Crystal nucleation in binary hard sphere mixtures: a Monte Carlo simulation study

We present calculations of the nucleation barrier during crystallization in binary hard sphere mixtures under moderate degrees of supercooling using Monte Carlo simulations in the isothermal-isobaric semigrand ensemble in conjunction with an umbrella sampling technique. We study both additive and negatively nonadditive binary hard sphere systems. The solid-fluid phase diagrams of such systems show a rich variety of behavior, ranging from simple spindle shapes to the appearance of azeotropes and eutectics to the appearance of substitutionally ordered solid phase compounds. We investigate the effect of these types of phase behavior upon the nucleation barrier and the structure of the critical nucleus. We find that the underlying phase diagram has a significant effect on the mechanism of crystal nucleation. Our calculations indicate that fractionation of the species upon crystallization increases the difficulty of crystallization of fluid mixtures and in the absence of fractionation (azeotropic conditions) the nucleation barrier is comparable to pure fluids. We also calculate the barrier to nucleation of a substitutionally ordered compound solid. In such systems, which also show solid-solid phase separation, we find that the phase that nucleates is the one whose equilibrium composition is closer to the composition of the fluid phase.     

Kinetic Monte Carlo study of nucleation processes on patterned surfaces

The properties of template-directed nucleation are studied in the transition region where full nucleation control is lost and additional nucleation beyond the prepatterned structure is observed. To get deeper insight into the microscopic mechanisms, Monte Carlo simulations were performed. In this context, the previously used continuous algorithm [F. Kalischewski, J. Zhu, and A. Heuer, Phys. Rev. B 77, 155401, (2008)] was replaced by a discrete one to reduce simulation time and to allow more detailed calculations. The applied method is based on the assumption that the molecules on the surface occupy the sites of a simple fcc lattice. It is shown that a careful mapping of the continuous Monte Carlo technique onto the discrete algorithm leads to a good reproduction of the former results by means of the latter method. Furthermore, the new method facilitates the calculation of the spatial distribution of nuclei on the surface. This provides a detailed comparison with experimental data.     

A Monte Carlo simulation study of branched polymers

Monte Carlo simulations are presented for the static properties of highly branched polymer molecules. The molecules consist of a semiflexible backbone of hard-sphere monomers with semiflexible side chains, also composed of hard-sphere monomers, attached to either every backbone bead or every other backbone bead. The conformational properties and structure factor of this model are investigated as a function of the stiffness of the backbone and side chains. The average conformations of the side chains are similar to self-avoiding random walks. The simulations show that there is a stiffening of the backbone as degree of crowding is increased, for example, if the branch spacing is decreased or side chain length is increased. The persistence length of the backbone is relatively insensitive to the stiffness of the side chains over the range investigated. The simulations reproduce most of the qualitative features of the structure factor observed in experiment, although the magnitude of the stiffening of the backbone is smaller than in experiment.     

Rate of two-dimensional nucleation: verifying classical and atomistic theories by Monte Carlo simulation

We present kinetic Monte Carlo simulation data for the stationary rate J of two-dimensional nucleation of monolayer-thick crystal clusters in the growth of an atomically smooth (100) face of single-component Kossel crystal. The data are over a wide range of supersaturations s and effective broken-bond energies omega of nearest-neighbor atoms, and the J values span about 15 orders of magnitude. The simulation reveals that, in the s,omega range studied, the ln J vs s curve is smooth but with nearly linear portions connected with rather sharply curved segments when the omega value is sufficiently great. The simulation J(s) data are used for verification of the classical (CNT) and atomistic (ANT) nucleation theories without free parameters. It turns out that whereas J is overestimated by CNT, it is underestimated by ANT. The disagreement between theory and simulation is much greater for CNT than for ANT and, with increasing omega, it increases for the former but almost disappears for the latter. However, the ANT prediction about broken linear ln J vs s dependence is not confirmed by the simulation in the s,omega range studied.     

Monte Carlo simulation of DNA electrophoresis

This paper describes an attempt to study the electrophoresis mobility of a DNA molecule in a gel by means of a Monte Carlo simulation. We find that the electrophoresis mobility mu can be well described by the empirical equation mu v kappa 1/N + kappa 2E2 with N being the number of monomers of the model chain and E being the applied field. For small E the data can merge into the linear response result mu = kappa 1/N. The paper also discusses necessary extensions of the present approach.     

