Bath; Birkbeck; Cambridge; CCLRC Daresbury Reading The Royal Institution University College London (UCL) eMinerals one of NERCs eScience testbed projects The eMinerals team: Environmental scientists; Chemists; Physicists; Computational and Grid scientists. PI: Martin Dove Web: eMinerals: Science Outcomes enabled by new Grid Tools Maria Alfredsson Nottingham 21/9/2005

eMinerals one of NERCs eScience testbed projects Research undertaken by: Bath group: A.Marmier, D.J. Cooke, S.C. Parker Birkbeck group: Z. Du and N.H. de Leeuw Cambridge group: K. Trachenko, E. Artacho, J.M Pruneda, M.T. Dove Daresbury group: I. Todorov and W. Smith RI group: M. Blanchard and K. Wright UCL group: M. Alfredsson, J.P. Brodholt and G.D. Price

eMinerals one of NERCs eScience testbed projects Environmental Processes AIM: we use computational modelling to research mineralogical processes at an atomistic level, providing information on transport and immobilisation processes of pollutants, including both toxic elements (.i.e. As, Cd, Pb and organic molecules) as well as radioactive waste. We have also looked alternative energy resources to fossil fuels. Sources of pollution e.g.: Acid mine drainage Land filling sites Industries and farming Accidents with toxics Natural catastrophes or mineralogical properties

eMinerals one of NERCs eScience testbed projects Environmental Processes Problem: Relastic models of mineral process are computationally very expensive. Layout: Grid ResourcesGrid Resources Data ManagementData Management Science OutcomesScience Outcomes Solution: GRID COMPUTING

Lakes (Bath, Cambridge, UCL): Lakes (Bath, Cambridge, UCL): 4 linux-based clusters 4 linux-based clusters 88 nodes in total with 2Gb memory per node 88 nodes in total with 2Gb memory per node Pond (Cambridge): 1 Apple Xserve cluster Pond (Cambridge): 1 Apple Xserve cluster 8 nodes with 8Gb memory per node 8 nodes with 8Gb memory per node 24-node IBM cluster (Reading) 24-node IBM cluster (Reading) 3 Condor-pools: UCL > 900 machines UCL > 900 machines Cambridge (25 machines) Cambridge (25 machines) Bath Bath NGS – CSAR - HPCxNGS – CSAR - HPCxNGS – CSAR - HPCxNGS – CSAR - HPCx Grid Resources: Resources marked in red suitable for first principles code green represents resources suitable for inter-atomic potential codes.

Storage Resource Broker (SRB) Bath, Cambridge, Reading and the central MCAT at Daresbury Chemical Markup Language (CML) Chemical Markup Language (CML) -version of XML adapted for chemical applications -All codes developed in eMinerals support CML Personal Interface Grid (PIG) Personal Interface Grid (PIG) MAST MAST Data Management WIKI WIKI Rcommands Rcommands Metadata Metadata

Job Submission: Globus (GSI/X.509-certificaes) Globus (GSI/X.509-certificaes) Condor-G Condor-G Seagull Seagull Computer Codes: Submit jobs from all machines from our work station. Maintained and developed with eMinerals: DL_Poly Metadise – Monte Carlo implemented Siesta Casino Other Codes: Gulp Marvin AbInit Casino VASP Crystal automatic meta-scheduler to submit to the most appropriate machine in the mini-grid. Dagman and Perl scripts

eMinerals one of NERCs eScience testbed projects Science Outcome: Surface and Interfaces Surface and Interfaces Determine water exchange and diffusion coefficient Effect of impurites Phase Transitions Phase Transitions due to compositional and pressure effects Lattice dynamics calculations to determine most stable polymorph Radioactive waste Radioactive waste

Aim: To fully understand transport and immobilisation processes of contaminants we need an accurate description of the mineral/solvent interfaces. Solution: We perform Molecular Dynamics simulations using the DL_POLY code. Snapshot of Goethite/Solvent interface using MD-simulation on the HPCx. A. Marmier, D. Cooke, S. Kerisit and S.C. Parker Bath University. Mineral/Solvent Interfaces Computer resources: Condor-pool - distributing many independent calculations over the machines available, using Dagman or Perl scripts good statistical data, which can be used to determine diffusion and water exchange coefficients. NGS HPCx – larger jobs

Mineral/Solvent Interfaces Result: Ordering of the water molecules close to mineral surface. Cl - ions order closer to the mineral surface than Na + ions The classical models of the electrical double layer do not describe correctly the ion distribution close to the surface. A. Marmier, D.J. Cooke, S. Kerisit and S.C. Parker Bath University.

