The research focus of the TCDC theme encompasses all areas of modern chemistry, including computational chemistry and modelling; theoretical chemistry and data-driven approaches to chemistry, including machine learning and AI. Computational chemistry and modelling in the theme cuts across different areas such as the design and study of catalysts and small molecules, modelling electrochemical processes, predicting and designing properties of new materials and studying the structure and function of biomolecules. A wide range of computational methods and software are being developed from quantum mechanical approaches to molecular dynamics and non-equilibrium computer simulations. Members of the theme are also actively involved in developing new theoretical approaches to rationalise and predict molecular structures and reactivity. A rapidly evolving area within the theme is the application of data-driven approaches to chemistry; some examples of this include the use of machine learning to predict reactions’ outcomes, application of unsupervised learning to biomolecular systems and artificial intelligence to predict properties of new materials. 

The coordinator for this theme is Prof. Kim Jelfs. For general enquiries about this theme please contact her at or feel free to contact any members of the theme listed below for more specific enquiries.



Academic staff

Dr. Francesco Aprile

Francesco Aprile

Dr. Francesco Aprile