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TERATEC 2017 Forum
Workshop 6 - Wednesday, June 28, from 14h00 to 17h30
Big Data for materials sciences

The NOMAD Laboratory and new data-based schemes for QM-accurate molecular dynamics
Alessandro DE VITA, Department of Physics, KING’S COLLEGE LONDON - Thomas Young Centre for Theory and Simulation of Materials and JCMaxwell-UK CECAM Node, UK - Department of Engineering and Architecture, University of Trieste, Italy

Abstract : I will describe the conception, structure and early achievements of the Novel Materials Discovery (NOMAD) Laboratory, a EC-funded Centre of Excellence developing a Materials Encyclopaedia and Big-Data Analytics and advanced graphics tools for materials science and engineering. The issue of data curation, from archiving to conversion with a flexible metadata structure, and the necessity of bespoke accurate parsing for all major software packages, have emerged as key issues in the first year of the CoE’s operation. An exciting aspect of the forthcoming work plan is the development of analytic tools to handle the data contained in the NOMAD Archive, either to identify previously unnoticed correlations between the database materials, or to boost existing modelling algorithms. As an example of the latter case, I will describe how Bayesian inference can be used to boost first-principles molecular dynamics, by means of machine-learning force fields based on appropriate Gaussian process kernel construction. Analysis reveals that the complexity associated with learning the atomic forces of a target physical system can be quantified, and if found so high that the “Big Enough Data” assumption is ruled out, extrapolation can still be avoided by online learning strategies that concentrate QM subroutine calls where/when “chemically novel” configurations are encountered along the system’s trajectory.

Biography : Alessandro has over twenty years experience in materials modelling, interdisciplinarily spanning over Physics and Materials Engineering, with a PhD in either discipline. During his career he has been working in various institutions, including the Universities of Keele, Oxford and Cambridge, the Swiss Federal Institute of Technology (EPFL) in Lausanne, and the University of Trieste. In 2010 he became Professor of Physics at King’s College London. He co-directs the Thomas Young London Centre for Theory and Simulation of Materials and director of the UK-JCMaxwell CECAM Node (partners: KCL, Imperial College, University College London, and the Universities of Oxford and Cambridge).  His research interests are centred on the development and application of atomistic modelling techniques involving massively parallel computing, dynamical database generation and machine learning. He uses these techniques to investigate materials’ chemo-mechanical properties such as their resistance to fracture and stress corrosion, as well as nanofabrication approaches such as supramolecular self-assembly. In the late 1990’s, he pioneered the “Learn On The Fly” (LOTF) multi-scale modelling scheme whose latest developments include on-the-fly force learning of first-principle forces from dynamically evolving databases using Bayesian techniques.

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Find the technical workshop of the previous edition of the Forum TERATEC dealing Materials Simulation and upload their presentations

Teratec 2016 Forum : High Performance Integrated Computational Materials Engineering

Teratec 2015 Forum : Big data, multiscale and materials

Teratec 2014 Forum : Material simulation: new materials, usage, and durability

Teratec 2013 Forum : Materials Simulation

For any other information regarding the workshops, please contact :

Jean-Pascal JEGU
Tel : +33 (0)9 70 65 02 10
jean-pascal.jegu@teratec.fr
Campus TERATEC
2, rue de la Piquetterie
91680 BRUYERES-LE-CHATEL
France


 
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