Pt/Graphite interface Graphite: Model for organic substrate Graphite: Model for organic substrate Pt/Graphite: Alternative (renewable) energy resource to fossil fuels know to generate green house gases. Pt/Graphite: Alternative (renewable) energy resource to fossil fuels know to generate green house gases. Graphite: Model for organic substrate Graphite: Model for organic substrate Pt/Graphite: Alternative (renewable) energy resource to fossil fuels know to generate green house gases. Pt/Graphite: Alternative (renewable) energy resource to fossil fuels know to generate green house gases. A.Marmier and S.C. Parker at University of Bath

Pt/Graphite interface Aim: Derive highly quality empirical potentials from density functional theory (DFT) calcualtions. Problem: Computational costly Solution: Grid computing - NGS Aim: Derive highly quality empirical potentials from density functional theory (DFT) calcualtions. Problem: Computational costly Solution: Grid computing - NGS A.Marmier and S.C. Parker at University of Bath

Conclusions: Most stable site is located on a bridge site The activation barrier is 0.5 eV The adsorption sites and energies are different for inter-atomic potential calculations Conclusions: Most stable site is located on a bridge site The activation barrier is 0.5 eV The adsorption sites and energies are different for inter-atomic potential calculations Pt/Graphite interface A.Marmier and S.C. Parker at University of Bath

CaO-termimated TiO 2 -termimated {001} surfaces of CaTiO 3 Mineral Surfaces M. Alfredsson, J.P. Brodholt and G.D. Price UCL Calculations: investigate surfaces 2 to 5 surface terminations 4 to 16 impurity positions > 4 concentrations Total number of calculations per impurity: Computer Resources: Condor Cluster SRB

We defined a new method to calculate surface energies which allow us to determine crystal particle shape. We find particle shapes change with concentration of the impurity and the type of dopant. Important to understand the reactivity and inter- actions between pollutants and minerals. Mineral Surfaces increasing concentration

In all mineral processes we are dealing with impurities, which may changes the crystal structures Phyllosilicates (layered silicate minerals, including clays) are known to adsorb and store toxic elements. Here we show how the crystal structure of layered Li 2 Si 2 O 5 transforms (breaks up) in the presence of different elements, e.g. Cs. Z. Du and N. H. de Leeuw Birkbeck College and UCL Compositional Phase Transitions Li Cs Na Computational Resources: Condor Pools Eminerals mini-grid SRB

Z. Du and N. H. de Leeuw: Birkbeck College and UCL Compositional Phase Transitions Li Na Processes Entalphy (kJ/mol) Results: Solid solutions of guest ions in silicates are often thermodynamically stable. Cation exchange from solution is an endothermic process; only K-Na exchange expected to occur

Pyrite (Fools gold): FeS 2 Fe-bearing minerals active role in the control of acid mine drainage and transport of heavy metals like As. Transport and imobilisation process: Pyrite may contain ca. 10wt% of As Adsorption of As on Pyrite surface Aim: understanding electronic structure and bonding properties of pure pyrite. Possible phase transitions? Method: linear respons phonon calculations, using DFT Computational resources: HPCx linking back to the SRBs M. Blanchard and K. Wright at the RI

Pyrite (Fools gold): FeS 2 Results: Pyrite is an insulator (in agreement with experiment) Pyrite is described by S 2 molecules interacting with Fe ions Conclusions: Calculated frequencies are in good agreement with experiment All vibrational modes show non-linear pressure dependence Mode Grüneisen parameters give information about thermodynamical properties M. Blanchard and K. Wright at the RI

