TEACHING INTERESTS: Statistical Thermodynamics

Statistical Mechanics is the application of the laws of mechanics (quantum and classical) to the microscopic motions of atoms and molecules in order to derive all the pertinent macroscopic laws such as the laws of thermodynamics, chemical kinetics, fluid dynamics, dielectric phenomena, magnetic phenomena, adsorption, diffusion, etc. In other words, statistical mechanics provides the molecular foundation for these macroscopic laws. The term "statistical thermodynamics" was proposed for use by Josiah Willard Gibbs in 1902. I have taught this subject in many incarnations, and this specific set of lecture slides, course outline and reading list constitutes only one version, used in the course described below. The problem sets and sample exams are taken from other versions of the course.

STATISTICAL THERMODYNAMICS WITH NUMERICAL APPLICATIONS

Chemistry 448 Spring Semester 2000

Prof. Cynthia J. Jameson

What we hope to accomplish in this semester is in two parts. First we start with the traditional fundamental approach, with examples in systems of non-interacting particles; we will consider microcanonical, canonical, and grand canonical ensembles, partition functions, and applications of partition functions to a priori determination of chemical equilibrium constants. We will consider systems of interacting particles and mixtures. Second, we will introduce numerical methods, starting with the simple random walk, introduce Monte Carlo sampling, and apply the Monte Carlo method to systems of interacting particles, to mixtures and heterogeneous systems. We will consider distribution functions and correlation functions. Other topics will be included, subject to student interests. As early as possible, we will do computer simulations. Students will run their own simulations, starting out with a working sample Monte Carlo program, which they can customize to do a computer simulation in their own interest, or they may choose to carry out a molecular dynamics simulation project, which will be the basis for the grade in the course.

• Course Outline
• Reading List