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In efforts to produce polymeric materials with tailored physical properties, significant interest has grown around the ability to control the spatial organization of nanoparticles in polymer nanocomposites. One way to achieve controlled particle arrangement is by grafting the nanoparticle surface with polymers that are compatible with the matrix, thus manipulating the interfacial interactions between the nanoparticles and the polymer matrix. Previous work has shown that the molecular weight of the grafted polymer, both at high grafting density and low grafting density, plays a key role in dictating the effective inter-particle interactions in a polymer matrix. At high grafting density nanoparticles disperse (aggregate) if the graft molecular weight is higher (lower) than the matrix molecular weight. At low grafting density the longer grafts can better shield the nanoparticle surface from direct particle-particle contacts than the shorter grafts and lead to the dispersion of the grafted particles in the matrix. Despite the importance of graft molecular weight, and evidence of non-trivial effects of polydispersity of chains grafted on flat surfaces, most theoretical work on polymer grafted nanoparticles has only focused on monodisperse grafted chains. In this paper, we focus on how bidispersity in grafted chain lengths affects the grafted chain conformations and inter-particle interactions in an implicit solvent and in a dense homopolymer polymer matrix. We first present the effects of bidispersity on grafted chain conformations in a single polymer grafted particle using purely Monte Carlo (MC) simulations. This is followed by calculations of the potential of mean force (PMF) between two grafted particles in a polymer matrix using a self-consistent Polymer Reference Interaction Site Model theory-Monte Carlo simulation approach. Monte Carlo simulations of a single polymer grafted particle in an implicit solvent show that in the bidisperse polymer grafted particles with an equal number of short and long grafts at low to medium grafting density, the short grafts are in a more coiled up conformation (lower radius of gyration) than their monodisperse counterparts to provide a larger free volume to the longer grafts so they can gain conformational entropy. The longer grafts do not show much difference in conformation from their monodisperse counterparts at low grafting density, but at medium grafting density the longer grafts exhibit less stretched conformations (lower radius of gyration) as compared to their monodisperse counterparts. In the presence of an explicit homopolymer matrix, the longer grafts are more compressed by the matrix homopolymer chains than the short grafts. We observe that the potential of mean force between bidisperse grafted particles has features of the PMF of monodisperse grafted particles with short grafts and monodisperse grafted particles with long grafts. The value of the PMF at contact is governed by the short grafts and values at large inter-particle distances are governed by the longer grafts. Further comparison of the PMF for bidisperse and monodisperse polymer grafted particles in a homopolymer matrix at varying parameters shows that the effects of matrix chain length, matrix packing fraction, grafting density, and particle curvature on the PMF between bidisperse polymer grafted particles are similar to those seen between monodisperse polymer grafted particles. [ABSTRACT FROM AUTHOR]

In the present paper, the adsorption thermodynamics of a lattice-gas model which mimics a nanoporous environment is studied by considering nonadditive interactions between the adsorbed particles. It is assumed that the energy linking a certain atom with any of its nearest neighbors strongly depends on the state of occupancy in the first coordination sphere of such an adatom. By means of Monte Carlo (MC) simulations in the grand canonical ensemble, adsorption isotherms and differential heats of adsorption were calculated. Their striking behaviors were analyzed and discussed in terms of the low temperature phases formed in the system. Finally, the results obtained from MC simulations were compared with the corresponding ones from Bragg-Williams approximation. [ABSTRACT FROM AUTHOR]

The selectivity filter of the L-type calcium channel works as a Ca2 + binding site with a very large affinity for Ca2 + versus Na+. Ca2 + replaces half of the Na+ ions in the filter even when these ions are present in 1 μM and 30 mM concentrations in the bath, respectively. The energetics of this strong selectivity is analyzed in this paper. We use Widom's particle insertion method to compute the space-dependent profiles of excess chemical potential in our grand canonical Monte Carlo simulations. These profiles define the free-energy landscape for the various ions. Following Gillespie [Biophys. J. 94, 1169 (2008)], the difference of the excess chemical potentials for the two competing ions defines the advantage that one of the ions has over the other in the competition for space in the crowded selectivity filter. These advantages depend on ionic bath concentrations: the ion that is present in the bath in larger quantity (Na+) has the 'number' advantage which is balanced by the free-energy advantage of the other ion (Ca2 +). The excess chemical potentials are decomposed into hard sphere exclusion and electrostatic components. The electrostatic terms correspond to interactions with the mean electric field produced by ions and induced charges as well to ionic correlations beyond the mean field description. Dielectrics are needed to produce micromolar Ca2 + versus Na+ selectivity in the L-type channel. We study the behavior of these terms with changes in bath concentrations of ions, charges, and diameters of ions, as well as geometrical parameters such as radius of the pore and the dielectric constant of the protein. Ion selectivity in calcium binding proteins probably has a similar mechanism. [ABSTRACT FROM AUTHOR]

For the atoms with Z <= 11, energies obtained using the 'initiator' extension to full configuration interaction quantum Monte Carlo (i-FCIQMC) come to within statistical errors of the FCIQMC results. As these FCIQMC values have been shown to converge onto FCI results, the i-FCIQMC method allows similar accuracy to be achieved while significantly reducing the scaling with the size of the Slater determinant space. The i-FCIQMC electron affinities of the Z <= 11 atoms in the aug-cc-pVXZ basis sets are presented here. In every case, values are obtained to well within chemical accuracy [the mean absolute deviation (MAD) from the relativistically corrected experimental values is 0.41 mEh], and significantly improve on coupled cluster with singles, doubles and perturbative triples [CCSD(T)] results. Since the only remaining source of error is basis set incompleteness, we have investigated using CCSD(T)-F12 contributions to correct the i-FCIQMC results. By doing so, much faster convergence with respect to basis set size may be achieved for both the electron affinities and the FCIQMC ionization potentials presented in a previous paper. With this F12 correction, the MAD can be further reduced to 0.13 mEh for the electron affinities and 0.31 mEh for the ionization potentials. [ABSTRACT FROM AUTHOR]