Monte Carlo simulation of osmotic equilibria

We present a Metropolis Monte Carlo simulation algorithm for the Tpπ-ensemble, where T is the temperature, p is the overall external pressure, and π is the osmotic pressure across the membrane. The algorithm, which can be applied to small molecules or sorption of small molecules in polymer networks, is tested for the case of Lennard-Jones interactions.     

Monte Carlo simulation of polymer welding

Monte Carlo Modelling of random polymer chains, course grained onto a cubic F lattice, provides the ability to monitor the long range relaxation processes and the dynamic parameters of chains up to 400 units long. The model, described and verified by Haire et al. (Haire KR, Carver TJ, Windle AH. A Monte Carlo model for dense polymer systems and its interlocking with molecular dynamics simulation. Computational and Theoretical Polymer Science 2000; in press), is here applied to the study of molecular parameters in the vicinity of different types of surface and also to the process of polymer welding, whereby adhesion between two adjacent surfaces is achieved by the interpenetration of chains which are across the surface.The model demonstrates that a surface distorts the conformation of chains adjacent to it to give an oblate molecular envelope, that the concentration of vacant sites and chain ends increases near to the surface and that the density of points representing the centres of mass of the chains increases in the sub-surface regions. These results confirm earlier predictions and provide additional confidence in the model.Modelling of the welding process leads to the parameter intrinsic weld time, t_w, which is the time from initial perfect contact of the surfaces to the achievement of a weld within which the chain conformation is indistinguishable from the bulk. After the initial period in which the mating surfaces roughen, the welding proceeds according to the t^1/4 law predicted by reptation theory. The time to a given level of interdiffusion across the boundary is proportional to the chain length l, a comparatively weak dependence, while t_w is proportional to l³, a strong dependence. This is the same dependence on length as for the relaxation time of the chain end-to-end vectors. In fact, the agreement between the relaxation time, measured on the model of the bulk, and t_w is surprisingly close, at least for the monodisperse polymers investigated here.     

Monte Carlo simulation of polymer adsorption

We developed and employed the incremental gauge cell method to calculate the chemical potential (and thus free energies) of long, flexible homopolymer chains of Lennard-Jones beads with harmonic bonds. The free energy of these chains was calculated with respect to three external conditions: in the zero-density bulk limit, confined in a spherical pore with hard walls, and confined in a spherical pore with attractive pores, the latter case being an analog of adsorption. Using the incremental gauge cell method, we calculated the incremental chemical potential of free polymer chains before and after the globual-random coil transitions. We also found that chains confined in attractive pores exhibit behaviors typical of low temperature physisorption isotherms, such as layering followed by capillary condensation.     

Order-parameter-based Monte Carlo simulation of crystallization

A Monte Carlo simulation method is presented for simulation of phase transitions, with emphasis on the study of crystallization. The method relies on a random walk in order parameter Phi(q(N)) space to calculate a free energy profile between the two coexisting phases. The energy and volume data generated over the course of the simulation are subsequently reweighed to identify the precise conditions for phase coexistence. The usefulness of the method is demonstrated in the context of crystallization of a purely repulsive Lennard-Jones system. A systematic analysis of precritical and critical nuclei as a function of supercooling reveals a gradual change from a bcc to a fcc structure inside the crystalline nucleus as it grows at large degrees of supercooling. The method is generally applicable and is expected to find applications in systems for which two or more coexisting phases can be distinguished through one or more order parameters.     

Monte Carlo simulation of hard spheroids

We present Monte Carlo simulations of the equation of state and radial distribution function for a model fluid composed of hard spheroids.     

Monte Carlo simulation of block copolymers

Monte Carlo simulations deal with crudely simplified but well-defined models and have the advantage that they treat the statistical thermodynamics of the considered model exactly (apart from statistical errors and problems due to finite size effects). Therefore, these simulations are well suited to test various approximate theories of block copolymer ordering, e.g. the self-consistent field theory. Recent examples of this approach include the study of block copolymer ordering at melt surfaces and confinement effects in thin films, adsorption of block copolymers at interfaces of unmixed homopolymer blends, the phase behavior of ternary mixtures of two homopolymers and their block copolymer, and micelle formation in selective solvents.     

