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 18 Intro, CMSE, MATLAB data analysis I Note: 2-4 pm
Thu Oct 20 MATLAB data analysis II, MATLAB practice, water_models.csv
Tue Oct 25 OOF2 - Theory, MATLAB Project, ASTM_C_TypeI.csv, ASTM_C_TypeIII.csv Note: 2-4 pm
Thu Oct 27 OOF2 - Practice, OOF2 Walkthrough, bimetallic.png, OOF2 Project, crack.png Note: 2-5 pm
Tue Nov 1 MATLAB project, OOF2 project Andre on travel
Thu Nov 3 MATLAB project, OOF2 project Andre on travel
Tue Nov 8 Election Day
Thu Nov 10 MATLAB project, OOF2 project Andre on travel, Project abstract upload
Tue Nov 15 ThermoCalc - Theory I, MATLAB project MATLAB project due: 11/15, 11.59 pm, upload here; Quiz 1: MATLAB, finish before 11/7, 11.59 pm;
Thu Nov 17 ThermoCalc - Theory II, ThermoCalc - Practice, OOF2 project Note: 2-4 pm, OOF2 Project due: 11/28, 11.59 pm, Quiz 2: OOF2, finish before 11/28, 11.59 pm;
Tue Nov 22 Thanksgiving Break
Thu Nov 24 Thanksgiving Break
Tue Nov 29 ThermoCalc Walkthrough, ThermoCalc Project
Thu Dec 1 ThermoCalc Project
Tue Dec 6 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
Participation6
Quizzes9
Project 1 (MATLAB)20
Project 2 (OOF2)20
Project 3 (Thermocalc)20
Term Project Abstract5
Term Project20

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