MSE404 :: MatSE Illinois :: University of Illinois at Urbana-Champaign


Online discussion forum

This class uses Piazza for announcements, updates, and all communication between the instructor, TA, and students. Please visit this page to register.

Excused Absences

Excused absences may be requested by filling out the Excused Absences form. For more information, please read the course syllabus.


All lectures will be recorded and the recordings will be posted under this link.

Date Reading Description Assignment due
Tue Oct 23 Intro, CMSE
Thu Oct 25 Travel
Tue Oct 30 MATLAB Project, ASTM_C_TypeI.csv, ASTM_C_TypeIII.csv, MATLAB data analysis, water_models.csv
Thu Nov 1 MATLAB data analysis, OOF2 - Theory
Tue Nov 6 OOF2 - Practice/Walkthrough, bimetallic.tiff
Thu Nov 8 Travel MATLAB project due: 11/9, 11.59 pm, upload here; Quiz 1: MATLAB, finish before 11/9, 11.59 pm;
Tue Nov 13 Walkthrough/Project (makeup class)
Thu Nov 15 ThermoCalc - Theory, OOF2 project (makeup class) Project abstract upload
Tue Nov 20 Thanksgiving Break
Thu Nov 22 Thanksgiving Break
Tue Nov 27 OOF2 project
Thu Nov 29 ThermoCalc Walkthrough OOF2 Project due: 11/30, 11.59 pm, crack.tiff, Quiz 2: OOF2, finish before 11/30, 11.59 pm;
Tue Dec 4 ThermoCalc - Practice
Thu Dec 6 Walkthrough/Project
Tue Dec 11 Project
Thu Dec 13 Reading Day ThermoCalc Project (due: 12/17, 11.59 pm),
Quiz 3: ThermoCalc (due: 12/17, 11.59 pm),
Term project (due: 12/21, 11.59 pm, Upload here)

Course Description


This class covers computer simulations on atomistic length and time scales for (structural or thermodynamic) properties of materials, numerical algorithms, and systematic and statistical error estimations. Concepts of statistical mechanics such as phase space and averages are critically important for this class. Students will become familiar with popular techniques to sample phase space, such as molecular dynamics (integration algorithms, static and dynamic correlations functions, and their connection to order and transport) and Monte Carlo and Random Walks (variance reduction, Metropolis algorithms, kinetic Monte Carlo, heat diffusion, Brownian motion). Example applications will include phase transitions (melting-freezing, calculating free energies) and polymers (growth and equilibrium structure). In addition, quantum simulations (zero temperature and finite temperature methods) and optimization techniques (e.g. simulated annealing) will be discussed.


The objective is to learn and apply fundamental techniques used in (primarily classical) simulations in order to help understand and predict properties of microscopic systems in materials science, physics, chemistry, and biology. Students will work towards a final project, where they will define, model, implement, and study a particular problem using atomic-scale simulation techniques. Use of the Python programming language, writing of proper reports, and presentation of results are important components of this class.

Course Grading


Your final grade for this class will be based upon your total score on all the components of the course. Please consult the course syllabus for details on particular components.

Course Component Percentage of total
Project 1 (MATLAB)20
Project 2 (OOF2)20
Project 3 (Thermocalc)20
Term Project25

Final Grade

The following cutoff table will be used to calculate final scores.

Final Grade Minimum Points
A+ 98
A 95
A– 92.5
B+ 87.5
B 85
B– 80
C+ 77.5
C 75
C– 66.7
D+ 58.3
D 50
D– 30
F <30