Symposium

Theory and Modelling progress for energy materials Symposium

***Symposium recording here***

14:00 - 14:45 - Professor Peter Littlewood, The University of Chicago

Metal-insulator transitions in elastic media

14:45 - 14:50 discussion

14:50 - 14:55 break

14:55 - 15:20 - Professor Chris Pickard, University of Cambridge

Random search - a tool to explore energy materials

15:20 - 15:25 - Discussion

15:25 - 15:55 - Professor Gabor Csanyi, University of Cambridge

Machine learned force fields and potential energy surfaces

15:55 - 16:00 - Discussion

16:00 - 16:10 - Break

16:10 - 16:40 - Dr Jarvist Frost, Imperial College London

Large polarons with the Feynman theory: mobility, defect scattering and vibrational response

16:40 - 16:45 - Discussion

16:45 - 17:15 - Arrival Ltd / Happy Electron Ltd

17:15 - 17:20 Discussion

Thursday 15 October 2020
Time: 2-6pm
Venue: Join Zoom Meeting
https://ucl.zoom.us/j/98285707119?pwd=RDJRaWR0Y3VTaDhsTUpWTmFscHcyUT09

Meeting ID: 982 8570 7119
Passcode: TYCSymp
Contact: Dr Cedric Weber

Professor Peter Littlewood holds a BA and PhD in Physics from the University of Cambridge.  He was a member of technical staff, and later Head of the Theoretical Physics research group at Bell Laboratories in New Jersey.  He moved to Cambridge in 1997 as Head of the Theory of Condensed Matter group, and later became Head of the Cavendish Laboratory and Department of Physics.  He came to the University of Chicago in 2011 as Associate Lab Director and then Lab Director at Argonne National Laboratory, returning full time to the University in 2017.  He serves on the advisory boards of several institutes, including the Faraday Institute, Simons Foundation, Paul Scherer Institute, Carnegie Institute for Science and the Max Planck Institutes at Halle and Hamburg.

Professor Chris Pickard is the inaugural Sir Alan Cottrell Professor of Materials Science in the Department of Materials Science and Metallurgy, University of Cambridge.  Previously he was Professor of Physics at University College London (2009-2015), and Reader in Physics at the University of St. Andrews (2006-2008).  He has held both EPSRC Advanced and Leadership Research Fellowships and is currently a Royal Society Wolfson Research Merit Award holder (2015).  He is lead developer of the widely used CASTEP code, and introduced both the GIPAW approach to the prediction of magnetic resonance parameters and Ab Initio Random Structure Searching (AIRSS).  In 2015 he won the Rayleigh Medal and Prize of the Institute of Physics.

Professor Gabor Csånyi's expertise is in atomistic simulation, particularly in multi-scale modelling that couples quantum mechanics to larger length scales.  He is currently engaged in applying machine learning techniques to materials modelling problems e.g. deriving force fields (interatomic potentials) from ab initio data.  Prof. Csånyi's interests include statistical problems in molecular dynamics, e.g. in enhanced sampling algorithms that can be used to explore the atomistic configuration space of materials and molecules.

Dr Jarvist Moore Frost has been a Royals Society University Research Fellow in the Department of Physics at Imperial College London since October 2019.  Prior to this he worked as a research scientist at a Machine-Learning drug discovery startup company GTN.ai Ltd.  As a postdoc in the group of Aron Walsh he worked on explaining the unusual properties of the new hybrid  lead halide perovskite class of semiconductors.  Immediately after his PhD he was seconded to Flexink Ltd. under the EPSRC Knowledge Transfer scheme, applying the computational sift methods developed during his PhD for the discovery of new Donor-Acceptor copolymer organic semiconductors.  His PhD under Prof. Jenny Nelson and Pro. Donal Bradley (Imperial 2012) was on developing methods to simulate charge carrier transport in organic semiconductors.  Most of his work has been at the join of experiment and theory, providing modelling and explanation of structure: property relationships in new classes of semiconductors proposed for large-scale renewabe energy applications.

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