D1 - Knowledge and understanding
At the end of the course, the student must demonstrate knowledge of the fundamental concepts of the equilibrium statistical mechanics.

D2 - Ability to apply knowledge and understanding
At the end of the course, the student must be able to correctly apply the concepts of statistical mechanics to realistic systems.

D3 - Autonomy of judgment
At the end of the course, the student must be able to analyze the concepts of the statistical mechanics in the framework of classical and quantum mechanics.

D4 - Communication skills
At the end of the course, the student will have to demonstrate that he/she is able to explain the concepts described in point D1

D5 - Learning skills
At the end of the course, the student must demonstrate to be able to use statistical mechanics to interpret physical and chemical phenomena.

Knowledge of fundamentals of thermodynamics and quantum mechanics.

- Boltzmann distribution
- Ideal gas, Boltzmann statistics
- Equipartition theorem
- Chemical equilibrium
- Vibrations in solids
- Third law of thermodynamics
- Real gas
- Liquids
- Fermi-Dirac and Bose-Einstein statistics

Statistical Mechanics: a concise introduction to chemists, D. Widom, Cambridge

An Introduction to Statistical Thermodynamics, T. L. Hill, Dover Pubns

Fundamentals thermodynamic formulas
- Boltzmann distribution
- Microcanonical, canonical (Z) and grandcanonical partition functions
- Two-level system
- Ideal gas, Boltzmann statistics
- Translational, vibrational, rotational and electronic Z
- Equipartition theorem
- Chemical equilibrium
- Vibrations in solids: Einstein and Debye models
- Third law of thermodynamics
- Real gas: virial coefficients, corrections for non-ideality
- Liquids: radial distribution function, qualitative discussion
- Computational methods: molecular dynamics and Monte Carlo
- Fermi-Dirac and Bose-Einstein statistics

Lectures.

Oral examination at the end of the course based on: questions about the concepts developed during the course and how to connect them, solving small numerical exercises, describing the physical meaning of the models and formulas of Statistical Mechanics. The evaluation is expressed in the scale of thirtieths: level of learning, appropriate language and ability of solving problems (by applying the theory on concrete examples) will be evaluated.

This course explores topics closely related to one or more goals of the United Nations 2030 Agenda for Sustainable Development (SDGs)