About this course
In this course, the student will get an introduction to Density Functional Theory (DFT) as one of the most used computational tools to study fundamental processes in materials for energy conversion and storage (batteries, nanocatalysts, fuel cells, photovoltaics, etc.). In the first half of the course, the students will learn the basics of the atomistic description of materials and electronic structure and the fundamentals of DFT. The second part is more practical. The students will first learn which properties can be calculated using DFT, how to bridge these quantities with the measured properties from experiments, and how to implement methodologies to automate and accelerate the design of novel materials. The course focuses on applying DFT through dedicated exercises, with limited technical details about the methodology used.
Expected learning outcomes
A student who has met the objectives of the course will be able to:
Describe the basics of computer simulations with a focus on Density Functional
Theory and the quantities that can be calculated Describe the physics behind key applications for energy materials
Interpret and adapt computer scripts for calculating physical properties of materials
Identify descriptors for an accelerated materials discovery approach
Create links between experimental results and simulations
Apply high-throughput techniques to a given data set to find novel materials
Perform atomic scale computer simulations of identified materials for energy applications
Identify problems and solutions related with computer simulations and materials discovery
Oral examination consisting of questions on the project report and course curriculum.
Basic concepts from physics and chemistry
The course is an e-learning course composed of lectures, exercises and a final project. Time for individual/group work is flexible.