Collective-variable Monte Carlo simulation of DNA

Monte Carlo simulations have been carried out on DNA oligomers using an internal coordinate model associated with a pseudorotational representation of sugar repuckering. It is shown that when this model is combined with the scaled collective variable approach of Noguti and Go, much more efficient simulations are obtained than with simple single variable steps. Application of this method to a DNA oligomer containing a recognition site for the TATA-box binding protein leads to striking similarities with results recently obtained from a 1-ns molecular dynamics simulation using explicit solvent and counterions. In particular, large amplitude bending fluctuations are observed directed toward the major groove. Conformational analysis of the Monte Carlo simulation shows clear base sequence effects on conformational fluctuations and also that the DNA energy hypersurface, like that of proteins, is complex with many local, conformational substates. © 1997 John Wiley & Sons, Inc. J Comput Chem 18 : 2001–2011, 1997     

Pressure-induced ordering in adamantane: a Monte Carlo simulation study

Isothermal-isobaric ensemble Monte Carlo simulation of adamantane has been carried out with a variable shape simulation cell. The low-temperature crystalline phase and the room-temperature plastic crystalline phases have been studied employing the modified Williams potential. We show that at room temperature, the plastic crystalline phase transforms to the crystalline phase on increase in pressure. Further, we show that this is the same phase as the low-temperature ordered tetragonal phase of adamantane. The high-pressure ordered phase appears to be characterized by a slightly larger shift of the first peak toward a lower value of r in C-C, C-H, and H-H radial distribution functions as compared to the low-temperature tetragonal phase. The coexistence curve between the crystalline and plastic crystalline phase has been obtained approximately up to a pressure of 4 GPa.     

Kinetic Monte Carlo simulations of nucleation and growth in electrodeposition

Nucleation and growth during bulk electrodeposition is studied using kinetic Monte Carlo (KMC) simulations. Ion transport in solution is modeled using Brownian dynamics, and the kinetics of nucleation and growth are dependent on the probabilities of metal-on-substrate and metal-on-metal deposition. Using this approach, we make no assumptions about the nucleation rate, island density, or island distribution. The influence of the attachment probabilities and concentration on the time-dependent island density and current transients is reported. Various models have been assessed by recovering the nucleation rate and island density from the current-time transients.     

Grand canonical Monte Carlo simulation study of capillary condensation between nanoparticles

Capillary condensation at the nanoscale differs from condensation in the bulk phase, because it is a strong function of surface geometry and gas-surface interactions. Here, the effects of geometry on the thermodynamics of capillary condensation at the neck region between nanoparticles are investigated via a grand canonical Monte Carlo simulation using a two-dimensional lattice gas model. The microscopic details of the meniscus formation on various surface geometries are examined and compared with results of classical macromolecular theory, the Kelvin equation. We assume that the system is composed of a lattice gas and the surfaces of two particles are approximated by various shapes. The system is modeled on the basis of the molecular properties of the particle surface and lattice gas in our system corresponding to titania nanoparticles and tetraethoxy orthosilicate molecules, respectively. This system was chosen in order to reasonably emulate our previous experimental results for capillary condensation on nanoparticle surfaces. Qualitatively, our simulation results show that the specific geometry in the capillary zone, the surface-surface distance, and the saturation ratio are important for determining the onset and broadening of the liquid meniscus. The meniscus height increases continuously as the saturation ratio increases and the meniscus broadens faster above the saturation ratio of 0.90. The change of the radius of curvature of the particle surface affects the dimensions of the capillary zone, which drives more condensation in narrow zones and less condensation in wide zones. The increase of surface-surface distance results in the decrease of the meniscus height or even the disappearance of the meniscus entirely at lower saturation ratios. These effects are significant at the nanoscale and must be carefully considered in order to develop predictive relationships for meniscus height as a function of saturation conditions.     

Monte Carlo simulation of catalytic CO oxidation

A simple Monte Carlo model of the CO oxidation on a single-crystal catalyst surface is presented. The simulation model considers the following elementary reaction steps:

1. (1) chemisorption of a CO molecule, its surface migration and possible desorption

2. (2) physisorption of an O₂ molecule to a precursor state and its subsequent dissociative chemisorption

3. (3) activated reaction of adsorbed O and CO (the Langmuir - Hinshelwood reaction mechanism), formation of CO₂ and its rapid desorption.