Using Monte Carlo simulation methods in the grand canonical and semigrand canonical ensembles, we study the phase behavior of two-dimensional symmetrical binary mixtures of Lennard-Jones particles. We discuss the interplay between the demixing transition in a liquid and the freezing in detail. Phase diagrams for several systems characterized by different parameters describing interactions in the system are presented. It is explicitly demonstrated that different scenarios involving demixing and freezing transitions, described in our earlier paper [A. Patrykiejew and S. Sokołowski, Phys. Rev. E, 81, 012501 (2010)], are possible. In one class of systems, the λ-line representing a continuous demixing transition in a liquid phase starts at the liquid side of either the vapor-liquid or liquid-solid coexistence. The second class involves the systems in which the λ-line begins at the liquid side of the vapor-liquid coexistence, in the lower critical end point, and then terminates at the liquid side of the liquid-solid coexistence, in the upper critical end point. It is also shown that in such systems the solid phase may undergo a demixing transition at the temperature above the upper critical end point. [ABSTRACT FROM AUTHOR]

Quantum mechanics for many-body systems may be reduced to the evaluation of integrals in 3N dimensions using Monte Carlo, providing the Quantum Monte Carlo ab initio methods. Here we limit ourselves to expectation values for trial wave functions, that is to variational quantum Monte Carlo. Almost all previous implementations employ samples distributed as the physical probability density of the trial wave function, and assume the central limit theorem to be valid. In this paper we provide an analysis of random error in estimation and optimization that leads naturally to new sampling strategies with improved computational and statistical properties. A rigorous lower limit to the random error is derived, and an efficient sampling strategy presented that significantly increases computational efficiency. In addition the infinite variance heavy tailed random errors of optimum parameters in conventional methods are replaced with a Normal random error, strengthening the theoretical basis of optimization. The method is applied to a number of first row systems and compared with previously published results. [ABSTRACT FROM AUTHOR]

Following the discovery of slow fluctuations in the catalytic activity of an enzyme in single-molecule experiments, it has been shown that the classical Michaelis–Menten (MM) equation relating the average enzymatic velocity and the substrate concentration may hold even for slowly fluctuating enzymes. In many cases, the average velocity is that given by the MM equation with time-averaged values of the fluctuating rate constants and the effect of enzyme fluctuations is simply averaged out. The situation is quite different for a sequence of reactions. For colocalization of a pair of enzymes in a sequence to be effective in promoting reaction, the second must be active when the first is active or soon after. If the enzymes are slowly varying and only rarely active, the product of the first reaction may diffuse away before the second enzyme is active, and colocalization may have little value. Even for single-step reactions the interplay of reaction and diffusion with enzyme fluctuations leads to added complexities, but for multistep reactions the interplay of reaction and diffusion, cell size, compartmentalization, enzyme fluctuations, colocalization, and segregation is far more complex than for single-step reactions. In this paper, we report the use of stochastic simulations at the level of whole cells to explore, understand, and predict the behavior of single- and multistep enzyme-catalyzed reaction systems exhibiting some of these complexities. Results for single-step reactions confirm several earlier observations by others. The MM relationship, with altered constants, is found to hold for single-step reactions slowed by diffusion. For single-step reactions, the distribution of enzymes in a regular grid is slightly more effective than a random distribution. Fluctuations of enzyme activity, with average activity fixed, have no observed effects for simple single-step reactions slowed by diffusion. Two-step sequential reactions are seen to be slowed by segregation of the enzymes for each step, and results of the calculations suggest limits for cell size. Colocalization of enzymes for a two-step sequence is seen to promote reaction, and rates fall rapidly with increasing distance between enzymes. Low frequency fluctuations of the activities of colocalized enzymes, with average activities fixed, can greatly reduce reaction rates for sequential reactions. [ABSTRACT FROM AUTHOR]

Functionalizing nanoparticles with organic ligands, such as oligomers, polymers, DNA, and proteins, is an attractive way to manipulate the interfacial interactions between the nanoparticles and the medium the particles are placed in, and thus control the nanoparticle assembly. In this paper we have conducted a Monte Carlo simulation study on copolymer grafted spherical nanoparticles to show the tremendous potential of using monomer sequence on the copolymers to tune the grafted chain conformation, and thus the effective interactions between copolymer grafted nanoparticles. We have studied AB copolymers with alternating, multiblock, or diblock sequences, where either A monomers or B monomers have monomer-monomer attractive interactions. Our focus has been to show the nontrivial effect of monomer sequence on the conformations of the grafted copolymers at various particle diameters, grafting densities, copolymer chain lengths, and monomer-monomer interactions in an implicit small molecule solvent. We observe that the monomer sequence, particle diameter, and grafting density dictate whether (a) the grafted chains aggregate to bring attractive monomers from multiple grafted chains together (interchain and intrachain monomer aggregation) if the enthalpy gained by doing so offsets the entropic loss caused by stretching of chains, or (b) each grafted chain folds onto itself to bring its attractive monomers together (only intrachain monomer aggregation) if the entropic loss from interchain aggregation cannot be overcome by the enthalpic gain. For six copolymers of chain length N=24 grafted on a spherical particle of diameter D=4, interchain and intrachain monomer aggregation occurs, and the radius of gyration varies nonmonotonically with increasing blockiness of the monomer sequence. At larger particle diameters the grafted chains transition to purely intrachain monomer aggregation. The radius of gyration varies monotonically with monomer sequence for intrachain monomer aggregation because as the sequence becomes blockier (like monomers are grouped together), the copolymer chain has to fold less compactly to maximize the enthalpically favorable contacts while maintaining high conformational entropy. The radius of gyration of alternating and diblock copolymers scales with chain length N through a power law g2>1/2=αNν with the prefactor α and scaling exponent ν, varying with monomer sequence and monomer-monomer attraction strength. [ABSTRACT FROM AUTHOR]

