The Experts below are selected from a list of 267 Experts worldwide ranked by ideXlab platform

Fujiu Ke - One of the best experts on this subject based on the ideXlab platform.

  • molecular cluster Statistical Thermodynamics methods to simulate quasi static deformations at finite temperature
    International Journal of Solids and Structures, 2008
    Co-Authors: Haiying Wang, Ming Hu, Fujiu Ke
    Abstract:

    The rapid evolution of nanotechnology appeals for the understanding of global response of nanoscale systems based on atomic interactions, hence necessitates novel, sophisticated, and physically based approaches to bridge the gaps between various length and time scales. In this paper, we propose a group of Statistical Thermodynamics methods for the simulations of nanoscale systems under quasi-static loading at finite temperature, that is, molecular Statistical Thermodynamics (MST) method, cluster Statistical Thermodynamics (CST) method, and the hybrid molecular/cluster Statistical Thermodynamics (HMCST) method. These methods, by treating atoms as oscillators and particles simultaneously, as well as clusters, comprise different spatial and temporal scales in a unified framework. One appealing feature of these methods is their "seamlessness" or consistency in the same underlying atomistic model in all regions consisting of atoms and clusters, and hence can avoid the ghost force in the simulation. On the other hand, compared with conventional MD simulations, their high computational efficiency appears very attractive, as manifested by the simulations of uniaxial compression and nanoindenation. (C) 2008 Elsevier Ltd. All rights reserved.

  • Molecular/cluster Statistical Thermodynamics methods to simulate quasi-static deformations at finite temperature
    International Journal of Solids and Structures, 2008
    Co-Authors: Haiying Wang, Ming Hu, Fujiu Ke
    Abstract:

    The rapid evolution of nanotechnology appeals for the understanding of global response of nanoscale systems based on atomic interactions, hence necessitates novel, sophisticated, and physically based approaches to bridge the gaps between various length and time scales. In this paper, we propose a group of Statistical Thermodynamics methods for the simulations of nanoscale systems under quasi-static loading at finite temperature, that is, molecular Statistical Thermodynamics (MST) method, cluster Statistical Thermodynamics (CST) method, and the hybrid molecular/cluster Statistical Thermodynamics (HMCST) method. These methods, by treating atoms as oscillators and particles simultaneously, as well as clusters, comprise different spatial and temporal scales in a unified framework. One appealing feature of these methods is their "seamlessness" or consistency in the same underlying atomistic model in all regions consisting of atoms and clusters, and hence can avoid the ghost force in the simulation. On the other hand, compared with conventional MD simulations, their high computational efficiency appears very attractive, as manifested by the simulations of uniaxial compression and nanoindenation. (C) 2008 Elsevier Ltd. All rights reserved.

S A Safran - One of the best experts on this subject based on the ideXlab platform.

  • Statistical Thermodynamics of soft surfaces
    Surface Science, 2002
    Co-Authors: S A Safran
    Abstract:

    We review the continuum, Statistical Thermodynamics of surfaces and interfaces in soft matter where both the energy and entropy of the surface are comparable. These systems include complex fluids that are dominated by either surface tension or the interfacial curvature, such as: fluid and solid interfaces, colloidal dispersions, macromolecular solutions, membranes, and other self-assembling aggregates such as micelles, vesicles, and microemulsions. The primary focus is on the theoretical concepts, their universality, and the role of fluctuations and inhomogeneities with connections to relevant experimental systems.

  • Statistical Thermodynamics of soft surfaces
    Surface Science, 2002
    Co-Authors: S A Safran
    Abstract:

    We review the continuum, Statistical Thermodynamics of surfaces and interfaces in soft matter where both the energy and entropy of the surface are comparable. These systems include complex fluids that are dominated by either surface tension or the interfacial curvature, such as: fluid and solid interfaces, colloidal dispersions, macromolecular solutions, membranes, and other self-assembling aggregates such as micelles, vesicles, and microemulsions. The primary focus is on the theoretical concepts, their universality, and the role of fluctuations and inhomogeneities with connections to relevant experimental systems. © 2001 Elsevier Science B.V. All rights reserved.

Haiying Wang - One of the best experts on this subject based on the ideXlab platform.

