Statistical Thermodynamics in Chemistry and Biology

The course introduces the basis of statistical thermodynamics with examples from chemistry and biology: entropy and Boltzmann distribution law, lattice models for liquids and mixtures, free energies, partition functions, chemical equilibrium, kinetics and transport processes, electrochemistry, intermolecular forces, adsorption, phase transitions, catalysis, and polymers.

After the course, the student is expected to be able to:

• Explain the basic concepts and principles in statistical thermodynamics.
• Use lattice models to study basic phenomena in chemistry and nanoscience.
• Construct new models based on the basic principles in statistical thermodynamics.

Skills:

• Use Python programming to solve exercise

Lectures and exercises. Obligatory programming exercises in Python.

Expected work load in the course is 200-225 hours.