A pillared interlayered clay is represented by a two-dimensional quenched charged disordered medium, in which the pillar configuration is produced by the quench of a two-dimensional electrolyte and the subsequent removal of the anions (that act as a template). The cation charge is counterbalanced by a neutralizing background that is an ideal representation of the layer’s negative charge in the experimental system. In this paper we investigate the adsorption of electrolyte particles in this charged disordered medium resorting both to the use of the replica Ornstein–Zernike equation in the hypernetted chain approximation and grand canonical Monte Carlo simulations. The theoretical approach qualitatively reproduces the simulated behavior of the adsorbed fluids. Theoretical estimates of the material porosities obtained for various types of pillar distributions are in good agreement with the simulation. We investigate the influence of the matrix on correlation functions and adsorption isotherms. [ABSTRACT FROM AUTHOR]

In a recent communication [V. Jadhao and N. Makri, J. Chem. Phys. 129, 161102 (2008)], we introduced an iterative Monte Carlo (IMC) path integral methodology for calculating complex-time correlation functions. This method constitutes a stepwise evaluation of the path integral on a grid selected by a Monte Carlo procedure, circumventing the exponential growth of statistical error with increasing propagation time, while realizing the advantageous scaling of importance sampling in the grid selection and integral evaluation. In the present paper, we present an improved formulation of IMC, which is based on a bead-adapted sampling procedure; thus leading to grid point distributions that closely resemble the absolute value of the integrand at each iteration. We show that the statistical error of IMC does not grow upon repeated iteration, in sharp contrast to the performance of the conventional path integral approach which leads to exponential increase in statistical uncertainty. Numerical results on systems with up to 13 degrees of freedom and propagation up to 30 times the “thermal” time hβ/2 illustrate these features. [ABSTRACT FROM AUTHOR]

The kinetic Monte Carlo (KMC) method provides a versatile tool to investigate the mechanisms underlying photocurrent generation in nanostructured organic solar cells. Currently available algorithms can already support the development of more cost-efficient photovoltaic devices, but so far no attempt has been made to test the validity of some fundamental model assumptions and their impact on the simulation result. A meaningful example is given by the treatment of the electrostatic interactions. In most KMC models, electrostatic interactions are approximated by means of cutoff based potentials, irrespective of the long-range nature of the Coulomb interaction. In this paper, the reliability of such approximation is tested against the exact Ewald sum. The results under short-circuit and flat-band conditions show that use of cutoff-based potentials tends to underestimate real device performance, in terms of internal quantum efficiency and current density. Together with this important finding, we formalize other methodological aspects which have been scarcely discussed in the literature. [ABSTRACT FROM AUTHOR]

In this paper we take a few steps further in the development of an approach based on the use of an artificial neural network (ANN) to introduce long-range chemical effects and zero temperature relaxation (elastic strain) effects in a rigid lattice atomistic kinetic Monte Carlo (AKMC) model. The ANN is trained to predict the vacancy migration energies as calculated given an interatomic potential with the nudged elastic band method, as functions of the local atomic environment. The kinetics of a single-vacancy migration is thus predicted as accurately as possible, within the limits of the given interatomic potential. The detailed procedure to apply this method is described and analyzed in detail. A novel ANN training algorithm is proposed to deal with the necessarily large number of input variables to be taken into account in the mathematical regression of the migration energies. The application of the ANN-based AKMC method to the simulation of a thermal annealing experiment in Fe–20%Cr alloy is reported. The results obtained are found to be in better agreement with experiments, as compared to already published simulations, where no atomic relaxation was taken into account and chemical effects were only heuristically allowed for. [ABSTRACT FROM AUTHOR]

In this paper, we performed carrier transport simulation to understand the unusual temperature dependence of the carrier mobility observed in nematic liquid crystals. For this purpose, we made a model liquid crystalline system consisting of biaxial Gay–Berne particles, and then we simulated hopping transport between these particles. The hopping rate was formulated suitably for the biaxial Gay–Berne particles based on the investigation of the electronic overlaps between actual aromatic molecules. The carrier transport simulation was performed by master equation method on the model system prepared by N-P-T ensemble Monte Carlo simulation. We reproduced gradual mobility increase in the nematic phase as a result of the change in the short range molecular order. [ABSTRACT FROM AUTHOR]

We consider a nearly (or quasi) uniform gas of interacting electrons for which spin statistics play a crucial role. A previously developed procedure, based on the extension of the Levy–Lieb constrained search principle and Monte Carlo sampling of electron configurations in space, allows us to approximate the form of the kinetic-energy functional. For a spinless electron gas, this procedure led to a correlation term, which had the form of the Shannon entropy, but the resulting kinetic-energy functional does not satisfy the Lieb–Thirring inequality, which is rigorous and one of the most general relations regarding the kinetic energy. In this paper, we show that when the fermionic character of the electrons is included via a statistical spin approach, our procedure leads to correlation terms, which also have the form of the Shannon entropy and the resulting kinetic-energy functional does satisfy the Lieb–Thirring inequality. In this way we further strengthen the connection between Shannon entropy and electron correlation and, more generally, between information theory and quantum mechanics. [ABSTRACT FROM AUTHOR]

We have performed a study of charge transport in λ-DNA using a recently developed model based on Marcus theory and dynamic Monte Carlo simulations. The model accounts for charge delocalization over multiple adjacent identical nucleobases. Such delocalized states are found to act as traps for charge transport and therefore have a negative impact on the charge carrier (hole) mobility. Both the electric field and temperature dependence of the mobility in λ-DNA is reported in this paper. Furthermore, the detailed information produced by the simulation allow us to plot the progress of a hole propagating through the DNA sequence and this is used to identify the bottlenecks that limits the charge transport process. [ABSTRACT FROM AUTHOR]

The classical bond-fluctuation model (BFM) is an efficient lattice Monte Carlo algorithm for coarse-grained polymer chains where each monomer occupies exclusively a certain number of lattice sites. In this paper we propose a generalization of the BFM where we relax this constraint and allow the overlap of monomers subject to a finite energy penalty [variant_greek_epsilon]. This is done to vary systematically the dimensionless compressibility g of the solution in order to investigate the influence of density fluctuations in dense polymer melts on various static properties at constant overall monomer density. The compressibility is obtained directly from the low-wave vector limit of the static structure factor. We consider, e.g., the intrachain bond-bond correlation function P(s) of two bonds separated by s monomers along the chain. It is shown that the excluded volume interactions are never fully screened for very long chains. If distances smaller than the thermal blob size are probed (s≤g) the chains are swollen according to the classical Fixman expansion where, e.g., P(s)∼g-1s-1/2. More importantly, the polymers behave on larger distances (s>g) like swollen chains of incompressible blobs with P(s)∼g0s-3/2. [ABSTRACT FROM AUTHOR]

