nanoHUB-U: From Atoms to Materials: Predictive Theory and Simulations

A five-week course on the basic physics that govern materials at atomic scales.


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A five-week course on the basic physics that govern materials at atomic scales

This web-based course was developed by Purdue University Professor of Materials Engineering Alejandro Strachan to update his courses, lectures, and other materials posted on, a nanoscience and nanotechnology resource created by the Network for Computational Nanotechnology.

From Atoms to Materials: Predictive Theory and Simulations is a five-unit online course that develops a unified framework for understanding essential physics that govern materials at atomic scales and relate these processes to the macroscopic world. The course will cover important applications, trends, and directions. The course is taught at the level of a Purdue graduate course for first-year students, but there are no admission requirements and no need to travel to Purdue. The online course can be taken from anywhere in the world.

Scientific Overview Video

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Course Goals

This short course will teach the basic physics that govern materials at atomic scales and relate these processes to the macroscopic world. Students will use online simulations on to enhance the learning of density functional theory and molecular dynamics.

Who Should Take the Course

Anyone interested in learning the fundamental science of materials and understanding work on atomic or electronic structure calculations. The course will be useful for advanced undergraduates, beginning graduate students, as well are researchers and practicing engineers and scientists. The goal is to provide a simple, accessible, but sound introduction to the fundamental science of materials.


This course is intended to be broadly accessible to those with a background in the physical sciences or engineering. A background in college-level calculus and algebra is expected. An introductory-level background in physics and chemistry, including classical mechanics, chemistry, and thermodynamics is expected.

Course Outline

Preview the lectures below, or join the course by clicking the yellow button on the right and entering your nanoHUB login information!

Week 1: Quantum Mechanics and Electronic Structure

  • L1.1: – Course Overview
  • L1.2: – Why Quantum Mechanics?
  • L1.3: – Basic Quantum Mechanics of Electronic Structure
  • L1.4: – Quantum Well, Quantization, and Optical Processes
  • L1.5: – The Hydrogen Atom
  • L1.6: – Excited States of Hydrogen and Multi-Electron Atoms

Week 2: Electronic Structure and Bonding of Molecules and Crystals

  • L2.1: – The Nature Chemical Bond
  • L2.2: – Structure of Simple Hydrides
  • L2.3: – Linear Combination of Atomic Orbitals
  • L2.4: – Electronic Structure of Crystals
  • L2.5: – Electronic Band Structures
  • L2.6: – Electronic Structure Review

Week 3: Dynamic of Atoms: Classical Mechanics and MD Simulations

  • L3.1: – What is Molecular Dynamics?
  • L3.2: – Interatomic Potentials for Molecular Materials: Covalent Interactions
  • L3.3: – Interatomic Potentials for Molecular Materials: Van Der Waals and Electrostatic Interactions
  • L3.4: – Potentials for Metals and Semiconductors
  • L3.5: – Normal Modes and Phonons
  • L3.6: – Final Examples and Review

Week 4: Connecting Atomic Processes to the Macroscopic World – Vibrations, Optical, and Dielectric Response, Thermo-mechanical Properties

  • L4.1: – Statistical Mechanics: Connecting the Micro and Macro Worlds
  • L4.2: – The Canonical Ensemble and Microscopic Definition of T
  • L4.3: – Statistical Mechanics of the Harmonic Solid
  • L4.4: – The Quantum Harmonic Solid
  • L4.5: – Isothermal and Isobaric MD Simulations
  • L4.6: – Quantum Statistical Mechanics of Electronics

Week 5: Case Studies

  • L5.1: – Ab Initio Electronic Structure Calculations
  • L5.2: – Hartree-Fock and Exchange Interaction
  • L5.3: – Density Functional Theory
  • L5.4: – Reactive Interatomic Potentials
  • L5.5: – Non-Equilibrium MD Simulation Example: Thermal Transport
  • L5.6: – Final Thoughts and Additional Resources

Course Resources

  • Prerecorded video lectures distilling the essential concepts into a concise, five-week module.
  • Full set of lecture notes (slides).
  • Homework exercises with solutions, MATLAB codes, and homework tutorials.
  • Online quizzes (ungraded) will be posted each Monday with the lectures.
  • A Final Exam is available near the end of the course. Once a student starts the test, the student will have two hours to complete it. Students may attempt the exam two times. The highest of the two scores will be used to calculate course average.
  • Students attaining a passing grade in the course (an average score of 70% or higher) are eligible to purchase a proof of completion certificate and/or continuing education credits (see below).
  • A account is required. Sign up for free now!

Registration, Recognition

Register for the new, free self-paced course starting July 1, 2013 at

Students have the chance to experience a Purdue University-level course and earn the opportunity to purchase a digitally signed proof of completion or CEUs from nanoHUB-U. To qualify, a student must attain an average score of 70% or higher. Depending on the course, a separate exam may be required to qualify.

nanoHUB-U is awarding digital badges to students who successfully complete courses. Digital badges are certifiable icons that represent academic achievements or skills smaller than a college degree. More information about digital badges is available:

Purdue News Badge Announcement
The New York Times Badge Coverage

Students looking for a more relaxed or self-paced learning experience and who are not interested in receiving a proof of completion can simply watch the lectures and take a few quizzes or exams as their time and interest permit.

Professor Alejandro Strachen

ALEJANDRO STRACHAN is professor of materials engineering at Purdue University and the deputy director of NNSA’s Center for the Prediction of Reliability, Integrity and Survivability of Microsystems. Prof. Strachan’s research focuses on the development of predictive atomistic and molecular simulation methodologies to describe materials from first principles, their application to problems of technological importance and quantification of associated uncertainties. Application areas of interest include: coupled electronic, thermal and mechanical processes in nano-electronics, MEMS and energy-conversion devices, thermo-mechanical response and chemistry of polymer composites, molecular solids and active materials including shape memory and high-energy density materials.

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