MSE404 :: MatSE Illinois :: University of Illinois at Urbana-Champaign
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This class uses the CampusWire System for announcements, updates, and all communication between the instructor, TA, and students. Please visit this page to access it.
Excused Absences
Excused absences may be requested by filling out the Excused Absences form. For more information, please read the course syllabus.
Schedule
All lectures will be recorded and the recordings will be posted under this link.
| Date | Reading | Description | Assignment due |
|---|---|---|---|
| Tue Oct 17 | Intro, CMSE, MATLAB data analysis I | ||
| Thu Oct 19 | MATLAB data analysis II, MATLAB practice, water_models.csv | ||
| Tue Oct 24 | MATLAB Project, ASTM_C_TypeI.csv, ASTM_C_TypeIII.csv | ||
| Thu Oct 26 | MATLAB project | Abstract feedback 1Andre on travel | |
| Tue Oct 31 | OOF2 - Theory, MATLAB project | ||
| Thu Nov 2 | OOF2 - Practice, OOF2 Walkthrough, bimetallic.png | Abstract feedback 2Matlab project figure upload for feedback | |
| Tue Nov 7 | OOF2 Project, crack.png | MATLAB project due: 11/8, 11.59 pm, upload here; Quiz 1: MATLAB, finish before 11/8, 11.59 pm; | |
| Thu Nov 9 | ThermoCalc - Theory I | Project abstract upload | |
| Tue Nov 14 | OOF2 project | Andre on travel | |
| Thu Nov 16 | ThermoCalc Walkthrough, OOF2 project | OOF2 Project due: 11/28, 11.59 pm, Quiz 2: OOF2, finish before 11/28, 11.59 pm; | |
| Tue Nov 21 | Thanksgiving Break | ||
| Thu Nov 23 | Thanksgiving Break | ||
| Tue Nov 28 | ThermoCalc - Theory II, ThermoCalc Project | ||
| Thu Nov 30 | ThermoCalc - Practice, ThermoCalc Project | ||
| Tue Dec 5 | ThermoCalc Project | ||
| Thu Dec 8 | Reading Day | ThermoCalc Project (due: 12/12, 11.59 pm), Quiz 3: ThermoCalc (due: 12/12, 11.59 pm), Term project (due: 12/15, 11.59 pm, Upload here) |
Course Description
Scope
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.
Objectives
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
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 |
|---|---|
| Participation | 6 |
| Quizzes | 9 |
| Project 1 (MATLAB) | 20 |
| Project 2 (OOF2) | 20 |
| Project 3 (Thermocalc) | 20 |
| Term Project Abstract | 5 |
| Term Project | 20 |
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 |