Confined crystallization of cylindrical diblock copolymers studied by dynamic Monte Carlo simulations

We report dynamic Monte Carlo simulations of polymer crystallization confined in the cylindrical microdomains of diblock copolymers. The microdomains were prepared via spontaneous microphase separation from homogeneous melt, and the major component was then frozen in a vitreous amorphous state to make a hard confinement to the crystallization of the minor component. We found that during the isothermal crystallization at high temperatures, crystal orientations are dominantly perpendicular to the cylinder axis at the early stage of crystal nucleation and remain to the final state; while if the block junctions are broken before crystallization, crystal orientations are dominantly parallel at the early stage of crystal nucleation, and eventually other orientations take the place of parallel preferences. Analysis of bond orientations in the heterogeneous melts demonstrates the microscopic origin of oriented crystal nucleation.     

Melting behaviors of icosahedral metal clusters studied by Monte Carlo simulations

We present an atom‐resolved analysis method that traces physical quantities such as the root‐mean‐square bond length fluctuation and coordination number for individual atoms as functions of temperature or time. This method is applied to explain the temperature‐dependent behaviors of three types of Ni_N (N=12,13,14) clusters. The detailed studies for the three types of clusters reveal characteristics as follows: (a) as the temperature increases, all three types of clusters undergo two‐stage melting, irrespective of the existence of vacancy or adatom on the icosahedral surfaces, (b) the melting of icosahedral clusters with vacancy starts with vacancy hopping, which has not been observed for any type of small clusters (N<34), (c) the melting of the icosahedral clusters with adatom (N=14) is initiated by adatom hopping, followed by the site exchange between the adatom and surface atoms. © 2000 John Wiley & Sons, Inc. J Comput Chem 21: 380–387, 2000     

Artificial neural system modeling of Monte Carlo simulations of polymers

In this work, a neural network was used to learn features in potential energy surfaces and relate those features to conformational properties of a series of polymers. Specifically, we modeled Monte Carlo simulations of 20 polymers in which we calculated the characteristic ratio and the temperature coefficient of the characteristic ratio for each polymer. We first created 20 rotational potential energy surfaces using MNDO procedures and then used these energy surfaces to produce 10000 chains, each chain 100 bonds long. From these results we calculated the mean-square end-to-end distance, the characteristic ratio and its corresponding temperature coefficient. A neural network was then used to model the results of these Monte Carlo calculations. We found that artificial neural network simulations were highly accurate in predicting the outcome of the Monte Carlo calculations for polymers for which it was not trained. The overall average error for prediction of the characteristic ratio was 4,82%, and the overall average error for prediction of the temperature coefficient was 0,89%.     

Three-dimensional dynamic Monte Carlo simulations of elastic actin-like ratchets

We present three-dimensional dynamic Monte Carlo simulations of the growth of a semiflexible fiber against a fluctuating obstacle. The natural reference for our numerical study are the elastic and Brownian ratchet models previously analyzed semianalytically. We find that the decay of the velocity versus applied load is exponential to a good degree of accuracy, provided we include in the load the drag force felt by the moving obstacle. If the fiber and obstacle only interact via excluded volume, there are small corrections to the Brownian ratchet predictions which suggest that tip fluctuations play a minor role. If on the other hand fiber and obstacle interact via a soft potential, the corrections are much larger when the obstacle diffuses slowly. This means that microscopic assumptions can profoundly affect the dynamics. We also identify and characterize a novel "pushing catastrophe"--which is distinct from the usual fiber buckling--in which the growth of the fiber decouples from the obstacle movement. The time distribution of catastrophes can be explained via an approximate analytical treatment, and our numerics suggest that the time taken to lose propulsive force is largely dependent on the fiber incidence angle. Our results are a first step in realizing numerical polymer models for the motion of sets or networks of semiflexible fibers close to a fluctuating membrane or obstacle.     

