Materials Discovery and Materials Modelling

Queen Mary has a long standing, world-leading track record in Materials Science with over 50 academics working in this field across areas including materials for electronics and communications, sustainable energy, transport technologies, and materials chemistry and physics. This includes both wet lab experimental approaches as well as expertise in AI, machine learning and computational modelling. 

Examples of QM staff working in this field:  

• Prof Yang Hao is a Fellow of the Royal Academy of Engineering working on Antennas and Electromagnetics and with expertise in AI-based materials discovery, transformation optics and machine learning.  

• Prof James Busfield is a Fellow of the Royal Academy of Engineering and leads the soft matter group with extensive industry collaborations. His research includes both experimental and computational modelling. 

• Dr Chinnapat Panwisawas is a Senior Lecturer in Materials and Solid Mechanics working in the area of digital technology using AI-physics modelling framework for manufacturing, sustainable energy, and future transport. 

• Dr Alston Misquita leads a Marie Skłodowska–Curie Actions Doctoral Network on molecular simulations, quantum chemistry, crystal structure prediction, intermolecular modelling, spectroscopy, machine-learning, and nano-clusters. 

• Dr Devis Di Tommaso works on the development and application of computational chemistry methods, including machine learning, on topic related to CO2 conversion, value-added chemicals, and materials. 

• Prof Joe Briscoe is an ERC grantee with experimental and computational research to develop next generation energy devices including photovoltaics, photocatalysis and energy harvesting using piezoelectric and ferroelectric materials. 

Research Centres:  
Centre for Experimental and Applied Physics; Centre for Intelligent Transport; Centre for Sustainable Engineering; Centre for Electronics