  • molecular cluster Statistical Thermodynamics methods to simulate quasi static deformations at finite temperature
    International Journal of Solids and Structures, 2008
    Co-Authors: Haiying Wang, Ming Hu, Fujiu Ke
    Abstract:

    The rapid evolution of nanotechnology appeals for the understanding of global response of nanoscale systems based on atomic interactions, hence necessitates novel, sophisticated, and physically based approaches to bridge the gaps between various length and time scales. In this paper, we propose a group of Statistical Thermodynamics methods for the simulations of nanoscale systems under quasi-static loading at finite temperature, that is, molecular Statistical Thermodynamics (MST) method, cluster Statistical Thermodynamics (CST) method, and the hybrid molecular/cluster Statistical Thermodynamics (HMCST) method. These methods, by treating atoms as oscillators and particles simultaneously, as well as clusters, comprise different spatial and temporal scales in a unified framework. One appealing feature of these methods is their "seamlessness" or consistency in the same underlying atomistic model in all regions consisting of atoms and clusters, and hence can avoid the ghost force in the simulation. On the other hand, compared with conventional MD simulations, their high computational efficiency appears very attractive, as manifested by the simulations of uniaxial compression and nanoindenation. (C) 2008 Elsevier Ltd. All rights reserved.

  • Molecular/cluster Statistical Thermodynamics methods to simulate quasi-static deformations at finite temperature
    International Journal of Solids and Structures, 2008
    Co-Authors: Haiying Wang, Ming Hu, Fujiu Ke
    Abstract:

    The rapid evolution of nanotechnology appeals for the understanding of global response of nanoscale systems based on atomic interactions, hence necessitates novel, sophisticated, and physically based approaches to bridge the gaps between various length and time scales. In this paper, we propose a group of Statistical Thermodynamics methods for the simulations of nanoscale systems under quasi-static loading at finite temperature, that is, molecular Statistical Thermodynamics (MST) method, cluster Statistical Thermodynamics (CST) method, and the hybrid molecular/cluster Statistical Thermodynamics (HMCST) method. These methods, by treating atoms as oscillators and particles simultaneously, as well as clusters, comprise different spatial and temporal scales in a unified framework. One appealing feature of these methods is their "seamlessness" or consistency in the same underlying atomistic model in all regions consisting of atoms and clusters, and hence can avoid the ghost force in the simulation. On the other hand, compared with conventional MD simulations, their high computational efficiency appears very attractive, as manifested by the simulations of uniaxial compression and nanoindenation. (C) 2008 Elsevier Ltd. All rights reserved.

Themis Matsoukas - One of the best experts on this subject based on the ideXlab platform.

  • Thermodynamics Beyond Molecules: Statistical Thermodynamics of Probability Distributions
    Entropy, 2019
    Co-Authors: Themis Matsoukas
    Abstract:

    Statistical Thermodynamics has a universal appeal that extends beyond molecular systems, and yet, as its tools are being transplanted to fields outside physics, the fundamental question, what is Thermodynamics, has remained unanswered. We answer this question here. Generalized Statistical Thermodynamics is a variational calculus of probability distributions. It is independent of physical hypotheses but provides the means to incorporate our knowledge, assumptions and physical models about a stochastic processes that gives rise to the probability in question. We derive the familiar calculus of Thermodynamics via a probabilistic argument that makes no reference to physics. At the heart of the theory is a space of distributions and a special functional that assigns probabilities to this space. The maximization of this functional generates the mathematical network of thermodynamic relationship. We obtain Statistical mechanics as a special case and make contact with Information Theory and Bayesian inference.

  • Generalized Statistical Thermodynamics
    arXiv: Statistical Mechanics, 2018
    Co-Authors: Themis Matsoukas
    Abstract:

    We develop the mathematical theory of generalized Statistical Thermodynamics by constructing phase spaces (canonical and microcanonical) of probability distributions. Generalized Thermodynamics is independent of physical hypotheses; it is applicable to probability distributions in general and provides the means to incorporate our knowledge, hypotheses and physical models about a stochastic process. The second law, Gibbs-Shannon entropy and Kullback-Leibler divergence, all have straightforward and noncontroversial interpretation in this theory. We obtain Statistical mechanics as a special case and make contact with Information Theory and Bayesian inference.