Dynamics of polyethylene melts studied by Monte Carlo simulations on a high coordination lattice

A detailed comparison is made between the experiment, prior simulations by other groups, and our simulation based on a newly designed dynamic Monte Carlo algorithm, on the dynamics of polyethylene (PE) melts. The new algorithm, namely, noncross random two-bead move has been developed on a high coordination lattice (the 2nnd lattice) for studying the dynamics of realistic polymers. The chain length (molecular weight) in our simulation ranges from C40 (562 Da) to C324 (4538 Da). The effects of finite chain length have been confirmed and significant non-Gaussian statistics evidently results in nonstandard static and dynamic properties of short PE chains. The diffusion coefficients scale with molecular weight (M) to the −1.7 power for short chains and −2.2 for longer chains, which coincides very well with experimental results. No pure Rouse scaling in diffusion has been observed. The transitional molecular weight to the entanglement regime is around 1500 Da. The detailed mean square displacements of middle bead (g1) are presented for several chain lengths. The reptation-like slowdown can be clearly observed only above M ∼ 2400 Da. The slope 0.25 predicted by the theory for the intermediate regime is missing; instead a slope close to 0.4 appears, indicating that additional relaxation mechanism exists in this transitional region. The relaxation times extracted by fitting the autocorrelation function of end-to-end vectors with reptation model scale with M to 2.5 for long chains, which seemingly conflicts with the scaling of diffusion. © 2006 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys 44: 2556–2571, 2006     

Macroion solutions in the cell model studied by field theory and Monte Carlo simulations

Aqueous solutions of charged spherical macroions with variable dielectric permittivity and their associated counterions are examined within the cell model using a field theory and Monte Carlo simulations. The field theory is based on separation of fields into short- and long-wavelength terms, which are subjected to different statistical-mechanical treatments. The simulations were performed by using a new, accurate, and fast algorithm for numerical evaluation of the electrostatic polarization interaction. The field theory provides counterion distributions outside a macroion in good agreement with the simulation results over the full range from weak to strong electrostatic coupling. A low-dielectric macroion leads to a displacement of the counterions away from the macroion.     

The theta-temperature depression caused by topological effect in ring polymers studied by Monte Carlo simulation

We studied equilibrium conformations of linear and ring polymers in dilute solutions over the wide range of segment number N of up to 2048 with Monte Carlo simulation, and evaluated N dependence of the radii of gyration, R(g), of chains. The polymer molecules treated in this study are assumed to be composed of beads and bonds, and they are put in a three-dimensional face-centered cubic (FCC) lattice. The values of Flory's critical exponent, ν, for linear and ring polymers were estimated from the N dependence of R(g), and the temperatures at which ν reach 1/2 were obtained. Here we define those as Θ-temperatures in this report. The simulation result shows that the Θ-temperature for ring polymers is evidently lower than that of the linear polymers, and the origin of the Θ-temperature depression is discussed. Since R(g) of a ring polymer is smaller than that for a linear polymer at the same N and temperature, the segment density for a ring polymer is increased by the topological effect and the repulsive force between segments of a ring polymer at the Θ-temperature for a linear polymer is stronger. Thus, the origin of the Θ-temperature depression for ring polymers is the repulsive force emphasized by the topological effect of rings.     

Rheology of polymer brush under oscillatory shear flow studied by nonequilibrium Monte Carlo simulation

The rheological behaviors of polymer brush under oscillatory shear flow were investigated by nonequilibrium Monte Carlo simulation. The grafted chain under oscillatory shear flow exhibited a waggling behavior like a flower, and the segments were found to have different oscillatory phases along the chain contour. Stress tensor was further obtained based on the statistics of sampled configuration distribution functions. The simulation reproduced the abrupt increase of the first normal stress difference N(1) with the flow velocity over a critical value, as observed in the experiment of Klein et al. [Nature (London) 352, 143 (1991)]. However, our simulation did not reproduce the brush thickening with shear velocity increased, which was suggested to be responsible for the abrupt increase of N(1) in the above-mentioned paper. This simulation demonstrates that the increase of normal stress might be an inherent behavior of polymer brush due to chain deformation under flow.     

Oxygen island formation on Pt(111) studied by dynamic Monte Carlo simulation

The formation of oxygen islands on the Pt(111) surface has been studied as a function of temperature by low energy electron diffraction (LEED) experiments and dynamic Monte Carlo (DMC) simulations. By raising the temperature, the (2 x 2) LEED spot intensity increases gradually and decays after a peak at around 255 K (T(p)) with full width of half maximum of 160 K. This behavior is interpreted by DMC simulations with the kinematical LEED analysis. In the DMC simulation, an oxygen atom hops to the neighboring site via the activation barrier of the saddle point. The potential energies at initial, saddle, and final points are changed at each hopping event depending on the surrounding oxygen atoms. By comparing the observed T(p) with the simulated one, the interaction energy E of oxygen atoms on Pt(111) was determined to be 25+/-3 meV at 2a(0). The DMC simulations visualize how the oxygen islands are formed and collapse on Pt(111) with increase of the temperature and well reproduce the surface configurations observed by scanning tunneling microscopy.     