The changes in the activation energy of reaction and in the adsorption energy of CO resulting from the interactions between adsorbed species are also considered. The model makes possible to monitor temperature programmed reaction spectra or reaction spectra obtained during changes of the ratio of the partial pressures of CO and O₂. The results of simulations for a Pd(111) single-crystal plane are compared with experiment.     

Monte Carlo simulation studies of polymer systems

Polymers molecules in solution or melt are more or less flexible and continuously change their shape and size. Thus, characteristic properties of the system fluctuate around statistical mean values which are dependent on the concentration of the solution, on the quality of the solvent used, and on the specific structure of the molecules, e.g. linear or star-branched. The most direct approach to these quantities on a molecular level are computer simulations. Due to restrictions of computer power fully atomistic simulations of macromolecules are presently still at the beginning but several arguments justify the use of simplified models. The most efficient way dealing with polymer systems are Monte Carlo simulations based on lattice chains, at least as long as static properties are of interest only. In the present paper a short introduction to the field is given and selected examples are presented in order to demonstrate the usefulness of these methods.     

Monte Carlo simulation of pulsed laser polymerization

Pulsed laser polymerization (PLP) has been simulated using a Monte Carlo procedure. From the results of numerous simulations it has been shown that the molecular weight distribution (MWD) consists primarily of two superimposed distributions. One distribution, a relatively broad background, represents the termination reactions during the dark period; the other, a rather sharply peaked distribution, represents the termination reactions occurring as a consequence of the large number of small radicals produced during the laser pulse. The postulate that the inflection point on the sharp peak can be used to calculate that the propagation rate constant was tested and found to be accurate to within 3%. The relative position of the broad and sharp distributions on the chain length scale determines the qualitative appearance of the overall MWD and is in turn governed by the rate of photoinitiation and the relative values of termination and propagation rate constants. This explains the qualitatively different shapes of MWD which have been experimentally observed. Finally, it is shown that the occurrence of chain length dependent termination reactions precludes the use of an analytical expression to deduce quantitative or qualitative information about the termination reaction from PLP data.     

DNA closed nanostructures: a structural and Monte Carlo simulation study

DNA nanoconstructs are obtained in solution by using six unique 42-mer DNA oligonucleotides, whose sequences have been designed to form a pseudohexagonal structure. The required flexibility is provided by the insertion of two non-base-paired thymines in the middle of each sequence that work as flexible hinges and constitute the corners of the nanostructure when formed. We show that hexagonally shaped nanostructures of about 7 nm diameter and their corresponding linear open constructs are formed by self-assembly of the specifically designed linear oligonucleotides. The structural and dynamical characterization of the nanostructure is obtained in situ for the first time by using dynamic light scattering (DLS), a noninvasive method that provides a fast dynamic and structural analysis and allows the characterization of the different synthetic DNA nanoconstructs in solution. A validation of the LS results is obtained through Monte Carlo (MC) simulations and atomic force microscopy (AFM). In particular, a mesoscale molecular model for DNA, developed by Knotts et al., is exploited to perform MC simulations and to obtain information about the conformations as well as the conformational flexibilities of these nanostructures, while AFM provides a very detailed particle analysis that yields an estimation of the particle size and size distribution. The structural features obtained by MC and AFM are in good agreement with DLS, showing that DLS is a fast and reliable tool for characterization of DNA nanostructures in solution.     

Percolation transition in supercritical water: a Monte Carlo simulation study

Computer simulations of water have been performed on the canonical ensemble at 15 different molecular number densities, ranging from 0.006 to 0.018 A-3, along the supercritical isotherm of 700 K, in order to characterize the percolation transition in the system. It is found that the percolation transition occurs at a somewhat higher density than what is corresponding to the supercritical extension of the boiling line. We have shown that the fractal dimension of the largest cluster and the probability of finding a spanning cluster are the most appropriate properties for the location of the true percolation threshold. Thus, percolation transition occurs when the fractal dimension of the largest cluster reaches 2.53, and the probability of finding a cluster that spans the system in at least one dimension and in all the three dimensions reaches 0.97 and 0.65, respectively. On the other hand, the percolation threshold cannot be accurately located through the cluster size distribution, as it is distorted by appearance of clusters crossing the finite simulated system even far below the percolation threshold. The structure of the largest water cluster is dominated by a linear, chainlike arrangement, which does not change noticeably until the largest cluster becomes infinite.