Atomistic Simulation of Nuclear Materials
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1 BEAR Launch th June 2013 Atomistic Simulation of Nuclear Materials Dr Mark S D Read School of Chemistry Nuclear Education and Research Centre
2 Birmingham Centre for Nuclear Education and Research College of Engineering and Physical Sciences Chemistry Physics and Astronomy Metallurgy and Materials
3 Modelling: Importance to Nuclear Industry Atomistic Simulation: Materials Challenges Current Fission Reactors: Nuclear Fuel Performance and ageing phenomena prediction. UO 2 / MOX / Thoria(?) Radiation damage High Level Waste Encapsulation and Immobilization Predicting solution of interstitials and radioactive dopant ions. Predicting stability of ions and migration energies to surfaces/grain boundaries and radiation damage of host matrix Future Fusion Reactors: New materials Able to withstand higher temperature and neutron fluxes
4 Research Interests Fuel Performance Nuclear Waste Sensors Behaviour under irradiation Safe, controlled and predictable heat source Calculate intrinsic /extrinsic defect energies to predict transport of species to grain boundaries and fuel-clad gap. Modelling of fission gas bubbles Safe and Secure immobilization of high level radioactive waste in a form suitable for final disposal Simulations predict properties of candidate ceramic compositions as host matrices, tolerance to radiation damage and radionuclide transport characteristics Predicting formation energies of defects causing optical response Fundamental understanding of neutron radiation induced lattice effects Relate to mode of operation of sensor
5 Application and Relevance Overview Modelling augments experimental characterization NOT replace it! Can be thought of as an additional analytical technique. D8 Mott Littleton! 900 MHz, 21.2 T NMR
6 Time Scale Modelling scales and regimes Finite Element Analysis ms Mesoscale µs Atomistic Simulation Molecular Dynamics ns ps Quantum Mechanical Molecular Mechanics Å nm µm mm Size Domain
7 Nuclear Fuel Ceramic Fuels Advanced Gas Reactor (AGR) Moderator: Graphite Pressurized Water Reactor (PWR) Moderator: light water H 2 O Fuel: UO 2 with 2.5% 235 U enrichment Coolant: CO 2 (very weak moderator ) A second-generation UK-designed nuclear reactor employing vertical fuel channel design
8 Simulation of Uranium Dioxide Simulation of the bulk lattice Need to describe interatomic forces
9 Potential Models Simulation Methodology Atomistic approach to modelling crystal structure and properties involves: Interatomic potential functions simulating the forces acting between ions. Interatomic pair potentials can be written as: Coulombic Term Short range interactions attributed to the repulsion between electron charge clouds, van der Waals attraction Classical Born model framework of ionic interactions: A, ρ and C are variable parameters Empirically fitted to experiment Shell Model (polarization)
10 Empirical Fitting of U O Potential Employing GULP to Fit Parameters Simultaneously Parameter Type Parameter Original Buckingham A Buckingham rho Spring k Parameter Type Parameter Final Buckingham A Buckingham rho Spring k Crystal Structure GULP Elastic Constants cell fractional U core O core U shel O shel space 225 Dielectric Constants Type Observable Weight Elastic Const Elastic Const Elastic Const High Freq DiC Static Di C
11 Parametric Study U - O C set to 0 A and r varied. Solutions for d = 0 identified by red diamonds.
![Extended [a]](/docs-images/94/118058138/images/12-7.jpg "P. Millet,")
12 Programme Drivers and Strategy Robust Simulation of Actinide Oxide Atomistic Regime Robust description of Bulk Lattice Surfaces Nanoparticles Surface defects Extended defects [a] P. Millet, Computational Materials Science 53 (2012) 31 36
13 Higher Order Surfaces # Lowest energy shift per Miller Index # index h k l Surface_Energy <4-55> Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index Index
14 The value of the quartz is drastically increased by the presence of a relative small number of Fe 3+ ions! Quartz, SiO 2 doped with Fe 3+ ions from Fe 2 O 3.
15 Willis Cluster // O i U O Cluster Energy = ev Binding Energy = ev
16 Cluster Defects Investigating the Defect Chemistry Schottky Clusters 2 3 Second Oxygen Vacancy at 3 equivalent positions! 1 Second Oxygen Vacancy at position: Position Cluster Energy ev / Defect Binding Energy ev / Defect
17 Simulating MOX fuel MOX 25% (U 0.75 Pu 0.25 O 2 ) Mean Field Approach Supercell U 4+ Pu 4+ Ionic radius = 0.97 Å Ionic radius = 0.93 Å
18 Intrinsic disorder Cerium brannerite Schottky Vacancy M.C. Stennett, C.L. Freeman, A.S. Gandy, N.C. Hyatt, Journal of Solid State Chemistry 192 (2012)
19 Modelling Radiation Damage Unstable Pu nucleus within MOX fuel decays principally by a decay U range 12 nm a range 10 µm U 86 kev Recoil nucleus Pu a e - e - 5 MeV a particle He Cascade size 0.8 nm 256 Frenkel Pairs Cascade size 7.5 nm 2550 Frenkel Pairs
20 HPC Resource Birmingham Environment for Academic Research Blue BEAR Theoretical peak performance of the compute nodes = 848 (cores) * 2.2 (GHz) * 8 (floating point operations/cycle) = 15 TFlop/s 150 TB of user disc space with a sophisticated cluster filesystem. HPC service was completely replaced in December currently based an on an IBM idataplex HPC cluster with 800 Sandy Bridge based compute cores and other facilities such as large memory servers and a GPU-assisted compute node
21 HPC Resource MidPlus Regional HPC Centre A centre of excellence for computational science, engineering and mathematics Easy access to e-infrastructure, research and collaboration for business MidPlus is a collaborative partnership between four of the UK s leading universities: University of Warwick University of Birmingham University of Nottingham Queen Mary, University of London. Partnership brings together academic expertise and leading-edge facilities for computing capability and capacity, with an aim to facilitate the rapid realisation of modern computational research methods for business and industry. This regional HPC centre complements the BEAR facilities and adds additional resources for demands that cannot be met locally.
22 HPC Resource
23 Collaborators Acknowledgements Dr Rob Jackson Prof. Steve Parker (METADISE) Prof. Richard Catlow FRS Birmingham Environment for Academic Research
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