Summary

This course provides an introduction to the modeling of matter at the atomic scale, using interactive jupyter notebooks to see several of the core concepts of materials science in action.

Content

Keywords

materials modeling

atomic-scale simulations

programming

python

numerical methods

Learning Prerequisites

Required courses

Information, computation, communication

Recommended courses

Materials structure

Numerical analysis

Important concepts to start the course

Basic python, some familiarity with jupyter notebooks

No need for QM or statistical mechanics

Some finite-elements and continuum modeling and numerical methods

Basic understanding of materials science: crystallography, defects, mechanical properties, thermodynamics, phase transitions

Learning Outcomes

By the end of the course, the student must be able to:

• Examine the code underlying a Jupyter notebook
• Sketch short code snippets to model materials properties
• Interpret the result of simulations in the light of core concepts in materials science

Teaching methods

The course is based on a set of interactive Jupyter notebooks, which guide the student in a step-by-step fashion into computing the numerical outcomes of a microscopic model of matter. The notebooks require a minimal amount of programming knowledge, and are executed in class by the students, under the guidance of the teacher.

Expected student activities

Students should go through the notebooks, experimenting with the effect of different parameters on the results of the models, writing short snippets of code, and reading the accompanying text that describes the underlying theory. They should then revise the content at home, and answer a couple of open questions that are then assessed as the course progresses.

Assessment methods

The students are assessed during the course, based on the answers they give to short open-ended questions that require commenting on the core concepts presented in each notebook.