Search results for "Statistical Mechanic"

showing 10 items of 707 documents

ORDERING KINETICS IN QUASI-ONE-DIMENSIONAL ISING-LIKE SYSTEMS

1993

We present results of a Monte Carlo simulation of the kinetics of ordering in the two-dimensional nearest-neighbor Ising model in anL xM geometry with two free boundaries of length M≫L. This model can be viewed as representing an adsorbant on a stepped surface with mean terrace widthL. We follow the ordering kinetics after quenches to temperatures 0.25 ⩽ T/Tc ⩽ 1 starting from a random initial configuration at a coverage ofΘ=0.5 in the corresponding lattice gas picture. The systems evolve in time according to a Glauber kinetics with nonconserved order parameter. The equilibrium structure is given by a one-dimensional sequence of ordered domains. The ordering process evolves from a short ini…

Stochastic processLattice (order)Logarithmic growthMonte Carlo methodStatistical and Nonlinear PhysicsIsing modelStatistical physicsStatistical mechanicsStructure factorRandom walkMathematical PhysicsMathematics
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Noise Induced Phenomena in the Dynamics of Two Competing Species

2015

Noise through its interaction with the nonlinearity of the living systems can give rise to counter-intuitive phenomena. In this paper we shortly review noise induced effects in different ecosystems, in which two populations compete for the same resources. We also present new results on spatial patterns of two populations, while modeling real distributions of anchovies and sardines. The transient dynamics of these ecosystems are analyzed through generalized Lotka-Volterra equations in the presence of multiplicative noise, which models the interaction between the species and the environment. We find noise induced phenomena such as quasi-deterministic oscillations, stochastic resonance, noise …

Stochastic resonanceMultiplicative noiseFOS: Physical sciencesPopulation dynamic01 natural sciencesMultiplicative noiseNoise induced phenomena010305 fluids & plasmasLangevin equation0103 physical sciencesQuantitative Biology::Populations and EvolutionStatistical physicsQuantitative Biology - Populations and Evolution010306 general physicsCondensed Matter - Statistical MechanicsPhysicsExtinctionPredictive microbiologyStatistical Mechanics (cond-mat.stat-mech)Applied MathematicsPopulations and Evolution (q-bio.PE)Langevin equation; Multiplicative noise; Noise induced phenomena; Population dynamics; Predictive microbiology; Stochastic resonance; Modeling and SimulationSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Langevin equationNoiseModeling and SimulationFOS: Biological sciencesSpatial ecologyProbability distributionStochastic resonanceCoupled map lattice
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Confined binary two-dimensional colloidal crystals: Monte Carlo simulation of crack formation.

2010

Binary mixtures (A, B) of colloidal particles of different sizes in two dimensions may form crystals with square lattice structure (the A-particles occupying the white sites and the B-particles the black sites of a checkerboard). Confining such a system by two parallel 'walls' a distance D apart, long-range order in the direction parallel to the walls is stabilized by 'corrugated walls' that are commensurate with the lattice structure but destabilized by structureless 'hard walls', even if there is no misfit between the strip width D and the crystal lattice spacing. The crossover to quasi-one-dimensional behavior is studied by Monte Carlo simulations, analyzing Lindemann parameters and disp…

Stress (mechanics)CrystalCorrelation function (statistical mechanics)Materials scienceCondensed matter physicsMonte Carlo methodParticleGeneral Materials ScienceColloidal crystalCondensed Matter PhysicsCritical valueSquare latticeJournal of physics. Condensed matter : an Institute of Physics journal
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1980

A phenomenological theory of the Phase Distribution Chromatography (PDC)-separation effect is outlined and a theoretical equation for the measured PDC-calibration curves is given. Assuming a reversible-thermodynamical equilibrium in the polystyrene-PDC-column, only a relatively small part of the measured PDC-calibration curves could be explained: namely those running below their tangents. In order to explain the whole sigmoidal shape of the experimental curves, a theory of steady state in the system sol/gel was developed assuming deformation of the polymer coil near the gel front due to the stress related to the velocity gradient. The resulting dynamical flow-equilibrium differs highly from…

