Search results for "statistical mechanics"

showing 10 items of 706 documents

Slow dynamics in ion-conducting sodium silicate melts: Simulation and mode-coupling theory

2005

A combination of molecular-dynamics (MD) computer simulation and mode-coupling theory (MCT) is used to elucidate the structure-dynamics relation in sodium-silicate melts (NSx) of varying sodium concentration. Using only the partial static structure factors from the MD as an input, MCT reproduces the large separation in relaxation time scales of the sodium and the silicon/oxygen components. This confirms the idea of sodium diffusion channels which are reflected by a prepeak in the static structure factors around 0.95 A^-1, and shows that it is possible to explain the fast sodium-ion dynamics peculiar to these mixtures using a microscopic theory.

Materials scienceStatistical Mechanics (cond-mat.stat-mech)SiliconSodiumFOS: Physical sciencesGeneral Physics and Astronomychemistry.chemical_elementSodium silicateDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksOxygenIonchemistry.chemical_compoundchemistryChemical physicsMode couplingDiffusion (business)Microscopic theoryCondensed Matter - Statistical MechanicsEurophysics Letters (EPL)
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Do the contact angle and line tension of surface-attached droplets depend on the radius of curvature?

2018

Results from Monte Carlo simulations of wall-attached droplets in the three-dimensional Ising lattice gas model and in a symmetric binary Lennard-Jones fluid, confined by antisymmetric walls, are analyzed, with the aim to estimate the dependence of the contact angle $(\Theta)$ on the droplet radius $(R)$ of curvature. Sphere-cap shape of the wall-attached droplets is assumed throughout. An approach, based purely on "thermodynamic" observables, e.g., chemical potential, excess density due to the droplet, etc., is used, to avoid ambiguities in the decision which particles belong (or do not belong, respectively) to the droplet. It is found that the results are compatible with a variation $[\Th…

Materials scienceStatistical Mechanics (cond-mat.stat-mech)Tension (physics)Antisymmetric relationMonte Carlo methodNucleationFOS: Physical sciences02 engineering and technologyMechanicsCondensed Matter - Soft Condensed Matter021001 nanoscience & nanotechnologyCondensed Matter Physics01 natural sciencesRadius of curvature (optics)Contact anglePhysics::Fluid Dynamics0103 physical sciencesThermodynamic limitSoft Condensed Matter (cond-mat.soft)General Materials Science010306 general physics0210 nano-technologyCondensed Matter - Statistical MechanicsLine (formation)
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Statics and dynamics of colloid-polymer mixtures near their critical point of phase separation: A computer simulation study of a continuous Asakura–O…

2008

We propose a new coarse-grained model for the description of liquid-vapor phase separation of colloid-polymer mixtures. The hard-sphere repulsion between colloids and between colloids and polymers, which is used in the well-known Asakura-Oosawa (AO) model, is replaced by Weeks-Chandler-Anderson potentials. Similarly, a soft potential of height comparable to thermal energy is used for the polymer-polymer interaction, rather than treating polymers as ideal gas particles. It is shown by grand-canonical Monte Carlo simulations that this model leads to a coexistence curve that almost coincides with that of the AO model and the Ising critical behavior of static quantities is reproduced. Then the …

Materials sciencecritical pointsMonte Carlo methodFOS: Physical sciencesGeneral Physics and AstronomyThermodynamicsCondensed Matter - Soft Condensed MatterCritical point (mathematics)Molecular dynamicscolloidspolymer solutionsPhysical and Theoretical Chemistryliquid-vapour transformationsBinodalliquid mixturesLennard-Jones potentialMonte Carlo methodsDisordered Systems and Neural Networks (cond-mat.dis-nn)Statistical mechanicsCondensed Matter - Disordered Systems and Neural Networksself-diffusionIdeal gasliquid theoryCondensed Matter::Soft Condensed Mattermolecular dynamics methodLennard-Jones potentialSoft Condensed Matter (cond-mat.soft)Ising modelstatistical mechanicsphase separationThe Journal of Chemical Physics
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Effect of mixing and spatial dimension on the glass transition

