The Adsorption and Advanced Materials group is part of the Department of ChemicalEngineering & Biotechnology at the University of Cambridge.
Our research concerns the study of the molecular mechanisms that control adsorption processes in porous materials. We are particularly interested in drug delivery systems, where nanotechnology has a fundamental impact to revolutionise cancer diagnosis and therapy. We are also interested in the use of novel porous materials for the necessary shift from today’s fossil-based energy economy to a more sustainable economy based on hydrogen and renewable energy, linked to the carbon capture to mitigate the effects of global warming. Our objective is to evaluate new strategies in the study of adsorption processes, the study and design of new porous materials such as metal-organic frameworks (MOFs) and to develop new methods in the prediction of their performance.
The huge development of computational power allow us to use computational simulation, such as grand canonical Monte Carlo (GCMC) and molecular dynamics (MD), and machine learning to design new materials. Nowadays, we run high-throughput screening (HTS) in databases with thousands of materials to find optimal ones for specific applications. Using big data analysis, we can understand how materials properties affect their final performance, whereas using machine learning we can recognise these relationships and discover hidden insights, extrapolating the behaviour towards optimal systems. Once an optimal material is identified, we experimentally engineer and adapt it to real world and final applications. Our lab’s research covers the whole process, where our team is roughly divided in three main themes: i) data mining for performance’s prediction; ii) engineering of systems for gas adsorption/separation; iii) nanomaterials for drug delivery.