Surface tension of associating fluids by Monte Carlo simulations

Canonical Monte Carlo (NVT-MC) simulations were performed to obtain surface tension and coexistence densities at the liquid-vapor interface of one-site associating Lennard-Jones and hard-core Yukawa fluids, as functions of association strength and temperature. The method to obtain the components of the pressure tensor from NVT-MC simulations was validated by comparing the equation of state of the associative hard sphere system with that coming from isothermal-isobaric Monte Carlo simulations. Surface tension of the associative Lennard-Jones fluid determined from NVT-MC is compared with previously reported results obtained by molecular dynamics simulations of a pseudomixture model of monomers and dimers. A good agreement was found between both methods. Values of surface tension of associative hard-core Yukawa fluids are presented here for the first time.     

Dynamics of polypropylene chains in their binary blends of different stereochemical sequences studied by Monte Carlo simulations

The conformational and dynamic properties of polypropylene （PP） for both pure melts and blends with different chain tacticity were investigated by Monte Carlo simulation of isotactic （iPP）, atactic （aPP） and syndiotactic （sPP） polypropylenes. The simulation of coarse-grained PP models was performed on a high coordination lattice incorporating short- and long-range intramolecular interactions from the rotational isomeric state （RIS） model and Lennard-Jones （LJ） potential function of propane pairs, respectively. The dynamics of chains in binary PP/PP mixture were investigated with the composition of C150H302 with different chain taciticity. The diffusion rates of PP with different stereochemistry are generally in the order as： iPP 〉 aPP 〉〉 sPP. For PP/PP blends with 50：50 wt% binary mixtures, immiscibility was observed when sPP was introduced into the mixtures. The diffusion rate of iPP and aPP became slower after mixing, while sPP diffuses significantly faster in the binary mixtures. The mobility of PP chains depends on both intramolecular （molecular size and chain stiffness） and intermolecular （chain packing） interactions. The effect of intramolecular contribution is greater than that of intermolecular contribution for iPP and aPP chains in binary mixtures. For sPP chain, intermolecular interaction has greater influence on the dynamics than intramolecular contribution.     

Monte Carlo simulations of the exchange kinetics of polymers adsorbed on a solid surface

The exchange kinetics of polymers adsorbing on a solid surface is extensively studied by dynamic Monte Carlo simulations. A model employed simulates a semidilute polymer solution placed in contact with a solid surface that attracts polymer segments by the adsorption interaction (χ_s). The exchange process of polymer chains, between the solution and the adsorbed polymer layer, is examined under various conditions. The exchange kinetics shows two characteristic regimes with increasing chain length. One is the diffusion‐controlled regime found with a small χ_s , and the other the detachment‐controlled regime with a large χ_s . These two regimes are well described by a kinetic theory. Various dynamic quantities show that the diffusion‐controlled regime is not due to sluggish dynamics near the surface, but rather to bulk diffusion of chains. The diffusion‐controlled regime found in this study is considered to appear at the high temperature limit.     

Monte Carlo simulations of star‐branched polymers in a network of obstacles

A simple model of branched polymers in space confined between two parallel plates is developed. Star‐branched polymer molecules are built on a simple cubic lattice with excluded volume and no attractive interactions. A single star molecule is immersed in a network of irregularly dispersed linear rod‐like obstacles. The classical Monte Carlo Metropolis sampling algorithm is employed in the simulation. The aim of this study is to determine the effects of changes in dynamic properties of the star‐branched polymer as functions of the length of the molecule and the concentration of obstacles. Also the mechanism of motion of the polymer is discussed.     

Parallel Markov chain Monte Carlo simulations

With strict detailed balance, parallel Monte Carlo simulation through domain decomposition cannot be validated with conventional Markov chain theory, which describes an intrinsically serial stochastic process. In this work, the parallel version of Markov chain theory and its role in accelerating Monte Carlo simulations via cluster computing is explored. It is shown that sequential updating is the key to improving efficiency in parallel simulations through domain decomposition. A parallel scheme is proposed to reduce interprocessor communication or synchronization, which slows down parallel simulation with increasing number of processors. Parallel simulation results for the two-dimensional lattice gas model show substantial reduction of simulation time for systems of moderate and large size.     

