Computer-Accelerated Design of Materials

We are a research group at Imperial College London working at the intersection of quantum chemistry, machine learning, and materials science. We use high-performance computing to design and optimise materials from first principles to function. Our work spans atomistic simulations, data-driven modelling, and multi-scale theory.

The group is led by Professor Aron Walsh and is part of the Thomas Young Centre and the Centre for Processable Electronics.

Materials design concept showing the intersection of chemistry, physics, and machine learning

Research Themes

Fundamentals

Inverse materials design with artificial intelligence
Thermodynamics and phase transitions in crystals
Ion, electron, and phonon transport in solids

Applications

Crystal engineering for clean energy technologies
Light–matter interactions in solar cells
Electrochemical systems for energy storage and conversion

Materials

Metal oxide semiconductors (e.g. In₂O₃, BiVO₄)
Halide perovskites (e.g. CH₃NH₃PbI₃, Cs₃Bi₂Br₉)
Multi-component chalcogenides (e.g. Cu₂ZnSnS₄, AgBiS₂)
Electroactive metal-organic frameworks (e.g. Fe₂(DSBDC), Cu₃(HHTP)₂)

Community Projects

Open computational materials science Nature Materials
Best practices in machine learning for chemistry Nature Chemistry
Emerging inorganic solar cell efficiency tables J Phys Energy
Stability assessment and reporting for perovskite photovoltaics Nature Energy

Open Positions

For postdoctoral candidates, the next call for Newton International Fellowships will be in early 2026.
For PhD candidates, the best time to get in touch with your CV and motivation is in October-December for admission in the following academic year.

Contact

If you are interested in collaborating or joining the group, please get in touch by e-mail.