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

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This class uses the Canvas Learning Management 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 22 Intro, CMSE
Thu Oct 24 MATLAB data analysis, MATLAB practice, water_models.csv
Tue Oct 29 MATLAB Project (Travel), ASTM_C_TypeI.csv, ASTM_C_TypeIII.csv
Thu Oct 31 OOF2 - Practice
Tue Nov 5 OOF2 - Theory
Thu Nov 7 OOF2 Walkthrough (Travel), bimetallic.tiff MATLAB project due: 11/8, 11.59 pm, upload here; Quiz 1: MATLAB, finish before 11/8, 11.59 pm;
Tue Nov 12 OOF2 Project (makeup class), crack.tiff
Thu Nov 14 OOF2 project Project abstract upload
Tue Nov 19 ThermoCalc - Theory
Thu Nov 21 ThermoCalc - Practice, ThermoCalc Walkthrough OOF2 Project due: 11/30, 11.59 pm, crack.tiff, Quiz 2: OOF2, finish before 11/30, 11.59 pm;
Tue Nov 26 Thanksgiving Break
Thu Nov 28 Thanksgiving Break
Tue Dec 3 ThermoCalc Project (makeup class)
Thu Dec 5 ThermoCalc Project (Travel)
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: 12/20, 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
Attendance5
Quizzes10
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