Configuration biased Monte Carlo and Brownian dynamics simulations of semiflexible polymers in extensional flows

Configuration Biased Monte Carlo (CBMC) and Non-Equilibrium Brownian Dynamics (NEBD) simulations are used to understand the dynamics of semi-flexible macromolecules undergoing extensional flow. The mathematical model utilizes a discretized version of the Kratky-Porod wormlike (or persistent) chain as the building block, and using kinetic theory, generalized to include flow. In steady, potential flows, the solution of the Fokker-Planck equation exists and is used in the generation of trial and acceptance moves in the CBMC scheme. For the NEBD, the Fokker-Planck equation is converted to a Stochastic Differential Equation (SDE) from which the simulation algorithm is obtained. Various conformational quantities are monitored, under both steady-state and transient conditions, with the primary independent variable being the flexibility parameter β, the bending constant of the chain. It is found that the model is able to describe qualitatively many of the experimentally observed effects in such systems. In particular, we find that there is a direct link between the molecular flexibility and its birefringence response in an elongational flow field. We are able to draw conclusions by considering the behavior of molecular-conformational quantities such as the radius of gyration and the moment of inertia.     

Predicting helical hairpins from sequences by Monte Carlo simulations

The key problem in polypeptide‐structure prediction is with regard to thermodynamics. Two factors limit prediction in ab initio computer simulations. First, the thermodynamically dominant conformations must be found from an extremely large number of possible conformations. Second, these low‐energy forms must deviate little from the experimental structures. Here, we report on the application of the diffusion‐controlled Monte Carlo approach to predict four α‐helical hairpins with 34–38 residues by global optimization, using an energy optimized on other supersecondary structures. A total of seven simulations is carried out for each protein starting from fully extended conformations. Three proteins are correctly folded (within 3.0 Å rms from the experimental structures), but the fourth protein cannot distinguish between several equienergetic conformations. Possible improvement of the energy model is suggested. © 2000 John Wiley & Sons, Inc. J Comput Chem 21: 582–589, 2000     

Adsorption of monovalent and divalent cations on planar water-silica interfaces studied by optical reflectivity and Monte Carlo simulations

Adsorption on planar silica substrates of various monovalent and divalent cations from aqueous solution is studied by optical reflectivity. The adsorbed amount is extracted by means of a thin slab model. The experimental data are compared with grand canonical Monte Carlo titration simulations at the primitive model level. The surface excess of charge due to adsorbed cations is found to increase with pH and salt concentration as a result of the progressive dissociation of silanol groups. The simulations predict, in agreement with experiments, that the surface excess of charge from divalent ions is much larger than from monovalent ions. Ion-ion correlations explain quantitatively the enhancement of surface ionization by multivalent cations. On the other hand, the combination of experimental and simulation results strongly suggests the existence of a second ionizable site in the acidic region. Variation of the distance of closest approach between the ions and surface sites captures ion specificity of water-silica interfaces in an approximate fashion.     

Dynamic Monte Carlo simulations of competition in crystallization of mixed polymers grafted on a substrate

Nowadays, preparation of poly(lactide) (PLA) with high content of stereocomplex crystallites (SCs) is receiving more and more attentions. The stereocomplex formation between enantiomeric poly(l ‐lactide) and poly(d ‐lactide) can efficiently improve the corresponding mechanical properties and thermal stability. In the current work, using dynamic Monte Carlo simulations, the microscopic mechanism of SC formation in grafted polymers was investigated. The increase in grafting density can lead to the enhancement of SC formation. On one hand, the miscibility between the chains of different types can be improved due to the grafting. On the other hand, the increase in grafting density can result in the higher degree of chain extension and the change in crystal nucleation and growth modes. The changes facilitate the stereocomplex formation. These findings not only provide an effective way to prepare PLAs with high content of SCs, but also reveal the underlying mechanisms controlling the SC formation. © 2018 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2019 , 57, 89–97     

Monte Carlo simulations of low background detectors

An implementation of the Electron Gamma Shower 4 code (EGS4) has been developed to allow convenient simulation of typical gamma ray measurement systems. Coincidence gamma rays, beta spectra, and angular correlations have been added to adequately simulate a complete nuclear decay and provide corrections to experimentally determined detector efficiencies. This code has been used to strip certain low-background spectra for the purpose of extremely low-level assay. Monte Carlo calculations of this sort can be extremely successful since low background detectors are usually free of significant contributions from poorly localized radiation sources, such as cosmic muons, secondary cosmic neutrons, and radioactive construction or shielding materials. Previously, validation of this code has been obtained from a series of comparisons between measurements and blind calculations. An example of the application of this code to an exceedingly low background spectrum stripping will be presented.Pacific Northwest Laboratory is operated by Battelle Memorial Institute for the US Department of Energy under Contract DE-AC06-76RLO 1830.