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Using Monte Carlo computer simulations, we investigate the kinetics of phase separation in the two-dimensional conserved Ising model with power-law decaying long-range interactions, the prototypical model for many long-range interacting systems. A long-standing analytical prediction for the characteristic length is shown to be applicable. In the simulation, we relied on our novel algorithm which provides a massive speedup for long-range interacting systems.

Porous solids with channel sizes that are not much above the size of small hydrocarbons can yield extremely large adsorption selectivity. Our Grand Canonical Monte-Carlo simulations indicate exceptionally high selectivity for the separation of methane, ethane and propane from natural gas. At 250 K the C

We study the nonequilibrium kinetics during the coil-globule transition of a flexible polymer chain with active beads after a quench from good to poor solvent condition using molecular dynamics simulation. Activity for each bead is introduced via the well-known Vicsek-like alignment rule due to which the velocity of a bead tries to align towards the average direction of its neighbors. We investigate the role of quenching temperature with varying activity during collapse of this polymer. We find that although for lower activities the kinetics remains qualitatively similar for different temperatures, for higher activity noticeable differences can be identified.

The separation of nitrogen dioxide (NO2) from the gas mixture with nitrogen (N2) by selective adsorption and diffusion in three Zeolitic Imidazolate Frameworks (ZIFs) is examined by Gibbs Ensemble Monte Carlo (GEMC) and Molecular Dynamics (MD) computer simulations at 373 K, which is a temperature that can be found in the exhaust gases of combustion engines and furnaces. This temperature ensures that the chemical equilibrium reaction between NO2 and N2O4 can be neglected since at this temperature almost only NO2 exists. At 373 K, the membrane selectivity of NO2 over N2 is predicted to be about 4.2 (ZIF-90), 5.2 (ZIF-8), and 10.6 (ZIF-78). In addition, it is shown that N2O4 can be neither adsorbed nor diffuses inside these ZIF materials, which makes these ZIFs a promising materials for separation by membranes. Due to molecular sieving, only N2 and NO2 can pass the ZIF membranes.

Population annealing is a recent addition to the arsenal of the practitioner in computer simulations in statistical physics and beyond that is found to deal well with systems with complex free-energy landscapes. Above all else, it promises to deliver unrivaled parallel scaling qualities, being suitable for parallel machines of the biggest calibre. Here we study population annealing using as the main example the two-dimensional Ising model which allows for particularly clean comparisons due to the available exact results and the wealth of published simulational studies employing other approaches. We analyze in depth the accuracy and precision of the method, highlighting its relation to older techniques such as simulated annealing and thermodynamic integration. We introduce intrinsic approaches for the analysis of statistical and systematic errors, and provide a detailed picture of the dependence of such errors on the simulation parameters. The results are benchmarked against canonical and parallel tempering simulations., Comment: 26 pages, 23 figures

Via molecular dynamics simulation with Langevin thermostat we study the structure and dynamics of a flexible bead-spring active polymer model after a quench from good to poor solvent conditions. The self propulsion is introduced via a Vicsek-like alignment activity rule which works on each individual monomer in addition to the standard attractive and repulsive interactions among the monomeric beads. We observe that the final conformations are in the globular phase for the passive as well as for all the active cases. By calculating the bond length distribution, radial distribution function, etc., we show that the kinetics and also the microscopic details of these \textit{pseudo equilibrium} globular conformations are not the same in all the cases. Moreover, the center-of-mass of the polymer shows a more directed trajectory during its motion and the behavior of the mean-squared-displacement gradually changes from a super-diffusive to ballistic under the influence of the active force in contrast to the diffusive behavior in the passive case.

A high selectivity of NOx over N2 (simulating air) is found in silico when studying the adsorption of the ternary mixture N2O4/NO2/N2 on the metal–organic framework MIL-127(Fe) by molecular simulations under consideration of the recombination reaction N2O4 ↔ 2NO2. The number of N atoms in nitrogen oxides NOx and that in N2 is used to define a selectivity of the combined adsorption and chemical recombination that can reach values of about 1000.

