During his PhD studies, Luuk Kempen researched how machine learning can be used to explore materials used to convert CO₂ into more useful products such as methanol. Specifically, inverse catalysts—metal oxide nanoparticles supported on metal surfaces—are investigated as they have shown very promising activity in laboratory experiments. By developing and applying machine learning methods, Luuk Kempen showed how this type of materials is structured at an atomic level. He further showed how a key intermediate in the conversion of CO₂, formate, is formed on these materials.

The new research methods and findings contribute to insights of these inverse catalysts on an atomic level, which can be used to further develop more performant materials for CO₂ conversion.

The PhD study was completed at Department of Physics and Astronomy, Faculty of Natural Sciences, Aarhus University.

This summary was prepared by the PhD student.

Time: Friday, 27 June 2025 at 10:00
Place: Building 1523, room 318, Fysisk Auditorium, Department of Physics and Astronomy, Aarhus University, Ny Munkegade 120, 8000 Aarhus C
Title of PhD thesis: Leveraging machine learning for materials discovery: Inverse catalysts for CO₂ hydrogenation
Contact information: Luuk Kempen, e-mail: luuk@phys.au.dk, tel.: +45 52558225
Members of the assessment committee:
Full Professor Henrik Grönbeck, Chemical Physics, Chalmers University of Technology, Sweden
Assoc. Prof. Dipl.-Ing. Dr.techn. Oliver T. Hofmann, Institut für Festkörperphysik, Graz University of Technology, Austria
Associate Professor Karsten Riisager (chair), Department of Physics and Astronomy, Aarhus University, Denmark
Main supervisor: Associate Professor Mie Andersen, Department of Physics and Astronomy, Aarhus University, Denmark
Language: The PhD dissertation will be defended in English.

The defence is public.
The PhD thesis is available for reading at the Graduate School of Natural Sciences/GSNS, Ny Munkegade 120, building 1521, 8000 Aarhus C