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X-WR-CALDESC:Events for THOMAS YOUNG CENTRE
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DTSTART;TZID=Europe/London:20220905T090000
DTEND;TZID=Europe/London:20220909T170000
DTSTAMP:20260412T123309
CREATED:20220516T094529Z
LAST-MODIFIED:20220609T145454Z
UID:2941-1662368400-1662742800@thomasyoungcentre.org
SUMMARY:Sargent Centre Summer School on Data-Driven Optimization
DESCRIPTION:Venue: Lecture Theatre 1\, ACE Extension\, South Kensington Campus\, Imperial College London \n\n\n\nTickets: £250 \n\n\n\nTo Register: Sargent Centre Summer School on Data-Driven Optimization | Events | Imperial College London \n\n\n\nThe Summer School will include tutorials and workshops by leading researchers on areas such as Reinforcement Learning\, Machine Learning\, Bayesian Optimisation\, Hybrid Modelling\, and other exciting topics. It will also allow participants to interact with speakers and peers to build a community around the topic and its applications.  The school is targeted at PhD students\, Postdocs and early career researchers in general.   \n\n\n\nThe summer school will be followed by a PSE@ResearchDay (9th of September)\, where the attendees will be able to present their work either in an oral presentation or poster format. The idea is that this will foster more interaction between participants and their research. This is of course optional but included with the Summer School. 
URL:https://thomasyoungcentre.org/event/summer-school-on-data-driven-optimization/
CATEGORIES:Main event
ATTACH;FMTTYPE=image/jpeg:https://thomasyoungcentre.org/wp-content/uploads/2022/05/CPSE-Centre-for-Process-Systems-Engineering.jpg
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BEGIN:VEVENT
DTSTART;TZID=Europe/London:20220919T090000
DTEND;TZID=Europe/London:20220923T180000
DTSTAMP:20260412T123309
CREATED:20220721T133654Z
LAST-MODIFIED:20220721T134016Z
UID:3124-1663578000-1663956000@thomasyoungcentre.org
SUMMARY:MSSC2022 - Ab initio Modelling in Solid State Chemistry
DESCRIPTION:MSSC2022 – Ab initio Modelling in Solid State Chemistry Share on X\n\n\n\n\nThe Department of Chemistry and the Thomas Young Centre at Imperial College London and the Theoretical Chemistry Group of the University of Torino\, in collaboration with the Computational Materials Science Group of the Science and TechnologyFacilities Council (STFC)\, are organising the 2022 MSSC Summer School on the “ab initio modelling of crystalline and defective solids with the CRYSTAL code”. \n\n\n\nThe MSSC2022 will be a virtual workshop\, the morning and the afternoon sessions will be run remotely. \n\n\n\nThe week long school is designed for new users of CRYSTAL\, PhD students\, Post-Docs and researchers with interests in solid state chemistry\, physics\, materials science\, surface science\, catalysis\, magnetism and nano-science. It will provide an introduction to the capabilities of quantum mechanical simulations and to the practical use of CRYSTAL. \n\n\n\nCRYSTAL is a general-purpose program for the study of periodic systems. It uses a local basis set comprised of Gaussian type functions and can be used to perform calculations at the Hartree-Fock\, density functional or global andrange-separated hybrid functionals (e.g. B3LYP\, HSE06)\, double hybrid levels of theory. \n\n\n\nAnalytical first derivatives with respect to the nuclear coordinates and cell parametersand analytical derivatives\, up to fourth order\, with respect to an applied electric field (CPHF/CPKS) are available. \n\n\n\nThe programme is available:https://www.imperial.ac.uk/mssc/mssc2022/programme/ \n\n\n\nYou can register at:https://www.imperial.ac.uk/mssc/mssc2022/registration/
URL:https://thomasyoungcentre.org/event/mssc2022-ab-initio-modelling-in-solid-state-chemistry/
CATEGORIES:Main event
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/London:20220921T140000
DTEND;TZID=Europe/London:20220921T160000
DTSTAMP:20260412T123309
CREATED:20220705T153353Z
LAST-MODIFIED:20221103T160656Z
UID:3039-1663768800-1663776000@thomasyoungcentre.org
SUMMARY:History (and future) of modelling materials using interatomic potentials
DESCRIPTION:Watch the recording here \n\n\n\n\n\n\n\n\nHistory (and future) of modelling materials using interatomic potentials Share on X\n\n\n\n\nInteratomic Potentials and modelling as a tool in materials science – Prof Sir Richard Catlow\, Dept. of Chemistry\, UCL; School of Chemistry\, Cardiff University; UK Catalysis Hub\, Research Complex at Harwell\, UKInteratomic potential models have played and continue to play a crucial role in in the application of simulation techniques to simulating and predicting the properties of complex real materials. We will review the development of the field and current trends\, including the growth of hybrid QM/MM and of ML based methods. We will show. how the use of modelling techniques especially in conjunction with a range of experimental methods can yield unique information on structures\, dynamics\, and mechanism in a range of functional inorganic materials. Our discussion will concentrate on the following topics and systems \n\n\n\n\nStructure modelling and prediction of inorganic materials;\n\n\n\nModelling of the structures and properties of oxide surfaces;\n\n\n\nModelling of defects in inorganic materials;\n\n\n\nModelling of nano-particles;\n\n\n\nModelling of active site structures and mechanisms of catalytic reactions.