Abstract We describe how metastable states of Ising spin glasses can be counted by means of Monte Carlo computer simulations. The method is applied to systems defined on hypercubic lattices in one to six dimensions with up to about 103 spins. It is shown that the number of metastable states obtained for different disorder realizations satisfies a log-normal distribution. We investigate the distribution of energies of metastable states by means of moments and cumulants. Graphical abstract

Population annealing is a promising recent approach for Monte Carlo simulations in statistical physics, in particular for the simulation of systems with complex free-energy landscapes. It is a hybrid method, combining importance sampling through Markov chains with elements of sequential Monte Carlo in the form of population control. While it appears to provide algorithmic capabilities for the simulation of such systems that are roughly comparable to those of more established approaches such as parallel tempering, it is intrinsically much more suitable for massively parallel computing. Here, we tap into this structural advantage and present a highly optimized implementation of the population annealing algorithm on GPUs that promises speed-ups of several orders of magnitude as compared to a serial implementation on CPUs. While the sample code is for simulations of the 2D ferromagnetic Ising model, it should be easily adapted for simulations of other spin models, including disordered systems. Our code includes implementations of some advanced algorithmic features that have only recently been suggested, namely the automatic adaptation of temperature steps and a multi-histogram analysis of the data at different temperatures., 12 pages, 3 figures and 5 tables, code at https://github.com/LevBarash/PAising

A silicious material containing massive array of spherical nanocages connected to each other by small micropores was used to study ice nucleation in confined water under conditions of well-defined pore geometry. By purposefully selecting small size of the interconnecting pores below 2 nm, ice nucleation and growth were limited to occur only within the nanocages. By exploitation of nuclear magnetic resonance, ice nucleation rates at different temperatures were accurately measured. These rates were obtained to be substantially higher than those typically observed for micrometer-sized water droplets in air. In addition, the occurrence of correlations between ice nucleation in one nanocage with the phase state in the adjacent cages were observed. These results have important implication for a deeper understanding of ice nucleation, especially in confined geometries.

Over the last two decades generalized ensemble Monte Carlo computer simulation studies employing multicanonical, Wang–Landau, or replica-exchange methods have proven to be a strong numerical tool for investigations of the statistical physics of polymer chains. After a discussion of the theoretical background of these approaches, their power will be demonstrated in two applications to coarse-grained models of semiflexible polymers, which show a rich variety of structural motifs such as hairpins, knots and twisted bundles.

Adsorption and diffusion of the gas mixture H2/CH4 in the metal–organic framework (MOF) of structure type zeolitic imidazolate framework-90 (ZIF-90) are revisited. While the adsorption can successfully be examined in Gibbs ensemble Monte Carlo (GEMC) simulations using the common approximation of a rigid lattice, the dynamics of methane in ZIF-90 is remarkably influenced by the lattice flexibility. Molecular dynamics (MD) simulations not only show a strong influence of the lattice flexibility on the diffusion of methane but even find a slight structural phase transition of the lattice. This structural change appeared at higher temperatures and was not caused by the content of guest molecules like in most former discoveries of gate opening. For prediction of mixed gas ZIF-90 membrane selectivity, the adsorption and diffusion results show that the high CH4 adsorption selectivity is overcompensated by the high H2 mobility. The comparison of our results for the H2/CH4 membrane selectivity with experimental fin...

We analyze the structural behavior of isolated semiflexible polymers grafted to an impenetrable surface. Employing a parallel multicanonical algorithm, we find a rich phase behavior for both purely entropic and attractive surface–polymer interactions. The corresponding conformations range from very compact ones, to folded bundles, to adsorbed and desorbed weakly bent rods. The case of a polymer grafted to a flat, noninteracting surface differs only marginally from the case of a completely free and isolated polymer. Introducing surface attraction, we find that below the adsorption transition temperature stiffer polymers are completely adsorbed and confined to an effectively two-dimensional conformation space. This ultimately holds true over the full range of semiflexibility for increasing surface attraction, in accordance with recent experimental findings.

Poly(3-hexylthiophene) (P3HT) has been in the focus of recent studies due to its promising future use in organic photovoltaics, electronics and photonics. Recent publications investigate the melt behavior of P3HT, its interaction with other molecules, mainly various fullerene derivates, and isolated chains interacting with substrates. In this work we lay the focus on the single-chain properties of P3HT in vacuum. We compare structural properties obtained from simulations using two coarse-grained models and an atomistic model of the polymer for various chain lengths and temperatures.