In this paper a lattice model for the diffusional transport of particles in the interphase cell nucleus is proposed. The dynamical behavior of single chains on the lattice is investigated and Rouse scaling is verified. Dynamical dense networks are created by a combined version of the bond fluctuation method and a Metropolis Monte Carlo algorithm. Semidilute behavior of the dense chain networks is shown. By comparing diffusion of particles in a static and a dynamical chain network, we demonstrate that chain diffusion does not alter the diffusion process of small particles. However, we prove that a dynamical network facilitates the transport of large particles. By weighting the mean square displacement trajectories of particles in the static chain, network data from the dynamical network can be reconstructed. Additionally, it is shown that subdiffusive behavior of particles on short time scales results from trapping processes in the crowded environment of the chain network. In the presented model a protein with 30 nm diameter has an effective diffusion coefficient of 1.24×10-11 m2/s in a chromatin fiber network. [ABSTRACT FROM AUTHOR]

In this paper, we carry out variational Monte Carlo and diffusion Monte Carlo (DMC) calculations for Li2(1Σg+)(4He)N and Li2(3Σu+)(4He)N with N up to 30 and discuss in detail the results of our computations. After a comparison between our DMC energies with the “exact” discrete variable representation values for the species with one 4He, in order to test the quality of our computations at 0 K, we analyze the structural features of the whole range of doped clusters. We find that both species reside on the droplet surface, but that their orientation is spin driven, i.e., the singlet molecule is perpendicular and the triplet one is parallel to the droplet’s surface. We have also computed quantum vibrational relaxation rates for both dimers in collision with a single 4He and we find them to differ by orders of magnitude at the estimated surface temperature. Our results therefore confirm the findings from a great number of experimental data present in the current literature and provide one of the first attempts at giving an accurate, fully quantum picture for the nanoscopic properties of alkali dimers in 4He clusters. [ABSTRACT FROM AUTHOR]

In this paper we study the structure of highly confined mixtures of polar and nonpolar macroparticles in an external field by Monte Carlo simulation in the canonical ensemble. Without attempting a systematic investigation of the model, several effects including confinement, polarization, and solvation forces are considered. In particular, we show that layering at different length scales can be obtained in mixtures of differently sized particles subject to an external electric field. [ABSTRACT FROM AUTHOR]

The Inhomogeneous Stochastic Simulation Algorithm (ISSA) is a variant of the stochastic simulation algorithm in which the spatially inhomogeneous volume of the system is divided into homogeneous subvolumes, and the chemical reactions in those subvolumes are augmented by diffusive transfers of molecules between adjacent subvolumes. The ISSA can be prohibitively slow when the system is such that diffusive transfers occur much more frequently than chemical reactions. In this paper we present the Multinomial Simulation Algorithm (MSA), which is designed to, on the one hand, outperform the ISSA when diffusive transfer events outnumber reaction events, and on the other, to handle small reactant populations with greater accuracy than deterministic-stochastic hybrid algorithms. The MSA treats reactions in the usual ISSA fashion, but uses appropriately conditioned binomial random variables for representing the net numbers of molecules diffusing from any given subvolume to a neighbor within a prescribed distance. Simulation results illustrate the benefits of the algorithm. [ABSTRACT FROM AUTHOR]

In view of the wide success of molecular quasichemical theory of liquids, this paper develops the soft-cutoff version of that theory. This development allows molecular dynamics simulations to be used for the calculation of solvation free energy, whereas the hard-cutoff version of the theory needs Monte Carlo simulations. This development also shows how fluids composed of molecules with smooth repulsive interactions can be treated analogously to the molecular-field theory of the hard-sphere fluid. In the treatment of liquid water, quasichemical theory with soft-cutoff conditioning does not change the fundamental convergence characteristics of the theory using hard-cutoff conditioning. In fact, hard cutoffs are found here to work better than softer ones in that case. [ABSTRACT FROM AUTHOR]

In this paper, we construct an effective model for the dynamics of an excluded-volume chain under confinement by extending the formalism of Rouse modes. We make specific predictions about the behavior of the modes for a single polymer confined to a tube. The results are tested against Monte Carlo simulations using the bond-fluctuation algorithm which uses a lattice representation of the polymer chain with excluded-volume effects. [ABSTRACT FROM AUTHOR]

In robust biological systems, wide deviations from highly controlled normal behavior may be rare, yet they may result in catastrophic complications. While in silico analysis has gained an appreciation as a tool to offer insights into system-level properties of biological systems, analysis of such rare events provides a particularly challenging computational problem. This paper proposes an efficient stochastic simulation method to analyze rare events in biochemical systems. Our new approach can substantially increase the frequency of the rare events of interest by appropriately manipulating the underlying probability measure of the system, allowing high-precision results to be obtained with substantially fewer simulation runs than the conventional direct Monte Carlo simulation. Here, we show the algorithm of our new approach, and we apply it to the analysis of rare deviant transitions of two systems, resulting in several orders of magnitude speedup in generating high-precision estimates compared with the conventional Monte Carlo simulation. [ABSTRACT FROM AUTHOR]

We solve the Percus–Yevick equation in even dimensions by reducing it to a set of simple integrodifferential equations. This work generalizes an approach we developed previously for hard disks. We numerically obtain both the pair correlation function and the virial coefficients for a fluid of hyperspheres in dimensions d=4, 6, and 8, and find good agreement with the available exact results and Monte Carlo simulations. This paper confirms the alternating character of the virial series for d≥6 and provides the first evidence for an alternating character for d=4. Moreover, we show that this sign alternation is due to the existence of a branch point on the negative real axis. It is this branch point that determines the radius of convergence of the virial series, whose value we determine explicitly for d=4, 6, 8. Our results complement, and are consistent with, a recent study in odd dimensions [R. D. Rohrmann et al., J. Chem. Phys. 129, 014510 (2008)]. [ABSTRACT FROM AUTHOR]

