Différences
Ci-dessous, les différences entre deux révisions de la page.
| Les deux révisions précédentes Révision précédente Prochaine révision | Révision précédente | ||
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animation:tutoriels:2011:houches [2013/01/30 14:09] sbarends |
animation:tutoriels:2011:houches [2015/01/07 10:04] (Version actuelle) |
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| ===== Full plan of lectures ===== | ===== Full plan of lectures ===== | ||
| - | === Lecture 1 : Introduction to Monte-Carlo and Molecular Dynamics, Walter Kob === | + | === Lecture 1: Introduction to Monte-Carlo and Molecular Dynamics, Walter Kob === |
| 1) Monte Carlo Technique | 1) Monte Carlo Technique | ||
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| * rare events | * rare events | ||
| - | === Lecture 2 : Soft Matter on a Lattice : From generic properties to semi-quantitative models, Ralf Everaers === | + | === Lecture 2: Soft Matter on a Lattice: From generic properties to semi-quantitative models, Ralf Everaers === |
| 1) Generic Polymer models / Monte Carlo techniques | 1) Generic Polymer models / Monte Carlo techniques | ||
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| * A semi-quantitative lattice model of RNA and DNA melting, folding & association | * A semi-quantitative lattice model of RNA and DNA melting, folding & association | ||
| - | === Lecture 3 : Molecular simulation approaches to polymer systems, J. Baschnagel === | + | === Lecture 3: Molecular simulation approaches to polymer systems, J. Baschnagel === |
| This course intends to give an introduction to molelcular simulation approaches of polymer systems. The computational study of the physical properties of polymers is challenging because of the extremely broad spectra of length and time scales governing their structure and dynamics. | This course intends to give an introduction to molelcular simulation approaches of polymer systems. The computational study of the physical properties of polymers is challenging because of the extremely broad spectra of length and time scales governing their structure and dynamics. | ||
| Therefore, the simulation models used in current research are obtained by some kind of coarse-graining procedure, designed to eliminate fast degrees of freedom. The resulting models can address phenomena over a specific window of time and length scales. This model-building step can take different levels of complexity, ranging from chemicallly realistic models over generic bead-spring models to coarse-grained representations of polymer systems inspired by self-consistent field theory or similar theoretical concepts and also tohierachical models encompassing many interconnected levels. After a brief introduction to polymer physics, serving as a justification for the coarse-graining idea, the course will discuss each level of modeling alluded to above, present adapted simulation strategies, and give example applications. | Therefore, the simulation models used in current research are obtained by some kind of coarse-graining procedure, designed to eliminate fast degrees of freedom. The resulting models can address phenomena over a specific window of time and length scales. This model-building step can take different levels of complexity, ranging from chemicallly realistic models over generic bead-spring models to coarse-grained representations of polymer systems inspired by self-consistent field theory or similar theoretical concepts and also tohierachical models encompassing many interconnected levels. After a brief introduction to polymer physics, serving as a justification for the coarse-graining idea, the course will discuss each level of modeling alluded to above, present adapted simulation strategies, and give example applications. | ||
| - | === Lecture 4 : Coarse-grained dynamics, Ignacio Pagonnabaraga === | + | === Lecture 4: Coarse-grained dynamics, Ignacio Pagonnabaraga === |
| In these lectures I will describe the physical basis of kinetic based coarse grained methods to describe the dynamics of materials in the mesoscale. In particular, I will analyze the relationship between lattice gases and the lattice Boltzman approaches. I will explore the flexibility that these approaches offer to model a variety of complex fluids, including binary mixtures, colloidal suspensions and electrolytes. | In these lectures I will describe the physical basis of kinetic based coarse grained methods to describe the dynamics of materials in the mesoscale. In particular, I will analyze the relationship between lattice gases and the lattice Boltzman approaches. I will explore the flexibility that these approaches offer to model a variety of complex fluids, including binary mixtures, colloidal suspensions and electrolytes. | ||
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| I will analyze critically the different approaches, their potentialities and limitations discussing representative examples. | I will analyze critically the different approaches, their potentialities and limitations discussing representative examples. | ||
| - | === Lecture 5 : Phase field models, Thierry Biben === | + | === Lecture 5: Phase field models, Thierry Biben === |
| Phase field models are very efficient tools to investigate the dynamics of a system undergoing a phase transition, or simply to solve a problem with free boundaries (moving interfaces for example). They are essentially based on two ingredients: the phase-field, a local order parameter field, and the corresponding dynamical equations. The goal of this lecture is to give an overview of the wide range of problems that can be treated with these models and to provide a practical experience on the way to design phase field models and to avoid the main dangers. We shall thus illustrate the different parts of the lecture with examples, and use the problem of the dendric growth as a basic example | Phase field models are very efficient tools to investigate the dynamics of a system undergoing a phase transition, or simply to solve a problem with free boundaries (moving interfaces for example). They are essentially based on two ingredients: the phase-field, a local order parameter field, and the corresponding dynamical equations. The goal of this lecture is to give an overview of the wide range of problems that can be treated with these models and to provide a practical experience on the way to design phase field models and to avoid the main dangers. We shall thus illustrate the different parts of the lecture with examples, and use the problem of the dendric growth as a basic example | ||