We investigate the binding transition of two flexible polymers grafted to a steric surface with closeby end points. While free polymers show a discontinuous transition, grafting to a steric flat surface leads to a continuous binding transition. This is supported by results from Metropolis and parallel multicanonical simulations. A combination of canonical and microcanonical analyses reveals that the change in transition order can be understood in terms of the reduced translational entropy of the unbound high-temperature phase upon grafting., 10 pages, 6 figures, submitted to Eur. Phys. J Spec. Topics

Simulations of systems with quenched disorder are extremely demanding, suffering from the combined effect of slow relaxation and the need of performing the disorder average. As a consequence, new algorithms, improved implementations, and alternative and even purpose-built hardware are often instrumental for conducting meaningful studies of such systems. The ensuing demands regarding hardware availability and code complexity are substantial and sometimes prohibitive. We demonstrate how with a moderate coding effort leaving the overall structure of the simulation code unaltered as compared to a CPU implementation, very significant speed-ups can be achieved from a parallel code on GPU by mainly exploiting the trivial parallelism of the disorder samples and the near-trivial parallelism of the parallel tempering replicas. A combination of this massively parallel implementation with a careful choice of the temperature protocol for parallel tempering as well as efficient cluster updates allows us to equilibrate comparatively large systems with moderate computational resources., Comment: accepted for publication in EPJB, Topical issue - Recent advances in the theory of disordered systems

We study properties of Markov chain Monte Carlo simulations of classical spin models with local updates. We derive analytic expressions for the mean value of the acceptance rate of single-spin-flip algorithms for the one-dimensional Ising model. We find that for the Metropolis algorithm the average acceptance rate is a linear function of energy. We further provide numerical results for the energy dependence of the average acceptance rate for the 3- and 4-state Potts model, and the XY model in one and two spatial dimensions. In all cases, the acceptance rate is an almost linear function of the energy in the critical region. The variance of the acceptance rate is studied as a function of the specific heat. While the specific heat develops a singularity in the vicinity of a phase transition, the variance of the acceptance rate stays finite., Comment: 8 pages, 5 figures; published version

An anisotropic limit of the 3d plaquette Ising model, in which the plaquette couplings in one direction were set to zero, was solved for free boundary conditions by Suzuki (Phys. Rev. Lett. 28 (1972) 507), who later dubbed it the fuki-nuke, or "no-ceiling", model. Defining new spin variables as the product of nearest-neighbour spins transforms the Hamiltonian into that of a stack of (standard) 2d Ising models and reveals the planar nature of the magnetic order, which is also present in the fully isotropic 3d plaquette model. More recently, the solution of the fuki-nuke model was discussed for periodic boundary conditions, which require a different approach to defining the product spin transformation, by Castelnovo et al. (Phys. Rev. B 81 (2010) 184303). We clarify the exact relation between partition functions with free and periodic boundary conditions expressed in terms of original and product spin variables for the 2d plaquette and 3d fuki-nuke models, noting that the differences are already present in the 1d Ising model. In addition, we solve the 2d plaquette Ising model with helical boundary conditions. The various exactly solved examples illustrate how correlations can be induced in finite systems as a consequence of the choice of boundary conditions., v5 - The title is changed to better reflect the contents and the exposition is streamlined. Version accepted for publication

Using state of the art Monte Carlo simulations of a bead-spring model we investigate both the equilibrium and the nonequilibrium behavior of the homopolymer collapse. The equilibrium properties obtained via multicanonical sampling recover the well-known finite-size scaling behavior of collapse for our model polymer. For the nonequilibrium dynamics we study the collapse by quenching the homopolymer from an expanded coiled state into the globular phase. The sequence of events observed during the collapse is independent of the quench depth. In particular, we focus on finding out universal scaling behaviors related to the growth or coarsening of clusters of monomers, by drawing phenomenological analogies with ordering kinetics. We distinguish the cluster coarsening stage from the initial stage of primary cluster formation. By successful application of a nonequilibrium finite-size scaling analysis we show that at all quench temperatures, during the coarsening stage, the cluster growth is roughly linear and can be characterised by a universal finite-size scaling function. In addition, we provide evidence of aging by constructing a suitable autocorrelation function and its corresponding dynamical power-law scaling with respect to the growing cluster sizes. The predicted theoretical bound for the exponent governing such scaling is strictly obeyed by the numerical data irrespective of the quench temperature. The results and methods presented here in general should find application in similar phenomena such as the collapse of a protein molecule preceding its folding.

