minor modifications of the GROMACS source code, not affecting the operation, efficiency, and performance of the GROMACS applications. We validate the grand‐canonical application against MD in the canonical ensemble by comparison of equations of state. The results of the grand‐canonical simulations are in complete agreement with MD in the canonical ensemble. The python overhead of the grand‐canonical scheme is only minimal. © 2012 Wiley Periodicals, Inc.     

Mesoscale simulation of polymer reaction equilibrium: combining dissipative particle dynamics with reaction ensemble Monte Carlo. I. Polydispersed polymer systems

We present a mesoscale simulation technique, called the reaction ensemble dissipative particle dynamics (RxDPD) method, for studying reaction equilibrium of polymer systems. The RxDPD method combines elements of dissipative particle dynamics (DPD) and reaction ensemble Monte Carlo (RxMC), allowing for the determination of both static and dynamical properties of a polymer system. The RxDPD method is demonstrated by considering several simple polydispersed homopolymer systems. RxDPD can be used to predict the polydispersity due to various effects, including solvents, additives, temperature, pressure, shear, and confinement. Extensions of the method to other polymer systems are straightforward, including grafted, cross-linked polymers, and block copolymers. To simulate polydispersity, the system contains full polymer chains and a single fractional polymer chain, i.e., a polymer chain with a single fractional DPD particle. The fractional particle is coupled to the system via a coupling parameter that varies between zero (no interaction between the fractional particle and the other particles in the system) and one (full interaction between the fractional particle and the other particles in the system). The time evolution of the system is governed by the DPD equations of motion, accompanied by changes in the coupling parameter. The coupling-parameter changes are either accepted with a probability derived from the grand canonical partition function or governed by an equation of motion derived from the extended Lagrangian. The coupling-parameter changes mimic forward and reverse reaction steps, as in RxMC simulations.     

Molecular dynamics study of polymer crystallization in the presence of a particle

We have used molecular dynamics simulations with a coarse‐grained model to study the effect of a particle on the crystallization of polymer melt. We analyzed in particular a bond order parameter to characterize the nucleation and crystallization process. Our calculations show that the presence of a particle modifies the free energy landscape of polymer melts, locally induces the ordering of polymer melts near the particle surface, and thus enhances the polymer crystallization. Because the interaction between the particle and polymers is repulsive, our results suggest that the origin of the enhancement for polymer crystallization is entropic. © 2007 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 45: 2161–2166, 2007     

Information theory approach to the isothermal–isobaric ensemble. 1. Monte Carlo simulations with the hard-sphere and square potentials

Monte Carlo (MC) simulations were performed on the isothermal–isobaric partition functions for both argon and methane gas. A newly implemented form was applied to the calculation of the volume for a variety of pressures, from which many potential applications can be derived.     

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 system's 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. © 1996 by John Wiley & Sons, Inc.     

An alternative approach to the g-matrix: theory and applications.

Starting from the formula proposed by Gerloch and McMeeking in 1975, the electronic g-matrix is expressed as a sum of two matrices called Lambda and Sigma describing the orbital and spin contributions respectively. This approach is applied on benchmark diatomic and triatomic molecules, and on TiF3 and Cu(NH3)4(2+) using either CASPT2 or CCSD(T) methods to calculate the spin-free states and SO-RASSI to calculate spin-orbit coupling. Results compare very well to experimental data and to previous theoretical work; and, for each molecule, the anisotropy of the g-matrix is modeled by the mean of a few parameters.     

Rigid-body dynamics in the isothermal-isobaric ensemble: a test on the accuracy and computational efficiency

We have developed a time-reversible rigid-body (rRB) molecular dynamics algorithm in the isothermal-isobaric (NPT) ensemble. The algorithm is an extension of rigid-body dynamics [Matubayasi and Nakahara, J Chem Phys 1999, 110, 3291] to the NPT ensemble on the basis of non-Hamiltonian statistical mechanics [Martyna, G. J. et al., J Chem Phys 1994, 101, 4177]. A series of MD simulations of water as well as fully hydrated lipid bilayer systems have been undertaken to investigate the accuracy and efficiency of the algorithm. The rRB algorithm was shown to be superior to the state-of-the-art constraint-dynamics algorithm SHAKE/RATTLE/ROLL, with respect to computational efficiency. However, it was revealed that both algorithms produced accurate trajectories of molecules in the NPT as well as NVT ensembles, as long as a reasonably short time step was used. A couple of multiple time-step (MTS) integration schemes were also examined. The advantage of the rRB algorithm for computational efficiency increased when the MD simulation was carried out using MTS on parallel processing computer systems; total computer time for MTS-MD of a lipid bilayer using 64 processors was reduced by about 40% using rRB instead of SHAKE/RATTLE/ROLL.