Stress (mechanics)Partition coefficientPartition function (statistical mechanics)Steady stateChromatographyDeformation (mechanics)ChemistryVelocity gradientPhase (matter)ThermodynamicsTangentDie Makromolekulare Chemie
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Disordered hyperuniformity in superconducting vortex lattices

2020

Particles occupying sites of a random lattice present density fluctuations at all length scales. It has been proposed that increasing interparticle interactions reduces long range density fluctuations, deviating from random behaviour. This leads to power laws in the structure factor and the number variance that can be used to characterize deviations from randomness which eventually lead to disordered hyperuniformity. It is not yet fully clear how to link density fluctuations with interactions in a disordered hyperuniform system. Interactions between superconducting vortices are very sensitive to vortex pinning, to the crystal structure of the superconductor and to the value of the magnetic …

Superconducting VorticesFOS: Physical sciencesCondensed Matter - Soft Condensed MatterCurrent Carrying Capability01 natural sciences010305 fluids & plasmasSuperconductivity (cond-mat.supr-con)Physics::Fluid DynamicsCondensed Matter::Superconductivity0103 physical sciences010306 general physicsCondensed Matter - Statistical MechanicsPinning StrengthSuperconductivityPhysicsStatistical Mechanics (cond-mat.stat-mech)Degree (graph theory)Condensed matter physicsDensity FluctuationCondensed Matter - SuperconductivityType II SuperconductorsFísicaCritical TemperaturesVortexStructure FactorsVortex ArrangementsSoft Condensed Matter (cond-mat.soft)Physical Review Research
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Toward a density functional description of liquid pH2.

2010

A finite-temperature density functional approach to describe the properties of parahydrogen in the liquid-vapor coexistence region is presented. The first proposed functional is zero-range, where the density-gradient term is adjusted so as to reproduce the surface tension of the liquid-vapor interface at low temperature. The second functional is finite-range and, while it is fitted to reproduce bulk pH2 properties only, it is shown to yield surface properties in good agreement with experiments. These functionals are used to study the surface thickness of the liquid-vapor interface, the wetting transition of parahydrogen on a planar Rb model surface, and homogeneous cavitation in bulk liquid…

Surface (mathematics)Chemical Physics (physics.chem-ph)Statistical Mechanics (cond-mat.stat-mech)Yield surfaceChemistryThermodynamicsFOS: Physical sciencesFísicaCondensed Matter - Soft Condensed MatterSpin isomers of hydrogenFunctional descriptionSurface tensionPhysics::Fluid DynamicsPlanarWetting transitionPhysics - Chemical PhysicsCavitationPhysics::Atomic and Molecular ClustersSoft Condensed Matter (cond-mat.soft)Physical and Theoretical ChemistryCondensed Matter - Statistical MechanicsThe journal of physical chemistry. A
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Structure and Dynamics of the Instantaneous Water/Vapor Interface Revisited by Path-Integral and Ab Initio Molecular Dynamics Simulations

2015

The structure and dynamics of the water/vapor interface is revisited by means of path-integral and second-generation Car-Parrinello ab-initio molecular dynamics simulations in conjunction with an instantaneous surface definition [A. P. Willard and D. Chandler, J. Phys. Chem. B 114, 1954 (2010)]. In agreement with previous studies, we find that one of the OH bonds of the water molecules in the topmost layer is pointing out of the water into the vapor phase, while the orientation of the underlying layer is reversed. Therebetween, an additional water layer is detected, where the molecules are aligned parallel to the instantaneous water surface.