Diffusion and adsorption of CO2/N2 mixtures in the zeolitic imidazolate framework ZIF-8 are investigated by molecular dynamics (MD) and Gibbs ensemble Monte Carlo (GEMC) simulations. Structural changes called “gate opening” could be found for the adsorbed single-component gases and for the mixture. The gate opening appears for the mixture at a total number of guest molecules per cavity between that for the pure CO2 and that for the pure N2 but closer to that of N2 which is lower. Due to the stronger dependence of CO2 adsorption upon the temperature in comparison with N2, the adsorption selectivity is predicted to be higher at lower temperatures, which is in accordance with experimental findings.

Since the simulation of the CO2 adsorption in ZIF-8 for the ZIF-8 HP (high-pressure phase) and ZIF-8 AP (conventional phase) structures – as defined in [1] – gave similar results [2] , Molecular Dynamics (MD) has been applied to decide which of these two structures exists at which CO2 pressure. MD simulations with flexible lattice show that a transition from the ZIF-8 AP to the ZIF-8 HP structure takes place at extremely high CO2 pressure, i.e. at high loading.

We show how a Monte Carlo method for generating self-avoiding walks on lattice geometries which employs a binary-tree data-structure can be adapted for hard-sphere polymers with continuous degrees of freedom. Data suggests that the time per Monte Carlo move scales logarithmically with polymer size. Next we generalize the method to Lennard-Jones polymers with untruncated monomer–monomer interaction. To this end we propose a variant of the Metropolis algorithm and demonstrate that in combination with the tree data-structure logarithmic scaling can be preserved. We further show how the replica-exchange method can be adapted for the same purpose.

The current understanding of aging phenomena is mainly confined to the study of systems with short-ranged interactions. Little is known about the aging of long-ranged systems. Here, the aging in the phase-ordering kinetics of the two-dimensional Ising model with power-law long-range interactions is studied via Monte Carlo simulations. The dynamical scaling of the two-time spin-spin autocorrelator is well described by simple aging for all interaction ranges studied. The autocorrelation exponents are consistent with $\ensuremath{\lambda}=1.25$ in the effectively short-range regime, while for stronger long-range interactions the data are consistent with $\ensuremath{\lambda}=d/2=1$. For very long-ranged interactions, strong finite-size effects are observed. We discuss whether such finite-size effects could be misinterpreted phenomenologically as subaging.

Population annealing is a novel Monte Carlo algorithm designed for simulations of systems of statistical mechanics with rugged free-energy landscapes. We discuss a realization of the algorithm for the use on a hybrid computing architecture combining CPUs and GPGPUs. The particular advantage of this approach is that it is fully scalable up to many thousands of threads. We report on applications of the developed realization to several interesting problems, in particular the Ising and Potts models, and review applications of population annealing to further systems.

From Kawasaki-exchange Monte Carlo simulations of the $q$-state Potts model, we present results for the kinetics of phase separation in multicomponent mixtures, for $q\ensuremath{\le}10$, in space dimension $d=2$. A particular focus has been on the quantification of finite-size scaling functions for various values of $q$ and quench depths. For a range of final quench temperatures, our analyses, via finite-size scaling and other state-of-the-art methods, show that the growth follows the Lifshitz-Slyozov behavior, expected for a diffusive mechanism, irrespective of the number of components. We show that the growth for different $q$ values and quench temperatures, in finite systems, can be described by a universal scaling function with a nonuniversal metric factor, originating from the differences in the amplitudes. We also demonstrate the morphological and kinetic equivalence between a $q$-component equal proportion mixture and an off-critical binary mixture, in the framework of the Ising model, with relative concentration of the minority component in the latter being ${x}_{c}=1/q$.

