Course unit
Large particle systems
Last updated: 22/02/2024
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Course Director(s):
GANSTER Patrick
CHARRIERE Renée
General Description:
Statistical Physics (R. Charrière) :
This course is an introduction to statistical physics. The objective is to present the concepts and tools allowing the calculation of the physical properties of a population of elementary particles, atoms or molecules. We will insist on the transition from the microscopic description of the object, making extensive use of quantum mechanics, to the macroscopic description of the population. We will thus see the transition from the quantum states of a single particle to those of a set of particles, and finally the link between these states and macroscopic quantities such as temperature, pressure, chemical potential. We will also see the particular case of a set of indistinguishable particles and the paradoxes that can arise in this case.
Atomistic simulations (P. Ganster) :
This course introduces atomic scale models and simulation tools that are used in many fields of industrial and basic research. After the presentation of different examples of use, the course presents different approximations necessary for the description of a large number of interacting atoms. In practical classes, you will use a molecular dynamics software (LAMMPS) to describe atomic systems (molecules, crystals) and derive physical properties from the nanometer scale.
Key words:
Statistic physics
statistic distributions
thermodynamic quantities
microscopic/macroscopic
Simulations
ab initio and empirical models
nanometric scale properties
Number of teaching hours
22
Fields of study
Materials Science
Mathematics
Chemistry, Process Engineering
Teaching language
French
Intended learning outcomes
| On completion of the unit, the student will be capable of: |
Classification level |
Priority |
| Master the concept of microcopic state and macroscopic state |
2. Understand |
Essential |
| Calculate a state density and a partition function |
3. Apply |
Essential |
| Calculate a thermodynamic quantity (pressure, temperature, free energy, ...) from the state density or the partition function |
3. Apply |
Essential |
| Understanding the theory establishing microcanonical and canonical distributions |
2. Understand |
Important |
| Know different description models at the atomic scale |
2. Understand |
Useful |
| Use a digital tool to describe and study nano systems |
3. Apply |
Useful |
| Understand the literature in the field and know its limits |
2. Understand |
Important |
Learning assessment methods
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Percentage ratio of individual assessment
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Percentage ratio of group assessment
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Written exam:
|
100
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%
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Project submission:
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0
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%
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Individual oral exam:
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0
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%
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Group presentation:
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0
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%
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Individual presentation:
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0
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%
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Group practical exercise:
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0
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%
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Individual practical exercise:
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0
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%
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Group report:
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0
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%
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Individual report:
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0
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%
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Other(s): 0 %
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Programme and content
| Type of teaching activity |
Content, sequencing and organisation |
| Course |
Statistical Physics :
Probabilities in physics
Definition of the microscopic and macroscopic states of a system
Presentation of the microcanonical and canonical distributions
Computing the thermodynamic functions and properties of a system (entropy, free energy, pressure, chemical potential…) - Presenting the problem of a system consituted of indiscernible particles
Maxwell-Boltzmann approximation Atomistic simulations :
Description of interacting atoms through different examples
From quantum mechanics to classical mechanics
State of the art
|
| Tutorial classes |
Statistical Physics :
Density of states computation
The classical perfect gaz and the Gibbs paradox -Heat capacity of solid materials |
| Practical classes |
Atomistic simulations :
Description of nano-objects and calculation of physical quantities with LAMMPS
|