The project is in connection with a new initiative on Autonomous Materials Discovery (AiMade) in the Department of Energy Conversion and Storage (DTU Energy).AiMade is a four-year cross disciplinary project that is focused on establishing a platform for accelerated, autonomous materials discovery of clean energy materials through creation of a common data infrastructure and holistic ontology for materials data, and connecting data and information from simulations, characterization, synthesis and testing spanning multiple time and length scales.
The project focuses on machine learning directed reaction optimization and development of an automated synthesis set-up for synthesis of (primarily) organic energy materials. This is a highly interdisciplinary project carried out in the context of the department competence initiative AiMADE and falls within the combined expertise of several sections within the department (ASC, ELE, EMA, ISA). The scientific focus lies on integration of on-line spectroscopic analysis equipment in automated organic synthesis set-ups (e.g. with a computer controlled multi-channel flow synthesis set-up available at DTU Energy). Machine learning algorithms will then be applied for reaction optimization with the automated organic synthesis set-up. Work towards integration of this intelligent synthesis robot / reaction optimizer with computational screening and prediction tools and more advanced product isolation/purification steps will be undertaken.