We investigate the structural phases of single poly(3-hexylthiophene) (P3HT) polymers that are adsorbed on a two-dimensional substrate with a striped pattern. We use a coarse-grained representation of the polymer and sophisticated Monte Carlo techniques such as a parallelized replica exchange scheme and local as well as non-local updates to the polymer's configuration. From peaks in the canonically derived observables, it is possible to obtain structural phase diagrams for varying substrate parameters. We find that the shape of the stripe pattern has a substantial effect on the obtained configurations of the polymer and can be tailored to promote either more stretched out or more compact configurations. In the compact phases, we observe different structural motifs, such as hairpins, double-hairpins, and interlocking "zipper" states.

Using high-precision Monte Carlo simulations and finite-size scaling we study the effect of quenched disorder in the exchange couplings on the Blume-Capel model on the square lattice. The first-order transition for large crystal-field coupling is softened to become continuous, with a divergent correlation length. An analysis of the scaling of the correlation length as well as the susceptibility and specific heat reveals that it belongs to the universality class of the Ising model with additional logarithmic corrections observed for the Ising model itself if coupled to weak disorder. While the leading scaling behavior in the disordered system is therefore identical between the second-order and first-order segments of the phase diagram of the pure model, the finite-size scaling in the ex-first-order regime is affected by strong transient effects with a crossover length scale $L^{\ast} \approx 32$ for the chosen parameters., 6 pages, 4 figures, version to be published in Phys. Rev. E as a Rapid Communication

To provide a novel tool for the investigation of the energy landscape of the Edwards-Anderson spin-glass model we introduce an algorithm that allows an efficient execution of a greedy optimization based on data from a previously performed optimization for a similar configuration. As an application we show how the technique can be used to perform higher-order greedy optimizations and simulated annealing searches with improved performance., Comment: 9 pages, 10 figures

Adsorption and diffusion of hydrogen in the metal organic framework ZIF-11 will be discussed in this paper using molecular dynamics (MD) and Gibbs Monte Carlo (GMC) computer simulations. Reliable force fields, needed for these simulations, are only partially available. Adsorption simulations, in comparison with experiments, have been used to fit some missing interaction parameters. The lattice flexibility turns out to have relatively small influence on adsorption. The obtained parameter set has been used to investigate the structure of ZIF-11 and the self-diffusion of hydrogen within the flexible framework.

The conformational behavior of a coarse-grained finite polymer chain near an attractive spherical surface was investigated by means of multicanonical Monte Carlo computer simulations. In a detailed analysis of canonical equilibrium data over a wide range of sphere radius and temperature, we have constructed entire phase diagrams both for non-grafted and end-grafted polymers. For the identification of the conformational phases, we have calculated several energetic and structural observables such as gyration tensor based shape parameters and their fluctuations by canonical statistical analysis. Despite the simplicity of our model, it qualitatively represents in the considered parameter range real systems that are studied in experiments. The work dicussed here could have experimental implications from protein-ligand interactions to designing nano smart materials.

We study long-range power-law correlated disorder on square and cubic lattices. In particular, we present high-precision results for the percolation thresholds and the fractal dimension of the largest clusters as function of the correlation strength. The correlations are generated using a discrete version of the Fourier filtering method. We consider two different metrics to set the length scales over which the correlations decay, showing that the percolation thresholds are highly sensitive to such system details. By contrast, we verify that the fractal dimension $d_{\rm f}$ is a universal quantity and unaffected by the choice of metric. We also show that for weak correlations, its value coincides with that for the uncorrelated system. In two dimensions we observe a clear increase of the fractal dimension with increasing correlation strength, approaching $d_{\rm f}\rightarrow 2$. The onset of this change does not seem to be determined by the extended Harris criterion., 12 pages, 8 figures

The three-dimensional purely plaquette gonihedric Ising model and its dual are investigated to resolve inconsistencies in the literature for the values of the inverse transition temperature of the very strong temperature-driven first-order phase transition that is apparent in the system. Multicanonical simulations of this model allow us to measure system configurations that are suppressed by more than 60 orders of magnitude compared to probable states. With the resulting high-precision data, we find excellent agreement with our recently proposed nonstandard finite-size scaling laws for models with a macroscopic degeneracy of the low-temperature phase by challenging the prefactors numerically. We find an overall consistent inverse transition temperature of β ∞ = 0.551334(8) from the simulations of the original model both with periodic and fixed boundary conditions, and the dual model with periodic boundary conditions. For the original model with periodic boundary conditions, we obtain the first reliable estimate of the interface tension σ = 0.12037(18), using the statistics of suppressed configurations. © 2014 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license