Long polyglutamine chains have been associated with a number of neurodegenerative diseases. These include Huntington’s disease, where expanded polyglutamine (PolyQ) sequences longer than 36 residues are correlated with the onset of symptoms. In this paper we study the folding pathway of a 54-residue PolyQ chain into a β-helical structure. Transition path sampling Monte Carlo simulations are used to generate unbiased reactive pathways between unfolded configurations and the folded β-helical structure of the polyglutamine chain. The folding process is examined in both explicit water and an implicit solvent. Both models reveal that the formation of a few critical contacts is necessary and sufficient for the molecule to fold. Once the primary contacts are formed, the fate of the protein is sealed and it is largely committed to fold. We find that, consistent with emerging hypotheses about PolyQ aggregation, a stable β-helical structure could serve as the nucleus for subsequent polymerization of amyloid fibrils. Our results indicate that PolyQ sequences shorter than 36 residues cannot form that nucleus, and it is also shown that specific mutations inferred from an analysis of the simulated folding pathway exacerbate its stability. [ABSTRACT FROM AUTHOR]

Coarse-grained (CG) modeling has emerged as a promising tool to bridge the gap between the temporal and spatial scales of all-atom (AA) simulations and those of many important biological processes. Resolution exchange, a variant of the replica exchange method, combines the efficiency of CG simulation and the accuracy of AA simulation by swapping configurations between AA and CG simulations. The crucial step in a resolution exchange move is to rigorously reconstruct the high-resolution system from models at coarser resolutions. In this paper, configurational-bias Monte Carlo is adopted as a general method to rebuild the missing degrees of freedom rigorously for CG models and for the first time combined with resolution exchange. The new approach is demonstrated on an alkane and a peptide system. It is found that the efficiency of resolution exchange depends significantly on the quality of the CG model. [ABSTRACT FROM AUTHOR]

The adsorption/desorption isotherms measured in nanoporous materials generally present a hysteresis. The hysteresis shrinks upon increasing the temperature (for a given pore size) or decreasing the pore size (for a given temperature), until it finally disappears at the so-called hysteresis (or pseudocritical) temperature Th or hysteresis (or pseudocritical) pore size Rh, not to be confused with a true critical point. In this paper, a Monte Carlo approach allowed calculating the surface free energy of confined fluid along the adsorption/desorption isotherms for various cylindrical pore sizes and temperatures. A simple phenomenological model then allowed exploiting these results to determine the relation between Th and Rh. The prediction is compared to various literature models and experimental data, showing agreement within uncertainties. On the other hand, the simulations cannot be used directly to predict Th and Rh since they significantly overestimate the hysteresis width. The model predicts a nonlinear relation between the reduced hysteresis temperature and the inverse pore radius. [ABSTRACT FROM AUTHOR]

In this paper, we solve quantum many-body problem by propagating ensembles of trajectories and guiding waves in physical space. We introduce the “effective potential” correction within the recently proposed time-dependent quantum Monte Carlo methodology to incorporate the nonlocal quantum correlation effects between the electrons. The associated correlation length is calculated by adaptive kernel density estimation over the walker distribution. The general formalism is developed and tested on one-dimensional helium atom in laser field of different intensities and carrier frequencies. Good agreement with exact results for the atomic ionization is obtained. [ABSTRACT FROM AUTHOR]

Although a lattice Monte Carlo method provides an effective, simple, and fast way to study thermodynamic properties of substitutional alloys, it cannot treat by itself the off-lattice effects, such as thermal vibrations and local distortions. Therefore, even if the interaction among atoms at lattice points is calculated accurately by means of first-principles calculations, the lattice Monte Carlo simulation overestimates the order-disorder phase transition temperature. In this paper, we treat this problem in the investigation of the FePt alloy, which has recently attracted considerable interest in its magnetic properties. We apply a simple version of the potential renormalization theory to determine the interaction among atoms, including partly the off-lattice effects by means of first-principles calculations. Then, we use the interaction to perform a lattice Monte Carlo simulation of the FePt alloy on a fcc lattice. From the results, we find that the transition temperature obtained after the present renormalization procedure becomes closer to the experimental value. [ABSTRACT FROM AUTHOR]

This paper deals with the application of the Monte Carlo simulation method for modeling of adsorption of chiral molecules on a planar surface patterned with active binding sites. The enantiomers are assumed to be rigid chains composed of four identical segments, each occupying one binding site. The energy of interaction between a segment and a binding site is characterized by [variant_greek_epsilon]a and [variant_greek_epsilon]b depending whether the site is active or it is inert. We demonstrate that [variant_greek_epsilon]a>[variant_greek_epsilon]b imposed in our previous work [J. Chem. Phys. 126, 144709 (2007)] is not a necessary condition for the separation of enantiomers form their racemate. The obtained results suggest that the major source of enantioselectivity of the surface lies in its geometrical properties. The active adsorption sites which form the chiral pattern do not have to interact stronger with the adsorbing molecules to ensure enantioseparation. In this context, the proposed chiral surface offers more flexibility in selection of the energetic properties of the binding sites. This, in practice, means wider possibilities of manipulating chemical composition of the surface. [ABSTRACT FROM AUTHOR]

