SAMBA 2025 - Summer Academy for Modelling Batteries
DTU Department of Energy Conversion and Storage
The student should learn to describe and use modelling of battery materials and devices at different lengths and time scales.
Learning objectives:
A student who has met the objectives of the course will be able to:
- Describe the fundamental theory behind different modelling methods
- Understand uses and limitations of various models
- Be able to choose the appropriate method to tackle different problems and aspects of a battery
- Perform calculations using the codes provided during the course (ASE/GPAW, LAMMPS, Matlab and Python scripts, COMSOL Multiphysics, CLEASE)
- Explain limitations in battery technologies
- Explain how to link materials scales
- Engage with battery modelling experts
- Present your results in a concise report
Contents:
• Introduction to the modelling and simulation of rechargeable batteries. • Porous electrode theories, materials, structure, function, and operation. • Density Functional Theory approaches. • Cluster expansion. • Kinetic Monte Carlo approaches. • Molecular Dynamics approaches. • Continuum modelling. • Multi-scale modelling. • Machine Learning methods. • Application to lithium and sodium chemistries (-ion, air, and sulfur) and redox flow batteries: intercalation and conversion materials, electrolytes, transport, electrochemical processes, ageing, and fabrication processes. • Access to specific software (freeware and in-house) will be provided.