In the field of nanoporous materials, guest-induced structural changes in metal–organic frameworks (MOFs) attracted great attention over the last years. One example concerns a gate-opening effect in MOF ZIF-8 which was found to occur upon sorption of N2. To mirror these structural changes in molecular simulations, suitable force fields for the proper description of framework flexibility are required. We demonstrate that our previously published force field is able to reproduce these structural changes in classical MD simulations. In particular, with our parameter set the diameter of the windows connecting adjacent cavities is found to match the X-ray values almost perfectly. We focus on investigating the impact of the structural changes on the mobility of N2 molecules in ZIF-8 framework and compare the results with those of another parameter set, which was published recently by Zhang and coworkers. The size of the windows increases notably, when the critical “gate-opening” loading is surpassed. Most surprisingly, this pronounced increase does not result in a speed-up of the N2 self-diffusivity. It appears, that a complex interplay of host-host and host-guest interactions increases the mutual hindrance of the N2 molecules and counter balance the acceleration of the mobility due to the larger window size.

In this work we investigate the effect of bending stiffness on a homopolymer inside a spherical confinement. In particular we are interested in the collapse transition and its dependence on the size of the confinement and the stiffness of the polymer. Using an advanced multicanonical Monte Carlo algorithm, we sample the phase space of a coarse-grained homopolymer model. We find that the confinement leads to a shift of the collapse transition temperature with a stiffness-dependent direction: flexible polymers become more unstable for a smaller confinement in contrast to semi-flexible polymers, where the transition temperature increases with decreasing size of the confinement.

The multicanonical method has been proven powerful for statistical investigations of lattice and off-lattice systems throughout the last two decades. We discuss an intuitive but very efficient parallel implementation of this algorithm and analyze its scaling properties for discrete energy systems, namely the Ising model and the 8-state Potts model. The parallelization relies on independent equilibrium simulations in each iteration with identical weights, merging their statistics in order to obtain estimates for the successive weights. With good care, this allows faster investigations of large systems, because it distributes the time-consuming weight-iteration procedure and allows parallel production runs. We show that the parallel implementation scales very well for the simple Ising model, while the performance of the 8-state Potts model, which exhibits a first-order phase transition, is limited due to emerging barriers and the resulting large integrated autocorrelation times. The quality of estimates in parallel production runs remains of the same order at same statistical cost., 7 pages, 9 figures

Generalized-ensemble Monte Carlo simulations such as the multicanonical method and similar techniques are among the most efficient approaches for simulations of systems undergoing discontinuous phase transitions or with rugged free- energy landscapes. As Markov chain methods, they are inherently serial computationally. It was demonstrated recently, however, that a combination of independent simulations that communicate weight updates at variable intervals allows for the efficient utilization of parallel computational resources for multicanonical simulations. Implementing this approach for the many-thread architecture provided by current generations of graphics processing units (GPUs), we show how it can be efficiently employed with of the order of $10^4$ parallel walkers and beyond, thus constituting a versatile tool for Monte Carlo simulations in the era of massively parallel computing. We provide the fully documented source code for the approach applied to the paradigmatic example of the two-dimensional Ising model as starting point and reference for practitioners in the field., Comment: source code available at https://github.com/CQT-Leipzig/cudamuca

We study the scaling laws of diffusion in two-dimensional media with long-range correlated disorder through exact enumeration of random walks. The disordered medium is modelled by percolation clusters with correlations decaying with the distance as a power law, $r^{-a}$, generated with the improved Fourier filtering method. To characterize this type of disorder, we determine the percolation threshold $p_{\text c}$ by investigating cluster-wrapping probabilities. At $p_{\text c}$, we estimate the (sub-diffusive) walk dimension $d_{\text w}$ for different correlation exponents $a$. Above $p_{\text c}$, our results suggest a normal random walk behavior for weak correlations, whereas anomalous diffusion cannot be ruled out in the strongly correlated case, i.e., for small $a$., Comment: 11 pages, 6 figures

