Materials Design and Informatics Group
Department of Chemistry
University College London
London WC1H 0AJ
Materials Design and Informatics Group (MDIG) is a research collective, working to accelerate develoment of new green energy materials. We are based at UCL, in the Department of Chemistry.
We use a combination of data-driven methods (such as deep learning and Bayesian statistics) and quantum mechanics calculations to design new materials on computers and to help accelerate the experimental characterisation of materials. We work with other academics, national facilities and companies.
news
| Jul 20, 2026 | Congratulations to Joley for winning first prize in the poster competition at the TYC Conference. |
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| Feb 25, 2026 | New publication alert 2026 roadmap toward sustainable thermoelectrics |
| Feb 9, 2026 | Welcome to Prakriti who has joined the group as a Postdoctoral Fellow on an EPSRC grant designing new materials for green cooling. |
| Feb 5, 2026 | New publication alert Leveraging transfer learning for accurate estimation of ionic migration barriers in solids |
| Jan 30, 2026 | New publication alert Self-optimizing machine learning potential assisted automated workflow for highly efficient complex systems material design |
selected publications
- Computational screening of all stoichiometric inorganic materialsChem 2016
- Machine learning for molecular and materials scienceNature 2018
- Designing interfaces in energy materials applications with first-principles calculationsnpj Computational Materials 2019
- Distributed representations of atoms and materials for machine learningnpj Computational Materials 2022
- Entropy-based active learning of graph neural network surrogate models for materials propertiesThe Journal of Chemical Physics 2021
- Interpretable and explainable machine learning for materials science and chemistryAccounts of Materials Research 2022