Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

Fast parallel algorithms for short-range molecular dynamics

抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

A modified SAFT equation of state is developed by applying the perturbation theory of Barker and Henderson to a hard-chain reference fluid. With conventional one-fluid mixing rules, the equation of state is applicable to mixtures of small spherical molecules such as gases, nonspherical solvents, and chainlike polymers. The three pure-component parameters required for nonassociating molecules were identified for 78 substances by correlating vapor pressures and liquid volumes. The equation of state gives good fits to these properties and agrees well with caloric properties. When applied to vapor−liquid equilibria of mixtures, the equation of state shows substantial predictive capabilities and good precision for correlating mixtures. Comparisons to the SAFT version of Huang and Radosz reveal a clear improvement of the proposed model. A brief comparison with the Peng−Robinson model is also given for vapor−liquid equilibria of binary systems, confirming the good performance of the suggested equation of state. ...

Perturbed-Chain SAFT: An Equation of State Based on a Perturbation Theory for Chain Molecules

The perturbed-chain SAFT (PC−SAFT) equation of state is applied to pure associating components as well as to vapor−liquid and liquid−liquid equilibria of binary mixtures of associating substances. For these substances, the PC−SAFT equation of state requires five pure-component parameters, two of which characterize the association. The pure-component parameters were identified for 18 associating substances by correlating vapor pressure and liquid density data. A comparison to an earlier version of SAFT confirms the good results for pure substances. When only one associating compound is present in a mixture, the PC−SAFT equation of state does not require mixing rules for the association term. Using one binary interaction parameter kij for the dispersion term only, the model was applied to azeotropic and nonazeotropic vapor−liquid equilibria at low and at high pressures, as well as to liquid−liquid equilibria. Simple mixing and combining rules were adopted for mixtures with more than one associating compound...

Application of the Perturbed-Chain SAFT Equation of State to Associating Systems

Over the last forty years many computer simulations of water have been performed using rigid non-polarizable models. Since these models describe water interactions in an approximate way it is evident that they cannot reproduce all of the properties of water. By now many properties for these kinds of models have been determined and it seems useful to compile some of these results and provide a critical view of the successes and failures. In this paper a test is proposed in which 17 properties of water, from the vapour and liquid to the solid phases, are taken into account to evaluate the performance of a water model. A certain number of points between zero (bad agreement) and ten (good agreement) are given for the predictions of each model and property. We applied the test to five rigid non-polarizable models, TIP3P, TIP5P, TIP4P, SPC/E and TIP4P/2005, obtaining an average score of 2.7, 3.7, 4.7, 5.1, and 7.2 respectively. Thus although no model reproduces all properties, some models perform better than others. It is clear that there are limitations for rigid non-polarizable models. Neglecting polarizability prevents an accurate description of virial coefficients, vapour pressures, critical pressure and dielectric constant. Neglecting nuclear quantum effects prevents an accurate description of the structure, the properties of water below 120 K and the heat capacity. It is likely that for rigid non-polarizable models it may not be possible to increase the score in the test proposed here beyond 7.6. To get closer to experiment, incorporating polarization and nuclear quantum effects is absolutely required even though a substantial increase in computer time should be expected. The test proposed here, being quantitative and selecting properties from all phases of water can be useful in the future to identify progress in the modelling of water.

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Simulating water with rigid non-polarizable models: a general perspective

Progress in developing equations of state for the calculation of fluid-phase equilibria is reviewed. There are many alternative equations of state capable of calculating the phase equilibria of a diverse range of fluids. A wide range of equations of state from cubic equations for simple molecules to theoretically-based equations for molecular chains is considered. An overview is also given of work on mixing rules that are used to apply equations of state to mixtures. Historically, the development of equations of state has been largely empirical. However, equations of state are being formulated increasingly with the benefit of greater theoretical insights. It is now quite common to use molecular simulation data to test the theoretical basis of equations of state. Many of these theoretically-based equations are capable of providing reliable calculations, particularly for large molecules.