We compare the transition barrier that accompanies a first-order phase transition in the canonical and microcanonical ensemble. This is directly encoded in the probability distributions of standard Metropolis Monte Carlo simulations and a proper microcanonical sampling technique. For the example of droplet formation, we find that in both ensembles the transition barrier scales as expected but that the barrier is much smaller in the microcanonical ensemble. In addition its growth with system size is weaker which will enhance this difference for larger systems. We provide an intuitive physical explanation for this observation., Comment: 5 pages, 1 figure, conference proceedings of 2017 CCP workshop

We analyze the structural behavior of a single polymer chain inside an attractive sphere. Our model is composed of a coarse-grained polymer governed by Lennard-Jones interactions of the monomers and an attractive sphere potential which follows by integrating the monomer-monomer interaction over the (inner) surface of the sphere. By means of extensive multicanonical Monte Carlo simulations it is shown that the system exhibits a rich phase diagram in the adsorption strength-temperature (e − T) plane ranging from highly ordered and compact to extended and random coil structures and from desorbed to partially or even completely adsorbed conformations. These findings are identified with different energetic and structural observables. The resulting phase diagram in the e − T plane is compared with that for a polymer adsorbing to a plane, attractive substrate obtained previously by Moddel, Bachmann, and one of the authors.

We discuss and compare two different methods that can be used to investigate self-avoiding walks on lattices with random site dilution. One is the so-called pruned-enriched Rosenbluth method (PERM), a chain-growth Monte Carlo algorithm, the other is a recently developed exact enumeration technique. While the latter is highly efficient for systems close to the critical concentration, it cannot be used for less dilute systems. PERM is more versatile but appears to have difficulties coping with strong confinement.

We present a simulation and data analysis technique to investigate first-order phase transitions and the associated transition barriers. The simulation technique is based on the real microcanonical ensemble where the sum of kinetic and potential energy is kept constant. The method is tested for the droplet condensation-evaporation transition in a Lennard-Jones system with up to 2048 particles at fixed density, using simple Metropolis-like sampling combined with a replica-exchange scheme. Our investigation of the microcanonical ensemble properties reveals that the associated transition barrier is significantly lower than in the canonical counterpart. Along the line of investigating the microcanonical ensemble behavior, we develop a framework for general ensemble evaluations. This framework is based on a clear separation between system-related and ensemble-related properties, which can be exploited to specifically tailor artificial ensembles suitable for first-order phase transitions.

We study the peculiarities of stretching of globular polymer macromolecules in a disordered (crowded) environment, using the model of self-attracting self-avoiding walks on site-diluted percolative lattices in space dimensions d = 3 . Applying the pruned–enriched Rosenbluth chain-growth method (PERM), we construct the phase diagram of collapsed–extended state coexistence when varying temperature and stretching force. The change in shape characteristics of globular polymers under stretching is analyzed as well.

We discuss the advantages of parallelization by multithreading on graphics processing units (GPUs) for parallel tempering Monte Carlo computer simulations of an exemplified bead-spring model for homopolymers. Since the sampling of a large ensemble of conformations is a prerequisite for the precise estimation of statistical quantities such as typical indicators for conformational transitions like the peak structure of the specific heat, the advantage of a strong increase in performance of Monte Carlo simulations cannot be overestimated. Employing multithreading and utilizing the massive power of the large number of cores on GPUs, being available in modern but standard graphics cards, we find a rapid increase in efficiency when porting parts of the code from the central processing unit (CPU) to the GPU., 8 pages, 9 figures, 2 tables

Population annealing is a novel generalized-ensemble simulation scheme used in large-scale parallel Monte Carlo simulations of disordered spin systems and similar problems. In a recent publication we proposed a generalization of this method to molecular dynamics simulations of biopolymers. In the present article we review this work and introduce a scheme for automatically choosing the temperature steps based on the observed distribution of potential energies in the population of simulated replica.

We investigate new programming techniques for parallel tempering Monte Carlo simulations of an elementary bead-spring homopolymer model using graphics processing units (GPUs). For a precise estimation of statistical quantities, like the peak structure of the specific heat, a large number of conformations with substantial statistical data is needed. Therefore the advantage of gathering this data faster by improving the performance of Monte Carlo simulations cannot be overrated. With the huge computational capability of the large number of cores on GPUs, that can be exploited by means of multithreaded programming, we find significant increases in e_ciency compared to CPU-only simulations.