Day, Graeme - University of Southampton

个人简介

Graeme is the author or co-author of over 150 publications, including 5 book chapters. He acts as Associate Editor for the Royal Society of Chemistry (RSC) flagship journal Chemical Science, and serves on the advisory board for the RSC’s journals Molecular Systems Design and Engineering and RSC Mechanochemistry, 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, and the 2023 RSC Corday-Morgan Prize for pioneering the development of computational methods for guiding the discovery of functional molecular crystals. 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 (2020-2027), combining predictive computational methods, automation of materials discovery and robotics. 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. 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

研究领域

crystal structure prediction materials discovery computational chemistry NMR crystallography energy landscapes 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.

近期论文

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Predictive crystallography at scale: mapping, validating, and learning from 1,000 crystal energy landscapes Christopher R. Taylor, Patrick W.V. Butler & Graeme M. Day, 2024, Faraday Discussions Computationally guided synthesis of a hierarchical [4[2 + 3] + 6] porous organic ‘cage of cages’ Qiang Zhu, Hang Qu, Gokay Avci, Roohollah Hafizi, Chengxi Zhao, Graeme M. Day, Kim E. Jelfs, Marc A. Little & Andrew I. Cooper, 2024, Nature Synthesis DOI: 10.1038/s44160-024-00531-7 Porous isoreticular non-metal organic frameworks Megan O'Shaughnessy, Joseph Glover, Roohollah Hafizi, Mounib Barhi, Rob Clowes, Samantha Y. Chong, Stephen P. Argent, Graeme M. Day & Andrew I. Cooper, 2024, Nature DOI: 10.1038/s41586-024-07353-9 Machine learned potentials by active learning from organic crystal structure prediction landscapes Patrick Walter Villers Butler, Roohollah Hafizi & Graeme M. Day, 2024, Journal of Physical Chemistry A, 128(5), 945–957 DOI: 10.1021/acs.jpca.3c07129 Exploring polymorphism: hydrochloride salts of pitolisant and analogues Jessica Patel, Zachary Leduc, Aaron Gabriel Nunez Avila, Joseph Glover, Kelin Wu, Yuxing Zhang, Jing Zhang, Xiaoting Zhai, Huize Jing, Alex M. Chen, Daniel Chartrand, Thierry Maris, Graeme M. Day & James D. Wuest, 2024, Crystal Growth & Design, 24(3), 1268-1283 DOI: 10.1021/acs.cgd.3c01245 Modular, multi-robot integration of laboratories: an autonomous workflow for solid-state chemistry Amy M. Lunt, Hatem Fakhruldeen, Gabriella Pizzuto, Louis Longley, Alexander White, Nicola Rankin, Rob Clowes, Ben Alston, Lucia Gigli, Graeme M. Day, Andrew I. Cooper & Samantha Y. Chong, 2023, Chemical Science DOI: 10.1039/D3SC06206F Pushing technique boundaries to probe conformational polymorphism Martin R. Ward, Christopher Taylor, Matthew T. Mulvee, Giulio I. Lampronti , Ana M. Belenguer, Jonathan Steed, Graeme M. Day & Iain D.H. Oswald, 2023, Crystal Growth & Design Crystal structure prediction of energetic materials Joseph Edward Arnold & Graeme M. Day, 2023, Crystal Growth & Design Reducing overprediction of molecular crystal structures via threshold clustering Patrick W. V. Butler & Graeme M. Day, 2023, Proceedings of the National Academy of Sciences, 120(23) DOI: 10.1073/pnas.2300516120 Experimental confirmation of a predicted porous hydrogen-bonded organic framework Caitlin E. Shields, Xue Wang, Thomas Fellowes, Rob Clowes, Linjiang Chen, Graeme M. Day, Anna G. Slater, John W. Ward, Marc A. Little & Andrew I. Cooper, 2023, Angewandte Chemie International Edition DOI: 10.1002/anie.202303167 SECTIONS Seeking rules governing mixed molecular crystallization Norbert M. Villeneuve, Joshua Thomas Dickman, Thierry Maris, Graeme M. Day & James D. Wuest, 2022, Crystal Growth & Design, 23(1), 273 - 288 DOI: 10.1021/acs.cgd.2c00992 Densest plane group packings of regular polygons Miloslav Torda, John Y. Goulermas, Vitaliy Kurlin & Graeme M. Day, 2022, Physical Review E, 106(5) DOI: 10.1103/PhysRevE.106.054603 Roles and opportunities for machine learning in organic molecular crystal structure prediction and its applications Rebecca Jane Clements, Joshua Thomas Dickman, Jay Johal, Jennifer Eleanor Martin, Joseph Glover & Graeme M. Day, 2022, MRS Bulletin Targeted design of porous materials without strong, directional interactions Megan O'Shaughnessy, Peter R Spackman, Marc A. Little, Luca Catalano, Alex James, Graeme M. Day & Andrew I. Cooper, 2022, Chemical Communications, 58(95), 13254-13257 DOI: 10.1039/D2CC04682B Global