Monte Carlo simulations of a model fluid in which the particles interact via a continuous potential that has a logarithmic divergence at a pair separation of σ, which we introduced in J. G. Powles et al., Proc. R. Soc. London, Ser. A 455, 3725 (1999), have been carried out. The potential has the form, [lowercase_phi_synonym](r)=-ε ln(f(r)), where ε sets the energy scale and f(r)=1-(σ/r)m. The value of m chosen was 12 but the qualitative trends depend only weakly on the value of m, providing it is greater than 3. The potential is entirely repulsive and has a logarithmic divergence as ∼-ln(r/σ-1) in the r→σ limit. Predictions of the previous paper that the internal energy can be computed at all temperatures using the standard statistical mechanics formula for continuous potentials are verified here. The pressure can be calculated using the usual virial expression for continuous potentials, although there are practical limitations in resolving the increasingly important contribution from the r→σ limit at reduced temperatures greater than ∼5. The mean square force ≤F2≥ and infinite frequency shear G∞ and bulk K∞ moduli are only finite for T*=kBT/ε<1. The logarithmic fluid’s physical properties become increasingly more like that of the hard sphere fluid with increasing temperature, showing a sharp transition in the behavior of the mean square force and infinite frequency elastic constants at T*=1. The logarithmic fluid is shown to exhibit a solid-fluid phase transition. [ABSTRACT FROM AUTHOR]

In this paper, we describe two types of effective events for describing heat transfer in a kinetic Monte Carlo (KMC) simulation that may involve stochastic chemical reactions. Simulations employing these events are referred to as KMC-TBT and KMC-PHE. In KMC-TBT, heat transfer is modeled as the stochastic transfer of “thermal bits” between adjacent grid points. In KMC-PHE, heat transfer is modeled by integrating the Poisson heat equation for a short time. Either approach is capable of capturing the time dependent system behavior exactly. Both KMC-PHE and KMC-TBT are validated by simulating pure heat transfer in a rod and a square and modeling a heated desorption problem where exact numerical results are available. KMC-PHE is much faster than KMC-TBT and is used to study the endothermic desorption of a lattice gas. Interesting findings from this study are reported. [ABSTRACT FROM AUTHOR]

In this paper, based on the stochastic model of NO reduction by CO on Pt crystal surfaces and taking Gaussian colored noise as external fluctuations of the NO partial pressure, we study the effect of the colored noise on the internal noise-induced stochastic oscillations (INSOs) and the effect of internal noise on the colored noise-induced stochastic oscillations (CNSOs). It is found that the INSO can be enhanced by the colored noise with appropriate correlation time or noise strength and, interestingly, the CNSO can be enhanced by the internal noise as well and, moreover, the enhanced CNSO can reach the best oscillatory states repetitively via proper internal noises. This effect of the internal noise is different from its effect on the stochastic oscillations induced by the external Gaussian white noise, which probably results from the interaction of the correlated colored noise and the internal noise. [ABSTRACT FROM AUTHOR]

This paper describes the application of a relatively simple, but computationally tractable, “particle-on-a-sphere” (POS) model for quantum-mechanical calculation of large-amplitude, H atom dynamics in polyatomic hydrides (XHn), based on radially relaxed, two-dimensional angular motion of H atoms on the surface of a sphere. This work focuses on systems with many degrees of freedom, i.e., XH4 (eight dimensional) and XH5 (ten dimensional), with corresponding molecular analogs of CH4 and CH5+ and is applicable to rovibrationally excited states with J>=0. A pairwise-additive potential fit for CH5+, which yields remarkable agreement with geometries, energies, and barrier heights on the full-dimensional surface of Brown et al. [J. Chem. Phys. 121, 4105 (2004)] is presented. Comparisons with experimental data and diffusion quantum Monte Carlo (DMC) methods test convergence for the POS model and provide insight into multidimensional quantum rovibrational dynamics. In particular, POS energy-level patterns for a series of scaled CH5+ potentials indicate an absence of strong tunneling behavior, consistent with the highly delocalized wave functions, large zero-point energies, and small interconversion barriers noted in previous DMC studies of Brown et al. [ABSTRACT FROM AUTHOR]

Proteins contain many voids, which are unfilled spaces enclosed in the interior. A few of them have shapes compatible to ligands and substrates and are important for protein functions. An important general question is how the need for maintaining functional voids is influenced by, and affects other aspects of proteins structures and properties (e.g., protein folding stability, kinetic accessibility, and evolution selection pressure). In this paper, we examine in detail the effects of maintaining voids of different shapes and sizes using two-dimensional lattice models. We study the propensity for conformations to form a void of specific shape, which is related to the entropic cost of void maintenance. We also study the location that voids of a specific shape and size tend to form, and the influence of compactness on the formation of such voids. As enumeration is infeasible for long chain polymer, a key development in this work is the design of a novel sequential Monte Carlo strategy for generating large number of sample conformations under very constraining restrictions. Our method is validated by comparing results obtained from sampling and from enumeration for short polymer chains. We succeeded in accurate estimation of entropic cost of void maintenance, with and without an increasing number of restrictive conditions, such as loops forming the wall of void with fixed length, with additionally fixed starting position in the sequence. Additionally, we have identified the key structural properties of voids that are important in determining the entropic cost of void formation. We have further developed a parametric model to predict quantitatively void entropy. Our model is highly effective, and these results indicate that voids representing functional sites can be used as an improved model for studying the evolution of protein functions and how protein function relates to protein stability. [ABSTRACT FROM AUTHOR]

The influence of intermittent convection movements on electrochemical voltammograms is investigated. When the bath temperature rises to 315 K, the voltammograms exhibit irregular plateaus that differ for independent voltammetry scans, even when the setup is maintained under exactly the same conditions. In this paper, we show that such behavior can be caused by convection movements that develop in the electrolytic cell as a consequence of velocity fluctuations, since no bubbles or regular convective patterns are observed at this temperature. Theoretical current-potential curves for the heterogeneous deposition of metals on silicon electrodes is derived from a model consisting of a one-dimensional balance equation that includes diffusion, convection, and reaction through a time-dependent boundary condition. We obtain the current density associated with the adsorption of particles on the surface and, through this expression, we consider the effect of constant convective velocities on voltammograms. Finally, we examine the effect of random convective movements, described by a Monte Carlo algorithm that takes into account the random temporal fluctuations around a null convective current. The model predicts accentuated fluctuations on the current profiles, especially on the current plateaus that correspond to a stationary current regime. The validity of the theoretical model is checked against experimental data. [ABSTRACT FROM AUTHOR]

