Powering Danish battery research with LUMI

The full article was originally published on DeiC website.

Researchers at DTU Energy, Manuel Dillenz and Jose Maria Castillo Robles, used LUMI to study how electrons move through battery materials at the atomic scale. By combining quantum mechanical simulations, molecular dynamics, and machine learning, they developed a workflow that enables accurate and efficient analysis of charge transport in lithium manganese oxide batteries.

LUMI’s CPU and GPU resources were essential for generating simulation data, training machine learning models, and running large-scale calculations. The project also benefited from support from the LUMI user support team, which helped adapt the workflow to LUMI’s AMD-based architecture.

Beyond this specific battery material, the researchers plan to make their workflows and machine learning models openly available, enabling other scientists to apply the approach to a wide range of battery research challenges.

Read the full article on the DeiC website: https://deic.dk/en/use-cases/battery-research-powered-lumi