\n\n\n\n\nWe will discuss the prospects of the field in the light of developments in computer hardware\, methodologies and algorithms. \n\n\n\nInteratomic potentials: Basic historical developments\, with the Natural Intelligence of our brilliant predecessors – Prof Olivier Hardouin Duparc\, Institut Polytechnique de ParisAbstract: If one cannot use Schrödinger\, let alone Dirac\, for large sets of atoms\, one uses interatomic potentials. Interatomic potentials have been proposed ever since scientists know atoms exist and tend to gather\, without collapsing together. Attraction and repulsion\, first by pairs but also via many-body interactions when some electrons can be exchanged between atoms: I will propose a historical-pedagogical development of these ideas\, mainly focused on metals but not only (also semiconductors). \n\n\n\nInteratomic potentials for modelling the intermolecular forces between organic molecules\, pharmaceuticals and biomolecules – Prof Sally Price\, UCLAbstract: An accurate intermolecular potential should be able to predict all physical properties of a molecule in the solid\, liquid and gas. This was achieved for argon about half a century ago\, but it is arguable whether it has yet been achieved for water\, and certainly not in a form that can be used in standard molecular dynamics codes. For organic molecules\, the intermolecular potential is expressed in an atom-atom form. However\, the non-sphericity of atoms in molecules\, non-additive effects\, limited transferability and molecular flexibility may all limit the accuracy of atomistic modelling of the organic solid state for specific molecules\, such as pharmaceuticals.
URL:https://thomasyoungcentre.org/event/history-of-modelling-materials-using-interatomic-potentials/
CATEGORIES:Main event
ORGANIZER;CN="Martijn Zwijnenburg":MAILTO:m.zwijnenburg@ucl.ac.uk
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BEGIN:VEVENT
DTSTART;TZID=Europe/London:20220930T143000
DTEND;TZID=Europe/London:20220930T163000
DTSTAMP:20260412T123309
CREATED:20220706T125401Z
LAST-MODIFIED:20220929T163647Z
UID:3045-1664548200-1664555400@thomasyoungcentre.org
SUMMARY:Latest Developments in Density Functional Methodology Symposium
DESCRIPTION:River Room\, Strand campus\, King’s College London \n\n\n\n\n\n\n\n\nLatest developments in Density Functional Methodology symposium Share on X\n\n\n\n\nPushing the frontiers of density functional theory using machine learning – Aron Cohen\, Google DeepmindWe will highlight the use of machine learning to the exchange-correlation functional\, where numerous hand-crafted functional forms have already achieved great success in calculations throughout chemistry and physcis. In our recent DM21 functional (Kirkpatrick et al.\, Science 374\, 1385 (2021)) we illustrate a path to utilise the power of machine learning to this critical problem from creating accurate data that captures large parts of chemistry to addressing some of the hardest challenges of DFT.  \n\n\n\nSmooth(er) meta-generalised gradient approximation functionals: design and applications in condensed systems – Albert Bartok-Partay\, WarwickI will present our efforts to create a regularised SCAN functional which improves on the numerical instabilities of the original. Results and benchmarks will be discussed\, focussing on structural\, energetic and NMR properties of organic and inorganic crystals. \n\n\n\nThe ABC… of extended DFT – Andrew Teale\, University of NottinghamThe universal density functional is elegantly expressed in Lieb’s convex formulation of DFT\, giving access to the tools of convex analysis. When additional variables are introduced the universal density functional can become dependent on not only the charge density but also additional variables. An example is DFT in a magnetic field B expressed in terms of a vector potential A. In this case the functional depends additionally on the paramagnetic current density. Another example is orbtial-free DFT\, in which the functional depends on the charge density and the the chemical potential. The four-way correspondence of bivariate functionals is a useful tool to understand the density functionals in these contexts. Practical implementations and applications of current-DFT and orbital-DFT will be discussed.
URL:https://thomasyoungcentre.org/event/latest-developments-in-density-functional-methodology-symposium/
LOCATION:King’s College London
CATEGORIES:Main event
ATTACH;FMTTYPE=image/jpeg:https://thomasyoungcentre.org/wp-content/uploads/2021/06/iStock-864501518-cropped-e1623144008703.jpg
ORGANIZER;CN="George Booth":MAILTO:george.booth@kcl.ac.uk
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