A dynamic Monte Carlo simulation of the collapse transition of polymer chains is presented. The chains are represented as self-avoiding walks on the simple cubic lattice with a nearest-neighbor contact potential to model the effect of solvent quality. The knot state of the chains is determined using the knot group procedure presented in the accompanying paper. The equilibrium knot spectrum and the equilibrium rms radius of gyration as functions of the chain length and the contact potential are reported. The collapse transition was studied following quenches from good-to poor-solvent conditions. Our results confirm the prediction that the newly formed globule is not yet at equilibrium, since it has not yet achieved its equilibrium knot spectrum. For our model system, the relaxation of the knot spectrum is about an order of magnitude slower than that of the radius of gyration. The collapse transition is also studied for a model in which both ends of the chain remain in good-solvent conditions. Over the time scale of these simulations, knot formation is frustrated in this inhomogeneous model, verifying that the mechanism of knotting is the tunneling of chain ends in and out of the globule. [ABSTRACT FROM AUTHOR]

In Part I [R. E. Beckham and M. A. Bevan, J. Chem. Phys. 127, 164708 (2007)], results were presented for the sedimentation equilibrium of concentrated colloidal dispersions using confocal scanning laser microscopy experiments, Monte Carlo (MC) simulations, and a local density approximation perturbation theory. In this paper, we extended the modeling effort on those systems to include nonlocal density functional theory (DFT), which is capable of predicting the microstructure of the sediment at length scales comparable to the colloidal particle dimension. Specifically, we use a closure-based DFT formulation to predict interfacial colloidal sedimentation equilibrium density profiles. The colloid-colloid and colloid-surface interactions were modeled with DLVO screened electrostatic potentials using parameters taken directly from the experimental work. The DFT profiles were compared to the experimental and MC results from Part I. Good agreement was found for relatively dilute interfacial colloidal fluids, but agreement was less satisfactory as interfacial layering became more pronounced for conditions approaching the onset of interfacial crystallization. We also applied DFT in an inverse sense using the measured colloid density profile to extract the underlying colloid-surface potential; this can be thought of as a microscopic analog to the well-known procedure of using the macroscopic (coarse-grained) density profile to extract the osmotic equation of state. For the dilute interfacial fluid, the inverse DFT calculations reproduced the true colloid-surface potential to within 0.5kT at all elevations. [ABSTRACT FROM AUTHOR]

This paper reports confocal microscopy measurements of inhomogeneous colloidal sedimentation equilibrium profiles near planar wall surfaces for conditions when colloid dimensions are comparable to the characteristic gravitational length scale. The intensity based confocal method developed in this work enables real-space measurements of one-dimensional density profiles of Brownian colloids without identifying many single colloid centers in large imaging volumes. Measured sedimentation equilibrium profiles for single-phase interfacial fluids and for coexisting inhomogeneous fluid and solid phases are in agreement with a perturbation theory and Monte Carlo simulations within the local density approximation. Monte Carlo simulated colloid scale density profiles display some minor differences with confocal images in terms of microstructural transitions involving the onset of interfacial crystallization and the precise elevation of the fluid-solid interface. These discrepancies are attributed to polydispersity unaccounted for in the analyses, sensitivity of the perturbation theory to the effective hard sphere size, and the influence of ensemble, system size, and box shape in Monte Carlo simulations involving anisotropic/inhomogeneous solids. Successful demonstration of intensity based confocal microscopy provides a basis for future measurements of three-dimensional colloidal interactions, dynamics, and structure near surfaces. [ABSTRACT FROM AUTHOR]

Urate oxidase from Asperigillus flavus has been shown to be a model protein for studying the effects of polyethylene glycol (PEG) on the crystallization of large proteins. Extensive experimental studies based on small angle x-ray scattering [Vivarès and Bonneté, J. Phys. Chem. B 108, 6498 (2004)] have determined the effects of salt, pH, temperature, and most importantly PEG on the crystallization of this protein. Recently, some aspects of the phase diagram have also been determined experimentally. In this paper, we use Monte Carlo techniques to predict the phase diagram for urate oxidase in solution with PEG, including the liquid-liquid and liquid-solid coexistence curves. The model used includes an electrostatic interaction, van der Waals attraction, and a polymer-induced depletion interaction [Vivarès et al., Eur. Phys. J. E 9, 15 (2002)]. Results from the simulation are compared with experimental results. [ABSTRACT FROM AUTHOR]

Monte Carlo simulations are used to calculate the exact potential of mean force between charged globular proteins in aqueous solution. The aim of the present paper is to study the influence of the ions of the added salt on the effective interaction between these nanoparticles. The charges of the model proteins, either identical or opposite, are either central or distributed on a discrete pattern. Contrarily to Poisson–Boltzmann predictions, attractive, and repulsive direct forces between proteins are not screened similarly. Moreover, it has been shown that the relative orientations of the charge patterns strongly influence salt-mediated interactions. More precisely, for short distances between the proteins, ions enhance the difference of the effective forces between (i) like-charged and oppositely charged proteins, (ii) attractive and repulsive relative orientations of the proteins, which may affect the selectivity of protein/protein recognition. Finally, such results observed with the simplest models are applied to a more elaborate one to demonstrate their generality. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of the thermodynamics of a model glass former. We have performed equilibrium sampling of a popular binary Lennard-Jones model, employing parallel tempering Monte Carlo to cover the crystalline, amorphous, and liquid regions of configuration space. Disconnectivity graphs are used to visualize the potential energy landscape in the vicinity of a crystalline geometry and in an amorphous region of configuration space. The crystalline global minimum is separated from the bulk of the minima by a large potential energy gap, leading to broken ergodicity in conventional simulations. Our sampling reveals crystalline global minima that are lower in potential energy than some of the previous candidates. We present equilibrium thermodynamic properties based on parallel tempering simulations, including heat capacities and free energy profiles, which depend explicitly on the crystal structure. We also report equilibrium melting temperatures. [ABSTRACT FROM AUTHOR]

