MSE 494, 598 – Topic: Microstructure Modeling & Simulations

Course Objective

This course will introduce students to the field of modeling and simulation of microstructural evolution. In the beginning of the course, fundamental key methods and basic numerical algorithms for prediction of microstructures will be discussed while citing examples from scientific and industrial applications. It will be followed by lectures on Phase-field method, which is one of the most popular and robust techniques to investigate microstructural evolution at the mesoscopic length and diffusive time scales. A short overview of other approaches in terms of their capabilities and limitations will also be provided. Students will gain hands-on experience in computer coding and model development for microstructural evolution that accompanies alloy solidification, spinodal decomposition, and grain growth, as shown below. Both, fundamental concepts as well as necessary analytical and numerical techniques for solving governing phase-field equations will be covered.  


The students should be familiar with computer programming language C/C++, and have a basic knowledge of linear algebra, differential equation, materials thermodynamics and kinetics. Programming basics will be reviewed in the early part of this course. The instructor will explain an example code to make the course accessible to students with minimal programming experience. Classroom tasks will be assigned while students get to choose their team projects. They are expected to combine their knowledge of materials science and computer programming in order to simulate various kinds of microstructures.

Grading Method:

The semester score will be determined based on a set of evaluation methods, and the weights are: 40% homework; 30% midterm exam; 30% final exam. The semester grade will be determined according to following scale:

A+ A A- B+ B B- C+ C D E
>97 >93 >89 >86 >83 >79 >76 >70 >60 <60


We will primarily be using C/C++ in this course. GCC compiler installed on Ubuntu (Linux operating system) is highly recommended. For data visualization, an open-source software, Gnuplot, will be used.