analysis of the energy landscapes of molecular crystal structures by applying the threshold algorithm Shiyue Yang & Graeme M. Day, 2022, Communications Chemistry, 5(1) DOI: 10.1038/s42004-022-00705-4 Analogy powered by prediction and structural invariants: computationally-led discovery of a mesoporous hydrogen-bonded organic cage crystal Qiang Zhu, Jay Johal, Dan E. Widdowson, Zhongfu Pang, Boyu Li, Christopher M. Kane, Vitaliy Kurlin, Graeme M. Day, Marc A. Little & Andrew I. Cooper, 2022, Journal of the American Chemical Society, 144(22), 9893-9901 DOI: 10.1021/jacs.2c02653 Surprising Chemistry of 6-Azidotetrazolo[5,1-a]phthalazine: What a purported natural product reveals about the polymorphism of explosives Aaron Gabriel Nunez Avila, Benoit Deschenes Simard, Joseph, Edward Arnold, Mathieu Morency, Daniel Chartrand, Thierry Maris, Gilles Berger, Graeme M. Day, Stephen Hanessian & James D. Wuest, 2022, The Journal of Organic Chemistry DOI: 10.1021/acs.joc.2c00369 De novo crystal structure determination from machine learned chemical shifts Martins Balodis, Manuel Cordova, Albert Hofstetter, Graeme M. Day & Lyndon Emsley, 2022, Journal of the American Chemical Society, 144(16), 7215-7223 DOI: 10.1021/jacs.1c13733 AI3SD Intern Project: Latent Space Encoding of Molecular Crystal Structures King Wong, Graeme M. Day, Samantha Kanza, Jeremy G. Frey & Victoria Hooper, 2021 DOI: 10.5258/SOTON/AI3SD0150 AI3SD Video: Skills4Scientists - Poster & Careers Symposium - Poster Compilation Jeremy G. Frey, Samantha Kanza, Nicola Knight, András Vekassy, Aspen Fenzl, Erhan Gulsen, Hewan Zewdu, Jamie Longio, Maximilian Hoffman, Rhyan Barrett, Rubaiyat Khondaker, Anna Catton, Hongyang Dong, Kevin Calvache, Kaylee Patel, King Wong, Louis Greenhalgh, Rebecca, Jane Clements, Thomas Allam, Sarah Scripps, Gavin Man, Samuel Munday, Michael Blakey, Graeme M. Day, Chris-Kriton Skylaris, Simon J. Coles, Stephen Gow & William Brocklesby, 2021 DOI: 10.5258/SOTON/P0158 Accelerating computational discovery of porous solids through improved navigation of energy structure function maps Edward O. Pyzer-Knapp, Linjiang Chen, Graeme M. Day & Andrew I. Cooper, 2021, Science Advances, 7(33) DOI: 10.1126/sciadv.abi4763 Inherent ethyl acetate selectivity in a trianglimine molecular solid Donglin He, Chengxi Zhao, Linjiang Chen, M.A. Little, Samantha Y. Chong, Rob Clowes, McKie Katherine, Roper Mark G., Graeme M. Day, Ming Liu & Andrew I. Cooper, 2021, Chemistry - A European Journal, 27(41), 10589-10594 DOI: 10.1002/chem.202101510 AI3SD Video: Accelerating structure prediction models for materials discovery Graeme M. Day, Samantha Kanza, Jeremy G. Frey, Mahesan Niranjan & Victoria Hooper, 2021 DOI: 10.5258/SOTON/P0074 Exploration and optimization in crystal structure prediction: combining basin hopping with quasi-random sampling Shiyue Yang & Graeme M. Day, 2021, Journal of Chemical Theory and Computation, 17(3), 1988-1999 DOI: 10.1021/acs.jctc.0c01101 Minimizing polymorphic risk through cooperative computational and experimental exploration Christopher Taylor, Matthew T. Mulvee, Domonkos S. Perenyi, Michael R. Probert, Graeme M. Day & Jonathan Steed, 2020, Journal of the American Chemical Society, 142(39), 16668-16680 DOI: 10.1021/jacs.0c06749 Multi-fidelity statistical machine learning for molecular crystal structure predictionOlga Egorova, Roohollah Hafizi, David Woods & Graeme M. Day, 2020, Journal of Physical Chemistry A, 124(39), 8065-8078 DOI: 10.1021/acs.jpca.0c05006 An expandable hydrogen-bonded organic framework characterized by three-dimensional electron diffraction Peng Cui, Erik Svensson Grape, Peter Spackman, Yue Wu, Rob Clowes, Graeme M. Day, A. Ken Inge, Marc A. Little & Andrew I Cooper, 2020, Journal of the American Chemical Society, 142(29), 12743-12750 DOI: 10.1021/jacs.0c04885 Crystal structure determination of an elusive methanol solvate - hydrate of catechin using crystal structure prediction and NMR crystallography Marta Dudek, Piotr Paluch, Justyna Sniechowska, Karol P. Nartowski, Graeme M. Day & Marek J. Potrzebowski, 2020, CrystEngComm, 22(30), 4969-4981 DOI: 10.1039/d0ce00452a Structure prediction of crystals, surfaces and nano-particles Scott M. Woodley, Graeme M. Day & C.R.A. Catlow, 2020, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 378(2186) DOI: 10.1098/rsta.2019.0600 Combining forces: complementary techniques brought together to determine tricky crystal structures Graeme M. Day, 2020, Acta Crystallographica Section B: Structural Science, 76(3), 294-295 DOI: 10.1107/S2052520620007283