  • Thermodynamics Beyond Molecules: Statistical Thermodynamics of Distributions
    arXiv: Statistical Mechanics, 2018
    Co-Authors: Themis Matsoukas
    Abstract:

    Statistical Thermodynamics has a universal appeal that extends beyond molecular systems, and yet, as its tools are being transplanted to fields outside physics, the fundamental question, \textit{what is Thermodynamics?}, has remained unanswered. We answer this question here. Generalized Statistical Thermodynamics is a variational calculus of probability distributions. It is independent of physical hypotheses but provides the means to incorporate our knowledge, assumptions and physical models about a stochastic processes that gives rise to the probability in question. We derive the familiar calculus of Thermodynamics via a probabilistic argument that makes no reference to physics. At the heart of the theory is a space of distributions and a special functional that assigns probabilities to this space. The maximization of this functional generates the entire mathematical network of thermodynamic relationships. We obtain Statistical mechanics as a special case and make contact with Information Theory and Bayesian inference.

  • Statistical Thermodynamics of irreversible aggregation the sol gel transition
    Scientific Reports, 2015
    Co-Authors: Themis Matsoukas
    Abstract:

    Binary aggregation is known to lead, under certain kinetic rules, to the coexistence of two populations, one consisting of finite-size clusters (sol), and one that contains a single cluster that carries a finite fraction of the total mass (giant component or gel). The sol-gel transition is commonly discussed as a phase transition by qualitative analogy to vapor condensation. Here we show that the connection to thermodynamic phase transition is rigorous. We develop the Statistical Thermodynamics of irreversible binary aggregation in discrete finite systems, obtain the partition function for arbitrary kernel, and show that the emergence of the gel cluster has all the hallmarks of a phase transition, including an unstable van der Waals loop. We demonstrate the theory by presenting the complete pre- and post-gel solution for aggregation with the product kernel.

Bingzheng Jiang - One of the best experts on this subject based on the ideXlab platform.

  • Statistical Thermodynamics OF POLYDISPERSE POLYMER MIXTURES
    Polymer, 2003
    Co-Authors: Lijia An, Rongtang Ma, Xinyi Tang, Bingzheng Jiang
    Abstract:

    Abstract A Statistical Thermodynamics theory of polydisperse polymer blends based on a lattice model description of a fluid is formulated. Characterization of a binary polydisperse polymer mixture requires a knowledge of the pure polymer system and the interaction energy. It is assumed that the intrinsic and interactive properties of polymer (for example, T∗ , P∗ , ϱ∗, and e∗ ij ) are independent of molecular size. Thermodynamic properties of ternary and higher order mixtures are completely defined in terms of the pure fluid polymer parameters and the binary interaction energies. Thermodynamic stability criteria for the phase transitions of a binary mixture are shown. The binodal and spinodal of general binary systems and of special binary systems are discussed.

  • Statistical Thermodynamics OF A LATTICE FLUID - PURE POLYMER
    Polymer, 2003
    Co-Authors: Lijia An, Rongtang Ma, Xinyi Tang, Bingzheng Jiang
    Abstract:

    A Statistical Thermodynamics theory of a polydisperse polymer based on a lattice model of a fluid is formulated. The pure polydisperse polymer is completely characterized by three scale factors and the distribution law of the system. The equation of state does not satisfy a simple corresponding state principle, except for the polymer fluid with sufficiently high molecular weight.

  • Statistical Thermodynamics OF POLYDISPERSE POLYMERS
    Polymer, 1993
    Co-Authors: Lijia An, Rongtang Ma, Xinyi Tang, Bingzheng Jiang
    Abstract:

    Abstract A Statistical Thermodynamics theory of polydisperse polymers based on a lattice model of fluids is formulated. Pure polydisperse polymer can be completely characterized by three scale factors and the molecular weight distribution of the system. The equation of state does not satisfy a simple corresponding-states principle, except for a polymer fluid of sufficiently high molecular weight. The relationships between thermal expansion coefficient α and isothermal compressibility β with reduced variables are also predicted.

  • Statistical Thermodynamics of polydisperse polymer blends with strong interaction
    Die Makromolekulare Chemie Theory and Simulations, 1993
    Co-Authors: Lijia An, Rongtang Ma, Xinyi Tang, Bingzheng Jiang
    Abstract:

    A Statistical Thermodynamics theory of polydisperse polymer mixtures with strong interaction between dissimilar components based on a lattice fluid model is formulated. Expressions for the free energy, equation of state, phase stability and spinodal for a polydisperse, binary polymer mixture with strong interaction are derived.