Surface (mathematics)KineticsFOS: Physical sciencesMolecular Dynamics SimulationCondensed Matter - Soft Condensed MatterMolecular physicsMolecular dynamicsPhysics - Chemical PhysicsMaterials ChemistryMoleculePhysical and Theoretical ChemistryCondensed Matter - Statistical MechanicsPhysics::Atmospheric and Oceanic PhysicsChemical Physics (physics.chem-ph)Statistical Mechanics (cond-mat.stat-mech)Molecular StructureChemistryHydrogen bondWaterHydrogen BondingComputational Physics (physics.comp-ph)Surfaces Coatings and FilmsKineticsSteamPath integral formulationSoft Condensed Matter (cond-mat.soft)Physical chemistryPhysics - Computational PhysicsLayer (electronics)Water vaporThe Journal of Physical Chemistry B
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Detecting self-similarity in surface microstructures

2000

The relative configurational entropy per cell as a function of length scale is a sensitive detector of spatial self-similarity. For Sierpinski carpets the equally separated peaks of the above function appear at the length scales that depend on the kind of the carpet. These peaks point to the presence of self-similarity even for randomly perturbed initial fractal sets. This is also demonstrated for the model population of particles diffusing over the surface considered by Van Siclen, Phys. Rev. E 56 (1997) 5211. These results allow the subtle self-similarity traces to be explored.

Surface (mathematics)Length scalePhysicsCondensed Matter - Materials Scienceeducation.field_of_studySelf-similarityStatistical Mechanics (cond-mat.stat-mech)PopulationConfiguration entropyMaterials Science (cond-mat.mtrl-sci)FOS: Physical sciencesSurfaces and InterfacesFunction (mathematics)Condensed Matter PhysicsSurfaces Coatings and FilmsSierpinski triangleMaterials ChemistryPoint (geometry)Statistical physicseducationCondensed Matter - Statistical Mechanics
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Roughening of the Cu(110) surface

1993

The structure of the Cu(110) surface is studied at high temperatures using a combination of lattice-gas Monte Carlo and molecular dynamics methods with identical many-atom interactions derived from the effective medium theory. The anisotropic six-vertex model is used in the interpretation of the lattice-gas results. We find a clear roughening transition around T_R=1000K and T_R/T_M=0.81. Molecular dynamics reveals the clustering of surface defects as the atomistic mechanism of the transition and allows us to estimate characteristic time scales. For the system of size 50x50, the time scale of the local roughening at 1150 K of an initially smooth surface is of the order of 100 ps.

Surface (mathematics)Materials scienceCondensed Matter (cond-mat)Monte Carlo methodFOS: Physical sciencesGeneral Physics and Astronomychemistry.chemical_elementCondensed Matter02 engineering and technology01 natural sciencesInterpretation (model theory)Molecular dynamicsTransition metalPhase (matter)Vacancy defect0103 physical sciencesAnisotropy010306 general physicsPhysicsCondensed matter physicsOrder (ring theory)021001 nanoscience & nanotechnologyCopperSmooth surfaceCorrelation function (statistical mechanics)chemistry0210 nano-technologyPhysical Review Letters
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Does Young's equation hold on the nanoscale? A Monte Carlo test for the binary Lennard-Jones fluid

2010

When a phase-separated binary ($A+B$) mixture is exposed to a wall, that preferentially attracts one of the components, interfaces between A-rich and B-rich domains in general meet the wall making a contact angle $\theta$. Young's equation describes this angle in terms of a balance between the $A-B$ interfacial tension $\gamma_{AB}$ and the surface tensions $\gamma_{wA}$, $\gamma_{wB}$ between, respectively, the $A$- and $B$-rich phases and the wall, $\gamma _{AB} \cos \theta =\gamma_{wA}-\gamma_{wB}$. By Monte Carlo simulations of bridges, formed by one of the components in a binary Lennard-Jones liquid, connecting the two walls of a nanoscopic slit pore, $\theta$ is estimated from the inc…

Surface (mathematics)PhysicsCondensed matter physicsStatistical Mechanics (cond-mat.stat-mech)Monte Carlo methodGeneral Physics and AstronomyThermodynamic integrationFOS: Physical sciencesComputational Physics (physics.comp-ph)Contact angleSurface tensionPhysics::Fluid DynamicsDistribution functionWetting transitionPhysics - Computational PhysicsScalingCondensed Matter - Statistical Mechanics
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