An efficient self-learning method for discovering new energy materials

Research Project, 2025 – 2027

In this project we will utilize AI and materials informatics to identify new materials for chemical looping technologies. Our approach will use advanced evaluation techniques, data mining, and generative machine learning models to create an active learning cycle that discovers new materials with superior properties. This will help establish chemical looping as the technology for sustainable energy systems. Our conjecture is that the new methodology will be highly generic and could be applied also for development of sustainable materials for other energy conversion systems.