Department of Chemistry · University College London
The acceleration of materials research is critical to the development of sustainable technologies for a carbon neutral future. The traditional approach to understanding energy materials is slow, labour intensive, and often produces results that are difficult to reproduce. This creates a huge challenge in using advances in machine learning to drive materials discovery, which relies on large, high quality datasets. We leverage technological advances in automation, hardware and software to build powerful, highly automated and open-source spectroscopic instruments. We then use these instruments to gain new insights into renewable energy conversion and storage, carbon neutral industry, and novel recycling technologies.