AI3SD Intern Project: Latent Space Encoding of Molecular Crystal Structures

Published date: 25 September 2021

Additional Information: King Wong: Hi everyone, this is Alex Wong, a second year Chemistry student from Southampton. The main thing I want to take out from this opportunity is to learn how to utilize machine learning to help and synthesize realistic crystal structure data and look at various of arrangement of molecules and interactions between them.   As a newbie in computational world, I am very much looking forward to developing my programming skills to push on various chemical problems and help to discover new materials to help the human nature in some sense in my future which will be a big jump from what I am doing in the university currently.   Furthermore, it will be my first time to carry out research and making proper report from the findings. I hope I can get a grip of it and find out whether I am suitable for computational research or not in order to pursue my career in the future. Graeme Day: Professor Graeme Day joined the University of Southampton in 2012. As a member of the Computational Systems Chemistry research group, his research develops computational methods for materials discovery and prediction of the crystal structures. Graeme Day received his BSc in Chemistry, Mathematics and Computing Science from Saint Mary's University, Halifax, Canada, after which he studied for an MSc in Theoretical Chemistry from the University of Oxford and obtained his PhD in 2003 from University College London. He then moved to the University of Cambridge for postdoctoral work and was awarded a Royal Society University Research Fellowship in 2005, which he held in Cambridge until 2012. In 2012 he moved to the University of Southampton as a Reader and was promoted to Professor of Chemical Modelling in 2014. His research concerns the development of computational methods for modelling the organic molecular solid state. A key focus of this work is the prediction of crystal structures from first principles; his research group applies these methods in a range of applications, including pharmaceutical solid form screening, NMR crystallography and computer-guided discovery of functional materials. Graeme is the author or co-author of over 125 publications, including 5 book chapters. He serves on the advisory board for the Royal Society of Chemistry’s journal Molecular Systems Design and Engineering, is on the steering committee of the UK Materials Chemistry High End Computing Consortium and is a member of the EPSRC peer review college. Graeme was awarded the CCDC Chemical Crystallography Prize for Younger Scientists in 2006 and the Molecular Graphics & Modelling Society, Silver Jubilee Prize in 2008, both for his contributions to crystal structure prediction methodologies. His current research is funded by the Engineering and Physical Sciences Research Council (EPSRC), the European Research Council (ERC) and a range of industrial collaborations. He leads the ERC Synergy Grant ADAM – Autonomous Discovery of Advanced Materials, which started in 2020, combining predictive computational methods, automation of materials discovery and robotics. BSc, Chemistry, Mathematics and Computing Science, Saint Mary's University, Halifax, Canada, 1996 MSc, Theoretical Chemistry, University of Oxford, 1997 PhD, University College London, 2003

Local EPrints ID: 452289

URI: http://eprints.soton.ac.uk/id/eprint/452289

DOI: doi:10.5258/SOTON/AI3SD0150

PURE UUID: 3ad800c2-c6b9-4bda-b1ad-3ddafa71ab56

ORCID for Graeme M. Day: orcid.org/0000-0001-8396-2771

ORCID for Samantha Kanza: orcid.org/0000-0002-4831-9489

ORCID for Jeremy G. Frey: orcid.org/0000-0003-0842-4302

Date deposited: 03 Dec 2021 17:30

Last modified: 17 Mar 2024 03:51