A clear observation of crystal growth of ice from water in a molecular dynamics simulation with a six-site potential model of H2O

Nada, Hiroki; Eerden, J.P.J.M. van der; Furukawa, Yoshinori

doi:10.1016/j.jcrysgro.2004.02.058

Cited by 58 publications

(73 citation statements)

References 16 publications

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“…Under these conditions, the transfer of heat poses a limit to the rate at which equilibrium is achieved. On the other hand, coupling the system to a thermostat leads to crystallization rates much higher than those found experimentally: 35 this is an advantage for the computation of the melting point, but not for the calculation of dynamical properties. Also, the solid is likely to be under stress when the simulation is carried out under standard constant-volume conditions, as the crystalline structure is not allowed to relax to equilibrium in the direction parallel to the interface.…”

Section: The Journal Of Chemical Physics 128 154507 ͑2008͒mentioning

confidence: 95%

Determination of the melting point of hard spheres from direct coexistence simulation methods

Noya

Vega

Miguel

2008

The Journal of Chemical Physics

109

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We consider the computation of the coexistence pressure of the liquid-solid transition of a system of hard spheres from direct simulation of the inhomogeneous system formed from liquid and solid phases separated by an interface. Monte Carlo simulations of the interfacial system are performed in three different ensembles. In a first approach, a series of simulations is carried out in the isothermal-isobaric ensemble, where the solid is allowed to relax to its equilibrium crystalline structure, thus avoiding the appearance of artificial stress in the system. Here, the total volume of the system fluctuates due to changes in the three dimensions of the simulation box. In a second approach, we consider simulations of the inhomogeneous system in an isothermal-isobaric ensemble where the normal pressure, as well as the area of the ͑planar͒ fluid-solid interface, are kept constant. Now, the total volume of the system fluctuates due to changes in the longitudinal dimension of the simulation box. In both approaches, the coexistence pressure is estimated by monitoring the evolution of the density along several simulations carried out at different pressures. Both routes are seen to provide consistent values of the fluid-solid coexistence pressure, p = 11.54͑4͒k B T / 3 , which indicates that the error introduced by the use of the standard constant-pressure ensemble for this particular problem is small, provided the systems are sufficiently large. An additional simulation of the interfacial system is conducted in a canonical ensemble where the dimensions of the simulation box are allowed to change subject to the constraint that the total volume is kept fixed. In this approach, the coexistence pressure corresponds to the normal component of the pressure tensor, which can be computed as an appropriate ensemble average in a single simulation. This route yields a value of p = 11.54͑4͒k B T / 3 . We conclude that the results obtained for the coexistence pressure from direct simulations of the liquid and solid phases in coexistence using different ensembles are mutually consistent and are in excellent agreement with the values obtained from free energy calculations.

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Section: The Journal Of Chemical Physics 128 154507 ͑2008͒mentioning

confidence: 95%

Determination of the melting point of hard spheres from direct coexistence simulation methods

Noya

Vega

Miguel

2008

The Journal of Chemical Physics

109

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“…The agreement between both techniques is quite good. Direct interface simulations have been used by several authors to estimate melting points or ice growth rates for different water models [92,255,194,256,187,192].…”

Section: Direct Coexistence Simulationsmentioning

confidence: 99%

Determination of phase diagrams via computer simulation: methodology and applications to water, electrolytes and proteins

Vega¹,

Sanz

Abascal

et al. 2008

J. Phys.: Condens. Matter

278

452

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Abstract. In this review we focus on the determination of phase diagrams by computer simulation with particular attention to the fluid-solid and solid-solid equilibria. The methodology to compute the free energy of solid phases will be discussed. In particular, the Einstein crystal and Einstein molecule methodologies are described in a comprehensive way. It is shown that both methodologies yield the same free energies and that free energies of solid phases present noticeable finite size effects. In fact this is the case for hard spheres in the solid phase. Finite size corrections can be introduced, although in an approximate way, to correct for the dependence of the free energy on the size of the system. The computation of free energies of solid phases can be extended to molecular fluids. The procedure to compute free energies of solid phases of water (ices) will be described in detail. The free energies of ices Ih, II, III, IV, V, VI, VII, VIII, IX, XI and XII will be presented for the SPC/E and TIP4P models of water. Initial coexistence points leading to the determination of the phase diagram of water for these two models will be provided. Other methods to estimate the melting point of a solid, as the direct fluid-solid coexistence or simulations of the free surface of the solid will be discussed. It will be shown that the melting points of ice Ih for several water models, obtained from free energy calculations, direct coexistence simulations and free surface simulations, agree within their statistical uncertainty. Phase diagram calculations can indeed help to improve potential models of molecular fluids. For instance, for water, the potential model TIP4P/2005 can be regarded as an improved version of TIP4P. Here we will review some recent work on the phase diagram of the simplest ionic model, the restricted primitive model. Although originally devised to describe ionic liquids, the model is becoming quite popular to describe the behaviour of charged colloids. Besides the possibility of obtaining fluid-solid equilibria for simple protein models will be discussed. In these primitive models, the protein is described by a spherical potential with certain anisotropic bonding sites (patchy sites).

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“…67 Unlike most of the models commonly used for simulation of water, such as SPC/E, 68 TIP4P 69 and TIP5P, 70 the sixsite model was proposed for simulation of ice and water near the actual T m at 1 a.t.m.. For such simulations, several MD studies have demonstrated that the six-site model is suitable for simulating ice growth. 63,[71][72][73] It naturally follows that the six-site model is also suitable for MD simulation of a growing ice-water interface to which AFP is bound.…”

Section: Simulationmentioning

confidence: 99%

Antifreeze proteins: computer simulation studies on the mechanism of ice growth inhibition

Nada

Furukawa

2012

Polym J

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Antifreeze proteins (AFPs), which are present in the bodily fluids of organisms inhabiting cold environments, function as inhibitors of ice growth by binding to certain planes of ice crystals. However, the exact mechanism of ice growth inhibition is still poorly understood as it is exceedingly difficult to experimentally analyze the molecular-scale growth kinetics of ice crystals at the planes to which the proteins bind. This review paper focuses on computer simulation studies on the mechanism of ice growth inhibition by AFPs. Recent molecular dynamics simulations of a growing ice-water interface to which protein is bound have indicated that, when the protein is stably bound to the interface, the growth rate of ice surrounding the protein decreases drastically, owing to depression of the ice melting point through the Gibbs-Thomson effect. The observed decrease in growth rate is expected to correspond to ice growth inhibition in real-world systems. In addition to presenting published simulation studies on the mechanism of ice growth inhibition by AFPs, this review also outlines the direction of future simulation studies in this field.

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A clear observation of crystal growth of ice from water in a molecular dynamics simulation with a six-site potential model of H2O

Cited by 58 publications

References 16 publications

Determination of the melting point of hard spheres from direct coexistence simulation methods

Determination of the melting point of hard spheres from direct coexistence simulation methods

Determination of phase diagrams via computer simulation: methodology and applications to water, electrolytes and proteins

Antifreeze proteins: computer simulation studies on the mechanism of ice growth inhibition

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