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 Atomistic Computer Modeling of Materials (SMA 5107  posted by  member7_php   on 3/2/2009  Add Courseware to favorites Add To Favorites  
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Ceder, Gerbrand, and Nicola Marzari, 3.320 Atomistic Computer Modeling of Materials (SMA 5107), Spring 2005. (Massachusetts Institute of Technology: MIT OpenCourseWare), (Accessed 07 Jul, 2010). License: Creative Commons BY-NC-SA

Atomistic Computer Modeling of Materials (SMA 5107)

Spring 2005

Matrix of atoms with an approaching methane molecule.

Still image from an animation of cold catalysis of methane, shown in the video for Lecture 14. (Image by Prof. Nicola Marzari.)

Course Highlights

This course features a complete set of video lectures.

Course Description

This course uses the theory and application of atomistic computer simulations to model, understand, and predict the properties of real materials. Specific topics include: energy models from classical potentials to first-principles approaches; density functional theory and the total-energy pseudopotential method; errors and accuracy of quantitative predictions: thermodynamic ensembles, Monte Carlo sampling and molecular dynamics simulations; free energy and phase transitions; fluctuations and transport properties; and coarse-graining approaches and mesoscale models. The course employs case studies from industrial applications of advanced materials to nanotechnology. Several laboratories will give students direct experience with simulations of classical force fields, electronic-structure approaches, molecular dynamics, and Monte Carlo.

This course was also taught as part of the Singapore-MIT Alliance (SMA) programme as course number SMA 5107 (Atomistic Computer Modeling of Materials).


Support for this course has come from the National Science Foundation's Division of Materials Research (grant DMR-0304019) and from the Singapore-MIT Alliance.

Special Features

  • Complete video lectures

Technical Requirements

Java® plug-in software is required to run the Java® files found on this course site. RealOne™ Player software is required to run the .rm files found on this course site. File decompression software, such as Winzip® or StuffIt®, is required to open the .zip files found on this course site.



The class is aimed at beginning graduate students and will introduce a variety of methods used in different fields of materials science.


Two 90 minute lectures with some lectures replaced by a laboratory.

Five lab assignments approximately every two or three weeks.


Grading is based on the lab assignments. There are no exams.


There is no required book for the course. Following are some suggested reference works; additional references are provided in lecture.

Allen, M. P., and D. J. Tildesley. Computer Simulation of Liquids. New York, NY: Oxford University Press, 1989. ISBN: 9780198556459.

Frenkel, D., and B. Smit. Understanding Molecular Simulation. 2nd ed. San Diego, CA: Academic Press, 2001. ISBN: 9780122673511.

Jensen, F. Introduction to Computational Chemistry. New York, NY: John Wiley & Sons, 1998. ISBN: 9780471984252.

Kaxiras, E. Atomic and Electronic Structure of Solids. Cambridge, UK: Cambridge University Press, 2003. ISBN: 9780521523394.

Martin, R. Electronic Structure: Basic Theory and Practical Methods. Cambridge, UK: Cambridge University Press, 2004. ISBN: 9780521782852.

Phillips, R. Crystals Defects and Microstructures. Cambridge, UK: Cambridge University Press, 2001. ISBN: 9780521793575.

Thijssen, J. M. Computational Physics. Cambridge, UK: Cambridge University Press, 1999. ISBN: 9780521575881.

Simulation Software

Quantum-Espresso is GNU Open Source quantum mechanical simulation software, used in the Labs and to create some lecture materials.


1 Introduction and Case Studies Prof. Gerbrand Ceder  
2 Potentials, Supercells, Relaxation, Methodology Prof. Gerbrand Ceder  
3 Potentials 2: Potentials for Organic Materials and Oxides

It's a Quantum World!
Prof. Gerbrand Ceder

Prof. Nicola Marzari
4 Lab 1: Energetics and Structure from Empirical Potentials    
5 First Principles Energy Methods: The Many-Body Problem Prof. Nicola Marzari  
6 First Principles Energy Methods: Hartree-Fock and DFT Prof. Nicola Marzari  
7 Technical Aspects of Density Functional Theory Prof. Nicola Marzari Assignment 1 due
8 Case Studies of DFT Prof. Nicola Marzari  
9 Advanced DFT: Success and Failure

DFT Applications and Performance
Prof. Nicola Marzari

Prof. Gerbrand Ceder
10 Lab 2: Density Functional Theory I    
11 Finite Temperature: Review of Stat Mech and Thermodynamics

Excitations in Materials and How to Sample Them
Prof. Gerbrand Ceder  
12 Lab 3: Density Functional Theory II    
13 Molecular Dynamics I Prof. Nicola Marzari Assignment 2 due
14 Molecular Dynamics II Prof. Nicola Marzari  
15 Molecular Dynamics III: First Principles Prof. Nicola Marzari  
16 Lab 4: Molecular Dynamics
SMA/Cambridge students off-line (no beaming)
  Assignment 3 due
17 Monte Carlo Simulations: Application to Lattice Models, Sampling Errors, Metastability Prof. Gerbrand Ceder  
18 Monte Carlo Simulation II and Free Energies Prof. Gerbrand Ceder  
19 Free Energies and Physical Coarse-Graining Prof. Gerbrand Ceder  
20 Model Hamiltonions Prof. Nicola Marzari Assignment 4 due
21 Lab 5: Monte Carlo Prof. Gerbrand Ceder  
22 Ab-Initio Thermodynamics and Structure Prediction Prof. Gerbrand Ceder  
23 Accelerated Molecular Dynamics, Kinetic Monte Carlo, and Inhomogeneous Spatial Coarse Graining Prof. Gerbrand Ceder  
24 Modeling in Industry Chris Wolverton, Ford Motor Company Assignment 5 due
25 Case Studies: High Pressure

Prof. Nicola Marzari

Prof. Gerbrand Ceder   Tell A Friend