Computational Nanoscience

This course will provide students with the fundamentals of computational problem-solving techniques that are used to understand and predict properties of nanoscale systems. Emphasis will be placed on how to use simulations effectively, intelligently, and cohesively to predict properties that occur at the nanoscale for real systems. The course is designed to present a broad overview of computational nanoscience and is therefore suitable for both experimental and theoretical researchers.
Specific examples of topics the course will cover are:

1. The central ideas behind a wide range of nanomaterials simulations methods
2. How to break down a nanoscale problem into its “simulatable” constituents, and then piece it back together
3. How to simulate the same thing in two different ways
4. How to know what you’re doing and why thinking is still important
5. The importance of connecting simulation directly with experiment
6. What to do with all of that data, and how to judge its accuracy and validity
7. Why the “multi-scale” modeling picture is critically important and also nonsense

While some aspects of the simulation methods such as numerical algorithms will be presented, there will be little if any programming required. Rather, we will emphasize the intelligent application (as opposed to “black box” use) of codes and methods, and the connection between the computer results and the physical properties of the problem.