2009

We study the influence of composition changes on the glass transition of binary hard disc and hard sphere mixtures in the framework of mode coupling theory. We derive a general expression for the slope of a glass transition line. Applied to the binary mixture in the low concentration limits, this new method allows a fast prediction of some properties of the glass transition lines. The glass transition diagram we find for binary hard discs strongly resembles the random close packing diagram. Compared to 3D from previous studies, the extension of the glass regime due to mixing is much more pronounced in 2D where plasticization only sets in at larger size disparities. For small size disparitie…

Materials sciencepacs:82.70.DdCondensed matter physicsStatistical Mechanics (cond-mat.stat-mech)business.industryDiagramRandom close packBinary numberFOS: Physical sciencesCondensed Matter - Soft Condensed MatterCondensed Matter::Disordered Systems and Neural NetworksCondensed Matter::Soft Condensed MatterOpticsPhase (matter)Mode couplingSoft Condensed Matter (cond-mat.soft)ddc:530Glass transitionbusinesspacs:64.70.Q-Mixing (physics)Condensed Matter - Statistical Mechanicspacs:64.70.PLine (formation)
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Mode-coupling theory of the glass transition for confined fluids

2012

We present a detailed derivation of a microscopic theory for the glass transition of a liquid enclosed between two parallel walls relying on a mode-coupling approximation. This geometry lacks translational invariance perpendicular to the walls, which implies that the density profile and the density-density correlation function depends explicitly on the distances to the walls. We discuss the residual symmetry properties in slab geometry and introduce a symmetry adapted complete set of two-point correlation functions. Since the currents naturally split into components parallel and perpendicular to the walls the mathematical structure of the theory differs from the established mode-coupling eq…

Mathematical analysisFOS: Physical sciencesCovarianceCondensed Matter - Soft Condensed MatterResidual01 natural sciencesSymmetry (physics)010305 fluids & plasmasCorrelation function (statistical mechanics)Classical mechanics0103 physical sciencesMode couplingPerpendicularSoft Condensed Matter (cond-mat.soft)Microscopic theory010306 general physicsGlass transition[PHYS.COND.CM-SCM]Physics [physics]/Condensed Matter [cond-mat]/Soft Condensed Matter [cond-mat.soft]Mathematics
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Fractional Laplacians and Levy flights in bounded domains

2018

We address L\'{e}vy-stable stochastic processes in bounded domains, with a focus on a discrimination between inequivalent proposals for what a boundary data-respecting fractional Laplacian (and thence the induced random process) should actually be. Versions considered are: restricted Dirichlet, spectral Dirichlet and regional (censored) fractional Laplacians. The affiliated random processes comprise: killed, reflected and conditioned L\'{e}vy flights, in particular those with an infinite life-time. The related concept of quasi-stationary distributions is briefly mentioned.

Mathematics - Spectral TheoryMathematics - Analysis of PDEsStatistical Mechanics (cond-mat.stat-mech)FOS: MathematicsFOS: Physical sciencesMathematical Physics (math-ph)Mathematics::Spectral TheorySpectral Theory (math.SP)Condensed Matter - Statistical MechanicsMathematical PhysicsAnalysis of PDEs (math.AP)
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Dynamical and statistical properties of high-temperature self-propagating fronts: An experimental study

2009

International audience; We present a detailed experimental study of high-temperature self-propagating fronts using image processing techniques. The intrinsic features of the wave propagation are investigated as a function of the combustion temperature TC for a model system made of titanium and silicon powders. Different front behavior is realized by changing the molar ratio x of the mixture Ti+xSi. Outside the range x=[0.3,1.5], no thermal front is propagating while inside, three regimes are observed: steady-state combustion which is characterized by a flat front propagating at constant velocity and two unsteady regimes. The combustion temperature (or the corresponding ratio x) is thus play…