Pressure Induced Phase diagrams: MgO and FeO Expt. 1) HF-AE * HF-PP ** QMC-PP ** a (Å) B 0 (GPa) ) M. I. McCarthy et al PRB (1994) and ref. therein * AE=All-electron ** PP=Pseudo-potential Note: The PP used in the HF and QMC calculations is the same. Problem: QMC calculations are ca times more computer intensive than traditional first principles calculations. Solution: HPCx – the CASINO code show excellent scaling Problem: Traditional DFT techniques often fail in reproducing Fe-bearing minerals Solution: Quantum Monte Carlo (QMC) calculations Hybrid-DFT calculations by UCL-team

P T calculated from H B1 =H B2 ; Birch-Murnaghan 3 rd order EOS Transition Pressure (P T ) B1 to B2: QMC Result: QMC and LDA (with the same PP) give similar results P T ~ 597GPa B1 Method GGA-PAW GGA-PP(PW) LDA-LAPW LDA-PP(PW) QMC-PP P(GPa) Oganov et al JPC 2003 and ref. therein This work PP=Pseudo-potential B2 Observeration: We consumed ca Cpu Hrs by UCL-team

P(GPa) r-B1(AFM) i-B8(AFM) B8(NM) insulatorinsulator metallic Phase Diagram and Crystal Structures T Néel =193 K P~115 GPa at T=0K Fei & Mao, Science (1994) To determine phase transitions we need to: optimise the geometries for all the possible crystal structures at various pressures. ~ 240 calculations for FeO optimise the geometries for all the possible crystal structures at various pressures. ~ 240 calculations for FeO for up to 10 computational methods (Hamiltonians) for up to 10 computational methods (Hamiltonians) ~240 x 10 = ~2400 calculations ~240 x 10 = ~2400 calculations Solution: Condor Condor SRB SRBSolution: Condor Condor SRB SRB Aim: Find alternative to QMC Solution: Hybrid-DFT by UCL-team

Radioactive Waste Nuclear waste disposal – encapsulation in ceramic materials Aim: Find the best waste form to be used to immobilise surplus Pu and high-radiation waste (hrw) Problem: Most of the currently considered waste forms are damaged (amorphorised) by irradiation from hrw K. Trachenko, M.T. Dove I. Todorov and W. Smith

Radioactive Waste K. Trachenko, M.T. Dove I. Todorov and W. Smith Observation of amorphisation in Zircon

Radioactive Waste Nuclear waste disposal – encapsulation in ceramic materials Aim: Find the best waste form to be used to immobilise surplus Pu and high-radiation waste (hrw) Problem: Most of the currently considered waste forms are damaged (amorphorised) by irradiation from hrw. Amorphisation requires large computational system sizes Code development: DL_Poly 5 million atoms using the HPCx K. Trachenko, M.T. Dove I. Todorov and W. Smith

SiO 2 GeO 2 TiO 2 Al 2 O 3 MgO Radioactive waste Result: The more ionic properties the ceramics show the faster healing processes are observed. Increasing ionicity Evolution of time K. Trachenko, M.T. Dove I. Todorov and W. Smith Snapshot of MD-generated structures caused by 40 keV U recoil.

Prior the eMinerals: project the data presented here would take several years, involving many projects. many of the calculations on realistic systems were also out of reach, such as the modelling of the electrical double layer at the solvent/mineral interface, and the radiation damage, using more than 5 millions ions in the simulation. Future: team projects automatic work flows for job submission and data analysis. Level of theory Adsorbing surface Contaminant Quantum Monte Carlo Large empirical models Linear-scaling quantum mechanics Organic molecules Halogens Metallic elements Clays, micas Aluminosilicates Natural organic matter Phosphates Carbonates Oxides/hydroxides Sulphides

Acknowledgement: The Eminerals team NERC for financial support NERC for financial support eMinerals one of NERCs eScience testbed projects Web: