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	Description	Assignment due
Tue Oct 22	No class	Andre on travel
Thu Oct 24	No class
Tue Oct 29	Intro, CMSE, MATLAB data analysis I
Thu Oct 31	MATLAB data analysis II, MATLAB practice, water_models.csv, MATLAB Project, ASTM_C_TypeI.csv, ASTM_C_TypeIII.csv
Tue Nov 5	MATLAB project	Andre on travel
Thu Nov 7	OOF2 - Theory, OOF2 - Practice, bimetallic.png	Abstract feedback 1 Matlab project figure upload for feedback
Tue Nov 12	OOF2 - Practice, OOF2 Walkthrough, OOF2 Project, crack.png	MATLAB project due: 11/13, 11.59 pm, upload here; Quiz 1: MATLAB, finish before 11/13, 11.59 pm;
Thu Nov 14	OOF2 project	Abstract feedback 2 Andre on travel
Tue Nov 19	ThermoCalc - Theory I, OOF2 project
Thu Nov 21	ThermoCalc Walkthrough, OOF2 project	Project abstract upload, OOF2 Project due: 12/3, 11.59 pm; Quiz 2: OOF2, finish before 12/3, 11.59 pm;
Tue Nov 26	Thanksgiving Break
Thu Nov 28	Thanksgiving Break
Tue Dec 3	ThermoCalc - Theory II, ThermoCalc Project
Thu Dec 5	ThermoCalc - Practice, ThermoCalc Project
Tue Dec 10	ThermoCalc Project
Thu Dec 12	Reading Day	ThermoCalc Project (due: 12/16, 11.59 pm); Quiz 3: ThermoCalc (due: 12/16, 11.59 pm); Term project (due: 12/18, 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