Mesoscopic physicsMaterials scienceSiliconFront (oceanography)chemistry.chemical_elementMechanicsCombustion01 natural sciences010305 fluids & plasmas[ PHYS.PHYS.PHYS-CHEM-PH ] Physics [physics]/Physics [physics]/Chemical Physics [physics.chem-ph]Classical mechanicschemistry[ PHYS.COND.CM-SM ] Physics [physics]/Condensed Matter [cond-mat]/Statistical Mechanics [cond-mat.stat-mech]Position (vector)0103 physical sciencesThermal[PHYS.PHYS.PHYS-CHEM-PH]Physics [physics]/Physics [physics]/Chemical Physics [physics.chem-ph][PHYS.COND.CM-SM]Physics [physics]/Condensed Matter [cond-mat]/Statistical Mechanics [cond-mat.stat-mech]010306 general physicsBifurcationStationary state
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Micro- and mesoscopic process interactions in protein coagulation

2000

It has recently been recognized that pathological protein coagulation is responsible for lethal pathologies as diverse as amyloidosis, Alzheimer and TSE. Understanding the coagulation mechanisms is therefore stirring great interest. In previous studies we have shown that on profoundly different systems coagulation is the result of a strong interaction between two processes on different length scales (mesoscopic and microscopic). Here we report experiments on bovine serum albumin (BSA) showing that the overall mechanism is the result of at least 3 distinct and strongly intertwined processes, on both length scales: molecular conformational changes, solution demixing and intermolecular crossli…

Mesoscopic physicsPatient diagnosisbiologyBiochemistryMechanism (biology)ChemistryIntermolecular forcebiology.proteinBiophysicsCoagulation (water treatment)Statistical mechanicsBovine serum albuminProtein coagulationAIP Conference Proceedings
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Calculation of phase diagrams for models of metallic alloys

2007

We briefly review a longstanding problem of metallurgy and statistical physics, namely, the prediction of phase diagrams of binary alloys from simple model assumptions on the atomic interactions, such as Ising-type models. Various methods of statistical mechanics which have been applied to this problem are introduced and compared to each other, such as the cluster-variation method and Monte-Carlo simulation. The merits as well as the limitations of these methods are discussed, emphasizing examples of fcc and bcc lattices which are potentially relevant for the problem of short-range order and long-range order in metallic alloys such as Cu−Au, Ni−Cr, and Fe−Al.A brief comparison with correspo…

Metallic alloyMaterials scienceSimple (abstract algebra)Experimental dataBinary numberStatistical mechanicsStatistical physicsPhase diagram
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Monte Carlo Tests of Nucleation Concepts in the Lattice Gas Model

2013

The conventional theory of homogeneous and heterogeneous nucleation in a supersaturated vapor is tested by Monte Carlo simulations of the lattice gas (Ising) model with nearest-neighbor attractive interactions on the simple cubic lattice. The theory considers the nucleation process as a slow (quasi-static) cluster (droplet) growth over a free energy barrier $\Delta F^*$, constructed in terms of a balance of surface and bulk term of a "critical droplet" of radius $R^*$, implying that the rates of droplet growth and shrinking essentially balance each other for droplet radius $R=R^*$. For heterogeneous nucleation at surfaces, the barrier is reduced by a factor depending on the contact angle. U…

Models MolecularCanonical ensembleModels StatisticalMaterials scienceStatistical Mechanics (cond-mat.stat-mech)Monte Carlo methodNucleationThermodynamicsFOS: Physical sciencesCondensed Matter - Soft Condensed MatterModels ChemicalLattice (order)Cluster (physics)Soft Condensed Matter (cond-mat.soft)Computer SimulationIsing modelGasesStatistical physicsLever ruleCrystallizationMonte Carlo MethodAlgorithmsCondensed Matter - Statistical MechanicsQuasistatic process
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