http://depa.fquim.unam.mx/amyd/archivero/TEORIADEECUACIONESDEESTADO_3411.pdf

Equations of state for the calculation of fluid-phase equilibria

Preface. List of Algorithms. Notation. 1. Introduction. What is molecular simulation? Progress in molecular simulation. 2. Theoretical Foundations. Basic statistical mechanics. Particle dynamics. Summary. 3. Intermolecular Potentials. Calculation of the potential energy. Intermolecular forces. Pairwise potentials for atoms and simple molecules. Contributions to molecular interactions. Simple pairwise potentials for molecules. Pairwise potentials from molecular mechanics. Many-body interactions for atoms. Many-body interactions for molecules. Ab initio calculations. Summary. 4. Calculating Molecular Interactions. Calculation of short-range interactions. Calculation of long-range interactions. Summary. 5. Monte Carlo Simulation. Basic concepts. Application to molecules. Some recent developments. Summary. 6. Integrators for Molecular Dynamics. Integrating the equations of motion. Gear predictor-corrector methods. Verlet predictor methods. Comparison of integrators. Integrators for molecules. Summary. 7. Non-Equilibrium Molecular Dynamics. Synthetic NEMD algorithms. Application of NEMD algorithms to molecules. Application of NEMD algorithms to mixtures. Comparison with equilibrium molecular dynamics. Summary. 8. Molecular Simulation of Ensembles. Monte Carlo methods. Molecular dynamics. Summary. 9. Molecular Simulation of Phase Equilibria. Calculating the chemical potential. Monte Carlo grand canonical Gibbs ensemble. Molecular dynamics grand canonical Gibbs ensemble. NPT + test particle. Gibbs-Duhem integration. Thermodynamic scaling. Pseudo ensemble methods. Histogram re-weighting algorithms. Finite size scaling. Summary. 10. Molecular Simulation and Object-Orientation. Fundamental concepts of object-orientation. Application of object-orientation to microcanonical molecular dynamics simulation of Lennard-Jones atoms. Application of object-orientation to a microcanonical Monte Carlo simulation of Lennard-Jones atoms. Combined molecular dynamics and Monte Carlo program for Lennard-Jones atoms in the microcanonical ensemble. Extensions. Summary. Appendices: A. Software User's Guide. B. Simulation Resources. Index.

Molecular Simulation of Fluids: Theory, Algorithms and Object-Orientation

Gibbs ensemble Monte Carlo simulations are reported for the vapor–liquid phase coexistence of argon, krypton, and xenon. The calculations employ accurate two-body potentials in addition to contributions from three-body dispersion interactions resulting from third-order triple-dipole, dipole–dipole–quadrupole, dipole–quadrupole–quadrupole, quadrupole–quadrupole–quadrupole, and fourth-order triple-dipole terms. It is shown that vapor–liquid equilibria are affected substantially by three-body interactions. The addition of three-body interactions results in good overall agreement of theory with experimental data. In particular, the subcritical liquid-phase densities are predicted accurately.

/pdf/molecular-simulation-of-the-phase-behavior-of-noble-gases-33iucic78x.pdf

Molecular simulation of the phase behavior of noble gases using accurate two-body and three-body intermolecular potentials

The role of bond flexibility on the dielectric constant of water is investigated via molecular dynamics simulations using a flexible intermolecular potential SPC/Fw [Y. Wu, H. L. Tepper, and G. A. Voth, J. Chem. Phys. 128, 024503 (2006)]. Dielectric constants and densities are reported for the liquid phase at temperatures of 298.15 K and 473.15 K and the supercritical phase at 673.15 K for pressures between 0.1 MPa and 200 MPa. Comparison with both experimental data and other rigid bond intermolecular potentials indicates that introducing bond flexibility significantly improves the prediction of both dielectric constants and pressure–temperature–density behavior. In some cases, the predicted densities and dielectric constants almost exactly coincide with experimental data. The results are analyzed in terms of dipole moments, quadrupole moments, and equilibrium bond angles and lengths. It appears that bond flexibility allows the molecular dipole and quadrupole moment to change with the thermodynamic state ...

https://researchbank.swinburne.edu.au/file/64ce05af-2714-4aa3-8ff5-3c9a7f224ddc/1/PDF (Published version).pdf

Molecular dynamics simulation of the dielectric constant of water: the effect of bond flexibility.

Molecular dynamics simulations are reported for the solid-liquid coexistence properties of n-6 Lennard-Jones fluids, where n=12, 11, 10, 9, 8, and 7. The complete phase behavior for these systems has been obtained by combining these data with vapor-liquid simulations. The influence of n on the solid-liquid coexistence region is compared using relative density difference and miscibility gap calculations. Analytical expressions for the coexistence pressure, liquid, and solid densities as a function of temperature have been determined, which accurately reproduce the molecular simulation data. The triple point temperature, pressure, and liquid and solid densities are estimated. The triple point temperature and pressure scale with respect to 1/n, resulting in simple linear relationships that can be used to determine the pressure and temperature for the limiting ∞-6 Lennard-Jones potential. The simulation data are used to obtain parameters for the Raveche, Mountain, and Streett and Lindemann melting rules, which indicate that they are obeyed by the n-6 Lennard Jones potentials. In contrast, it is demonstrated that the Hansen–Verlet freezing rule is not valid for n-6 Lennard-Jones potentials.

Richard J. Sadus

Papers

Equations of state for the calculation of fluid-phase equilibria

Molecular Simulation of Fluids: Theory, Algorithms and Object-Orientation

Molecular simulation of the phase behavior of noble gases using accurate two-body and three-body intermolecular potentials

Molecular dynamics simulation of the dielectric constant of water: the effect of bond flexibility.

Solid-liquid equilibria and triple points of n-6 Lennard-Jones fluids.