AI opens new possibilities in materials science

Artificial Intelligence (AI) is rapidly becoming an essential tool in materials science — from discovering new solar materials to improving the analysis of biological systems. In late September, the Department of Materials Science and Engineering hosted a seminar to share knowledge, experiences, and inspiration among researchers.

“AI is here to stay,” said Professor Cecilia Persson from the Division of Biomedical Engineering, who opened the seminar.
Associate Professor Jens Sjölund, Division of Systems and Control at the Department of Information Technology, then introduced the fundamentals of machine learning. He highlighted the importance of large datasets and how AI enables researchers to tackle problems that were previously difficult or even impossible to solve.

Examples from ongoing research

The morning continued with presentations showing how AI is being applied in various research areas. Profssor Eric Berg, from Chemistry Ångström, presented work on AI in battery research, followed by two examples from the department illustrating the diversity of AI applications in materials science.

Detecting bubbles in microphysiological systems

Nadia Koriakina from the Division of Biomedical Engineering demonstrated how machine learning can be used to automatically detect bubbles in microphysiological systems — a critical task in many biomedical experiments.
Working with the EMBLA group, she aims to develop automated detection methods that can be used both during and after experiments as part of post-processing analysis.

Accelerating the discovery of solar absorber materials

Jonathan Scragg from the Division of Solar Cell Technology explained how AI is used to speed up the discovery of new inorganic materials for solar energy applications.
With BERTHA, a Self-Driving Lab for solar absorber development, researchers can automate and optimize experiments in real time — paving the way for faster advances in next-generation solar cells.

A field in transformation

The seminar highlighted how rapidly AI is transforming research in materials science — from automated data analysis to intelligent material discovery.
“Our goal is to inspire more researchers to integrate AI into their projects and to build a platform where we can learn from each other,” said Cecilia Persson.