The thermodynamics and kinetics of a many-body system can be described in terms of a potential energy landscape in multidimensional configuration space. The partition function of such a landscape can be written in terms of a density of states, which can be computed using a variety of Monte Carlo techniques. In this paper, a new self-consistent Monte Carlo method for computing density of states is described that uses importance sampling and a multiplicative update factor to achieve rapid convergence. The technique is then applied to compute the equilibrium quench probability of the various inherent structures (minima) in the landscape. The quench probability depends on both the potential energy of the inherent structure and the volume of its corresponding basin in configuration space. Finally, the methodology is extended to the isothermal-isobaric ensemble in order to compute inherent structure quench probabilities in an enthalpy landscape. [ABSTRACT FROM AUTHOR]

This paper reports the first computational estimation of the comb polymers’ third virial coefficients. The number of the chains in the comb polymers range from 5 to 11. An algorithm that counts the contributing terms of the third virial coefficients in an accelerated manner is presented along with its efficiency dependence on the polymers’ size. In addition, the second virial coefficients are estimated for the comb polymers and compared to previously reported results. [ABSTRACT FROM AUTHOR]

Density functional theory as proposed by Rosenfeld [Phys. Rev. Lett. 63, 980 (1989)] is used to study hard sphere mixture exposed by cylindrically symmetric external field. Exploiting the symmetry of the system, explicit formulas for the weighted densities are derived. The resulting density profiles are compared with new grand canonical Monte Carlo simulations. The comparison reveals very good agreement between the predicted and simulated results even at high densities and very narrow pores. Finally, simple algorithms for computing complete elliptic functions of the first and second kinds that occur in the derived formulae are presented to make the paper self-contained. [ABSTRACT FROM AUTHOR]

Gillespie’s exact stochastic simulation algorithm (SSA) [J. Phys. Chem. 81, 2350 (1977)] has been widely used to simulate the stochastic dynamics of chemically reacting systems. In this algorithm, it is assumed that all reactions occur instantly. While this is true in many cases, it is also possible that some chemical reactions, such as gene transcription and translation in living cells, take certain time to finish after they are initiated. Thus, the product of such reactions will emerge after certain delays. Apparently, Gillespie’s SSA is not an exact algorithm for chemical reaction systems with delays. In this paper, the author develops an exact SSA for chemical reaction systems with delays, based upon the same fundamental premise of stochastic kinetics used by Gillespie in the development of his SSA. He then shows that an algorithm modified from Gillespie’s SSA by Barrio et al. [PLOS Comput. Biol. 2, 1017 (2006)] is also an exact SSA for chemical reaction systems with delays, but it needs to generate more random variables than the author’s algorithm. [ABSTRACT FROM AUTHOR]

In the present paper, the connection between surface order-disorder phase transitions and the percolating properties of the adsorbed phase has been studied. For this purpose, four lattice-gas models in the presence of repulsive interactions have been considered. Namely, monomers on honeycomb, square, and triangular lattices, and dimers (particles occupying two adjacent adsorption sites) on square substrates. By using Monte Carlo simulation and finite-size scaling analysis, we obtain the percolation threshold θc of the adlayer, which presents an interesting dependence with w/kBT (w, kB, and T being the lateral interaction energy, the Boltzmann constant, and the temperature, respectively). For each geometry and adsorbate size, a phase diagram separating a percolating and a nonpercolating region is determined. [ABSTRACT FROM AUTHOR]

The direct correlation function plays an important role in describing the effects of the structure of particle systems with respect to light diffraction, x-ray diffraction as well as transmission and transmission fluctuations of radiation through a dense suspension. In this paper, the direct correlation function for a monolayer of monodisperse hard spheres or disks is derived theoretically. Based on the approximation of Baus and Colot [Phys. Rev. A 36, 3912 (1987)] and the equation of state for a fluid of hard disks by Santos et al. [J. Chem. Phys. 103, 4622 (1995)], we propose a new direct correlation function, which compares well to the approximate analytical expressions and gives a good prediction of the structure factor in a wide range of monolayer density or suspension concentration. The resulting radial distribution function also agrees well with Monte Carlo computer simulation data. The corresponding contact values of the radial distribution function compare well with the results of analytic approximations, numerical solutions, and computer simulations. Our proposed direct correlation function is applied to the transmission fluctuation spectrometric study. Experimental results show good agreement with the theory. [ABSTRACT FROM AUTHOR]

This paper investigates effects of using monodisperse inverse analyses to extract particle-particle and particle-surface potentials from simulated interfacial colloidal fluids of polydisperse attractive particles. Effects of polydispersity are investigated as functions of particle concentration and attractive well depth and range for van der Waals and depletion potentials. Forward Monte Carlo simulations are used to generate particle distribution functions for polydisperse interfacial colloidal fluids from which inverted potentials are obtained using an inverse Ornstein-Zernike analysis and an inverse Monte Carlo simulation method. Attractive potentials are successfully recovered for monodisperse colloidal fluids, but polydispersity that is unaccounted for in inverse analyses produces (1) apparent softening of strong forces, (2) anomalous repulsive and attractive interactions, and (3) aphysical particle overlaps. This investigation provides insights into the role of polydispersity in altering the equilibrium structure and corresponding inverted potentials of attractive colloidal fluids near surfaces. These findings should assist the design and interpretation of optical microscopy experiments involving interfacial colloidal fluids similar to the simulated experiments reported here. [ABSTRACT FROM AUTHOR]

Kinetic Monte Carlo (KMC) simulations are carried out to directly study diffusion of benzene through thin (37–100 nm) NaX zeolite membranes under a gradient in chemical potential. Nonlinearities in adsorbate loading near the membrane boundaries are shown to arise from the difference in adsorbate density between the zeolite and adjacent fluid phase. Direct extraction of the transport diffusivity from gradient KMC simulations enables testing of the Darken approximation. This rigorous approach reveals limitations of the Darken approximation and, for the first time, the potentially complex nonunique functionality and multiplicity of the transport diffusivity for strongly interacting adsorbates. In the companion paper we explore these nonlinear interfacial effects in the context of permeation through both single-crystal and polycrystalline membranes. [ABSTRACT FROM AUTHOR]