Course description: A working knowledge of thermodynamics and statistical mechanics is critical for solving many classes of problems that occur in both academic and industrial research settings. Statistical thermodynamics is important in solving problems in areas as diverse as reaction kinetics, catalysis, biochemical engineering, polymer engineering, drug design, and separations. This class will provide the student with basic thermodynamic tools for solving many classes of problems. It will also help the student gain a working knowledge of classical and statistical thermodynamics specifically as it relates to the calculation of thermophysical properties, phase equilibria, and chemical equilibria. Intended for first year chemical engineering graduate students with at least one undergraduate course in classical thermodynamics. Students from other departments may join with permission from the instructor.

Course description: Covers solutions to linear and nonlinear sets of equations, numerical solutions of partial differential equations, introductory partial differential equations and numerical methods, linear and nonlinear regression. Uses Matlab to teach skills in programming and algorithm design.