Introduction to atomic-scale modeling
MSE-305 / 2 credits
Teacher: Ceriotti Michele
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.
Simulation and modeling has become an integral part of the process of designing and optimizing materials for the most diverse applications. Truly predictive simulations, that can estimate the properties of materials before they have ever been synthesized, require atomistic resolution. This course provides an introduction to some of the techniques that underlie atomic-scale simulations of materials. With a strong hands-on component, based on interactive Jupyter notebooks, we will revisit, and see in a new light, several basic concepts on the nanometer-scale description of matter, and see a number of different modelling techniques in action, from molecular dynamics to atomic-scale machine learning.
Information, computation, communication
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
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
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.
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.
In the programs
- Semester: Spring
- Exam form: During the semester (summer session)
- Subject examined: Introduction to atomic-scale modeling
- Lecture: 2 Hour(s) per week x 14 weeks