Working on the ERC project ADAM (Autonomous Discovery of Advanced Materials) "Active Learning for Computational Polymorph Landscape Analysis", a collaboration with Prof. Andrew Cooper (Liverpool) and Prof. Dr. Kerstin Thurow (Rostock).

Currently working on the EPSRC funded Programme Grant "Digital navigation of chemical space for function", a collaboration with Liverpool and Imperial College London.

Currently working on the EPSRC funded project "A Supramolecular Gel Phase Crystallisation Strategy", a collaboration with Prof. Jon Steed (Durham).

Developing crystal structure prediction methodologies, and applications to polymorph screening of pharmaceutical molecules.

Previously working on the ERC ANGLE project developing crystal structure prediction of multi-component materials.

Working on the ERC project ADAM (Autonomous Discovery of Advanced Materials) "Active Learning for Computational Polymorph Landscape Analysis", a collaboration with Prof. Andrew Cooper (Liverpool) and Prof. Dr. Kerstin Thurow (Rostock).

Working on the ERC project ADAM (Autonomous Discovery of Advanced Materials) "Active Learning for Computational Polymorph Landscape Analysis", a collaboration with Prof. Andrew Cooper (Liverpool) and Prof. Dr. Kerstin Thurow (Rostock).

Developing computational methods for characterising crystal energy landscapes

Funded by a University of Southampton Presidential Scholarship

Incorporating crystal structure prediction into molecular discovery.

Working on the ERC project ADAM (Autonomous Discovery of Advanced Materials) "Active Learning for Computational Polymorph Landscape Analysis", a collaboration with Prof. Andrew Cooper (Liverpool) and Prof. Dr. Kerstin Thurow (Rostock).

The Generalised Convex Hull for the Identification of Synthesisable Predicted Materials

Funder by the Leverhulme Research Centre for Functional Materials Design. co-supervised by Prof. Michele Ceriotti (EPFL)

IComputational Modelling of Crystal Sponges

co-supervised by Prof. Simon Coles, in collaboration with Merck

Computational screening and structure prediction of energetic materials

Funded by the Air Force Office of Scientific Research.

Crystal Structure Prediction: Predicting Synthesizable Polymorphs

Funded by an EPSRC Industrial CASE studentship with Johnson Matthey.

Machine learning models for crystal structure prediction

Funded by the EPSRC Centre for Doctoral Training in Next Generation Computational Modelling

Including synthesisability measures in computer-guided materials discovery

School of Chemistry funded studentship and teaching assistantship

Developing evolutionary methods for the design of molecular materials.

Funded by the Centre for Doctoral Training in Theory and Modelling in Chemical Sciences.

publications:

Evolutionary chemical space exploration for functional materials: computational organic semiconductor discovery, Chi Y. Cheng, Josh E. Campbell and Graeme M. Day, Chemical Science, 11, 4922-4933 (2020)

Developing advanced methods for global exploration of lattice energy surfaces.

Funded by the Chinese Scholarship Council.

publications:

Exploration and optimization in crystal structure prediction: combining basin hopping with quasi-random sampling, Shiyue Yang and Graeme M. Day, J. Chem. Theory Comput., (2021) 17, 3, 1988-1999.

Global analysis of crystal energy landscapes: applying the threshold algorithm to molecular crystal structures, Shiyue Yang and Graeme M. Day, ChemRXiv.

Developing methods to predict the formation of crystalline hydrates.

Part of the Centre for Doctoral Training in Theory and Modelling in Chemical Sciences. Funded by Pfizer and the Cambridge Crystallographic Data Centre.