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University College London (UCL) eMinerals one of NERCs eScience testbed projects ... Seagull. Computer Codes: Submit jobs from all machines from. our work station. ... – PowerPoint PPT presentation

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Title: Situated :


1
eMinerals one of NERCs eScience testbed projects
eMinerals Science Outcomes enabled by new Grid
Tools
Maria Alfredsson Nottingham 21/9/2005
The eMinerals team Environmental
scientists Chemists Physicists Computational
and Grid scientists. PI Martin Dove
(martin_at_esc.cam.ac.uk) Web www.eminerals.org
Situated _at_ Bath Birkbeck Cambridge CCLRC
Daresbury Reading The Royal Institution University
College London (UCL)
2
eMinerals one of NERCs eScience testbed projects
  • Research undertaken by
  • Bath group
  • 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

3
eMinerals one of NERCs eScience testbed projects
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

4
eMinerals one of NERCs eScience testbed projects
Problem Relastic models of mineral process are
computationally very expensive.
Solution GRID COMPUTING
  • Layout
  • Grid Resources
  • Data Management
  • Science Outcomes

5
Grid Resources
  • Lakes (Bath, Cambridge, UCL)
  • 4 linux-based clusters
  • 88 nodes in total with 2Gb memory per node
  • Pond (Cambridge) 1 Apple Xserve cluster
  • 8 nodes with 8Gb memory per node
  • 24-node IBM cluster (Reading)
  • 3 Condor-pools
  • UCL gt 900 machines
  • Cambridge (25 machines)
  • Bath

Resources marked in red suitable for first
principles code green represents resources
suitable for inter-atomic potential codes.
NGS CSAR - HPCx
6
Data Management
  • Storage Resource Broker (SRB)
  • Bath, Cambridge, Reading and the central MCAT at
    Daresbury
  • Chemical Markup Language (CML)
  • -version of XML adapted for chemical applications
  • -All codes developed in eMinerals support CML
  • Metadata
  • Rcommands
  • MAST
  • Personal Interface Grid (PIG)
  • WIKI

7
Job Submission
Submit jobs from all machines from our work
station.
  • Globus (GSI/X.509-certificaes)

Dagman and Perl scripts
  • Condor-G

automatic meta-scheduler to submit to the most
appropriate machine in the mini-grid.
  • Seagull

Computer Codes
  • Maintained and developed with eMinerals
  • DL_Poly
  • Metadise Monte Carlo implemented
  • Siesta
  • Casino
  • Other Codes
  • Gulp
  • Marvin
  • AbInit
  • Casino
  • VASP
  • Crystal

8
eMinerals one of NERCs eScience testbed projects
  • Science Outcome
  • Surface and Interfaces
  • Determine water exchange and diffusion
    coefficient
  • Effect of impurites
  • Phase Transitions
  • due to compositional and pressure effects
  • Lattice dynamics calculations to determine most
    stable
  • polymorph
  • Radioactive waste

9
Mineral/Solvent Interfaces
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.
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 HPC
x larger jobs
Snapshot of Goethite/Solvent interface using
MD-simulation on the HPCx. A. Marmier, D.
Cooke, S. Kerisit and S.C. Parker Bath
University.
10
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.
11
Pt/Graphite interface
  • Graphite Model for organic substrate
  • Pt/Graphite Alternative (renewable) energy
    resource to fossil fuels know to generate green
    house gases.
  • Marmier and
  • S.C. Parker at University of Bath

12
Pt/Graphite interface
  • Marmier and
  • S.C. Parker at University of Bath

Aim Derive highly quality empirical
potentials from density functional theory (DFT)
calcualtions. Problem Computational
costly Solution Grid computing - NGS
13
Pt/Graphite interface
  • 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
  • Marmier and
  • S.C. Parker at University of Bath

14
CaO-termimated
Mineral Surfaces
  • Calculations
  • investigate 10-20 surfaces
  • 2 to 5 surface terminations
  • 4 to 16 impurity positions
  • gt 4 concentrations
  • Total number of calculations
  • per impurity 120-2440

001 surfaces of CaTiO3
TiO2-termimated
  • Computer Resources
  • Condor Cluster
  • SRB

M. Alfredsson, J.P. Brodholt and G.D. Price UCL
15
Mineral Surfaces
increasing concentration
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.
16
Compositional Phase Transitions
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 Li2Si2O5 transforms
(breaks up) in the presence of different
elements, e.g. Cs.
  • Computational Resources
  • Condor Pools
  • Eminerals mini-grid
  • SRB

Z. Du and N. H. de Leeuw Birkbeck College and UCL
17
Compositional Phase Transitions
  • 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

Z. Du and N. H. de Leeuw Birkbeck College and UCL
18
M. Blanchard and K. Wright at the RI
Pyrite (Fools gold) FeS2
  • 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
19
Pyrite (Fools gold) FeS2
  • Results
  • Pyrite is an insulator (in agreement
  • with experiment)
  • Pyrite is described by S2 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
20
Pressure Induced Phase diagrams MgO and FeO
by UCL-team
Problem Traditional DFT techniques often fail in
reproducing Fe-bearing minerals Solution Quantum
Monte Carlo (QMC) calculations Hybrid-DFT
calculations
Problem QMC calculations are ca. 1000 times more
computer intensive than traditional first
principles calculations. Solution HPCx the
CASINO code show excellent scaling
21
Transition Pressure (PT) B1 to B2 QMC
by UCL-team
PT calculated from HB1HB2 Birch-Murnaghan 3rd
order EOS
Result QMC and LDA (with the same PP) give
similar results
Observeration We consumed ca. 200.000 Cpu Hrs
22
Phase Diagram and Crystal Structures
by UCL-team
Aim Find alternative to QMC Solution Hybrid-DFT
  • To determine phase transitions we need to
  • optimise the geometries for all the possible
    crystal structures at various pressures. ? 240
    calculations for FeO
  • for up to 10 computational methods
    (Hamiltonians)
  • ? 240 x 10 2400 calculations

TNéel 193 K
  • Solution
  • Condor cluster _at_UCL
  • SRB

23
K. Trachenko, M.T. Dove I. Todorov and W. Smith
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
24
K. Trachenko, M.T. Dove I. Todorov and W. Smith
Radioactive Waste
Observation of amorphisation in Zircon
25
K. Trachenko, M.T. Dove I. Todorov and W. Smith
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
26
K. Trachenko, M.T. Dove I. Todorov and W. Smith
Radioactive waste
Evolution of time
Result The more ionic properties the ceramics
show the faster healing processes are observed.
Snapshot of MD-generated structures caused by 40
keV U recoil.
Increasing ionicity
27
  • 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.

28
eMinerals one of NERCs eScience testbed projects
Acknowledgement The Eminerals team
NERC for financial support
Web www.eminerals.org
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