Make it simple but significant. We create simple models for complex molecular systems.

Computational Chemistry, multiscale modelling, and big data analytics constitute the common thread that connects our research areas. We apply Density Functional Theory (DFT), Molecular Dynamics (MD) simulations, and Coarse-Grained (CG) modelling to simulate the behaviour of molecules and complex materials from the nanoscale to the mesoscale. We simulate chemical reactivity, electron transport, mechanical properties, self-assembly and degradation mechanisms.

The large datasets that we generate are used for training Machine Learning (ML) algorithms that speed up property predictions, and molecular discovery. We performed HTC, and HPC simulations at Google Cloud Platform (GCP) and Supercomputing Wales (SCW), and we are part of the ‘AccelerateAI’ initiative, funded by the Welsh Government through a Sêr Cymru grant, in collaboration with Atos, NVIDIA Data Centre, and other research groups at Swansea University.

RESEARCH PROJECTS

ACCELERATED-AI: BIG DATA ANALYTICS OF CHEMICAL DATASETS FOR MACHINE LEARNING

REACTIVITY DESCRIPTORS FOR MATERIALS DEGRADATION AND POLYMERISATION

HIGH-THROUGHPUT GENERATION OF CHEMICAL STRUCTURES FOR ORGANIC SOLAR CELLS

COLLABORATORS

Adebayo Gboyega | Federal University of Agriculture, Abeokuta, Nigeria
Chi-Hua Yu | Cheng Kung University, Taiwan
James Ryan | Swansea University, UK
Jingjie Yeo | Cornell University, USA
Paul Meredith | Swansea University, UK
Rafael Gomez-Bombarelli | Massachusetts Institute of technology, USA
Stephan Irle | Oak Ridge National lab, USA

SUPPORT

BACK TO ALL RESEARCH AREAS