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Atomistic Characterization of Stable and Metastable Alumina Surfaces ECSS Symposium Jun 18, 2013

Atomistic Characterization of Stable and Metastable Alumina Surfaces ECSS Symposium Jun 18, 2013. Sudhakar Pamidighantam. Atomistic Characterization of Stable and Metastable Alumina Surfaces. PI Doug Spearot and co-PI Shawn Coleman at the University of Arkansas. Grant #: DMR130007

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Atomistic Characterization of Stable and Metastable Alumina Surfaces ECSS Symposium Jun 18, 2013

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  1. Atomistic Characterization of Stable and Metastable Alumina Surfaces ECSS Symposium Jun 18, 2013 Sudhakar Pamidighantam

  2. Atomistic Characterization of Stable and Metastable Alumina Surfaces • PI Doug Spearot and co-PI Shawn Coleman at the University of Arkansas. • Grant #: DMR130007 • ECSS Team - Sudhakar Pamidighantam at NCSA - Yang Wang at PSC, - Mark Vanmoer at NCSA

  3. Metastable Alumina Stable a Form Because of their fine particle size, high surface area, and catalytic activity of their surfaces, the transition aluminas (especially the gform) find applications in industry as adsorbents, catalysts or catalyst carriers, coatings, and soft abrasives. The excellent stoichiometry and stability of Al2O3 help to make it an important constituent of many protective oxide scales formed on the surface of high-temperature metals and alloys. J. Am. Ceram. Soc., 81 [8] 1995–2012 (1998)

  4. Solid State Structure Determination and Function X-Ray Crystal Lattice Molecular and Solid State Structure Characterization and Crystal Engineering Function Materials for Diverse Applications

  5. XRD Compute In Lammps • The algorithm is sufficiently generic to be applicable to both electron and x-ray diffraction conditions and • is integrated into the LAMMPS molecular dynamics simulator • the algorithm is capable of performing diffraction analyses either statically (single snap shot after energy minimization) or dynamically during a molecular dynamics simulation to produce time averaged diffraction patterns at finite temperature. • A visualization procedure is developed to create SAD patterns and 2θ x-ray diffraction line profiles from the intensities computed using the atomistic simulation data.

  6. XRD Algorithm • generates a three-dimensional mesh of points filling a volume of reciprocal space constructed from the entire domain of the atomistic simulation cell. • The mesh of reciprocal lattice points is built on a rectilinear grid with spacing cn|An|−1 along each reciprocal lattice axis Bn. Each reciprocal lattice axis Bn is determined from the associated vector An corresponding to the n = 1, 2, or 3 edge of the simulation cell. • each reciprocal lattice point is associated with a reciprocal lattice vector K describing the deviation between the diffracted and incident wave vectors kD and kI ---- K = kD − kI = ξB1 + ηB2 + ζB3, sin (θ) = |K| ---------- ------ --------- Braggs’s Law 1/dhkl= |KB| λ 2 Atomic Scattering Factor (x-ray) Structure Factors

  7. X-ray virtual diffraction code (xrd) has been implemented as a LAMMPS compute, a plugin capable of computing the diffraction pattern for the structure generated by LAMMPS • The parallization of xrd is atom based, and is implemented within the framework of LAMMPS • Further parallization of xrd has been explored over the k-space mesh. • Built a stand-alone xrd code as a test bed K-mesh loop • Parallization based on a MPI implementation has shown significant performance enhancement • Another parallelization level (on top of the parallelization over the atoms) and employ extra MPI (or openMP) processes to parallelize the k-mesh is planned Parallel Approach to the Simulation of Diffraction Pattern

  8. Scaling and Memory Characteristics of Lammps_DS on Gordon Before Optimization

  9. Ongoing Efforts in the K-mesh Parallelization of the XRD Compute • Implement MIC offload directives in xrd to allow for taking advantage of the many core co-processors on Stampede • A project under the XSEDE Student Engagement Program. Summer intern student: Paula Romero Bermudez • Implement MPI group in xrd to allow for running on a large number of cores on a distributed memory system • A XSEDE Campus Champion project. Campus Champion fellow for this project: Luis A. Cueva-Parra

  10. Simulation Conditions Virtual selected area electron diffraction (SAED) patterns are created by examining the region in reciprocal space intersecting the Ewald sphere of radius λ−1. Simulated 200 kV electron radiation (λ = 0.0251Å) and Cu Kα x-rays (λ = 1.54178Å) are used to create SAED patterns and 2θ x-ray line profiles. Embedded-atom method (EAM) potential is used for modeling atoms and their interaction. Table. Parameters used to compute analytical approximations of the Ni atomic scattering factors for electron and x-ray diffraction as calculated via equations (5) and (6) respectively with sin θ/λ (Å−1). Electrona a1 a2 a3 a4 a5 b1 b2 b3 b4 b5 0.3860 1.1765 1.5451 2.0730 1.3814 0.2478 1.7660 6.3107 25.2204 74.3146 X-rayb a1 a2 a3 a4 b1 b2 b3 b4 c 12.8376 3.8785 7.2920 0.2565 4.4438 12.1763 2.3800 66.3421 1.0341 ------------------------------------------------------------------------------------------------------------- a Parameters fit to equation (5) by Peng et al Peng L-M, Ren G, Dudarev S L and WhelanMJ 1996 Robust parameterization of elastic and absorptive electron atomic scattering factors Acta Crystallogr. A 52 257–76. b Parameters fit to equation (6) by Fox et al Fox A G, O’KeefeMA and TabbernorMA 1989 Relativistic Hartree–Fock x-ray and electron atomic scattering factors at high angles Acta Crystallogr. A 45 786–93 Virtual diffraction analysis of Ni [0 1 0] symmetric tilt grain boundaries S P Coleman, D E Spearot and L Capolungo, Modelling Simul. Mater. Sci. Eng. 21 (2013) 055020

  11. Virtual Electron Diffraction Pattern and Visualization Diffraction IntensityLorentz Polarization Factor Virtual selected area electron diffraction (SAED) patterns are created by examining the region in reciprocal space intersecting the Ewald sphere of radius λ−1. A thin hemispherical slice of the reciprocal lattice mesh lying near the surface of the Ewald sphere is isolated and viewed parallel to the zone axis. The thickness of this slice is dependent on the resolution of the reciprocal space mesh and is chosen such that between 1-5 reciprocal lattice points

  12. Integration Into SEAGrid Science Gateway • Deployed Lammps_DS under the community access on Gordon • Registered the application in SEAGrid Applications registry • Registered ECSS team as users in SEAGrid – Separate PI ships for Mark and Doug created • Added Restrictions to access to Lammps_DS to ECSS project team pending public release - Demonstrating the access restriction to the PI - Ye Fan (NCSA) implemented this and additional output/log access for debugging. • Created internal single resource workflow consisting of Lammps_DS execution—XRD Compute- SAED Parsing - Visit Visualization on Gordon • Tested multiple production inputs for PI and Co-PI, with varying virtual shared memory upto 760 GB over 16 nodes.

  13. SEAGrid Access to Lammps_DS

  14. SEAGrid- Lammps_DS Results

  15. Integrating visualization Application output .saed converted to .xyz with sed script. Using OpenMPI build of VisIt (thanks to Amit Chourasia for building) VisIt launched with –s for Python script driver. Driver checks if user uploaded a sessionfile, uses RestoreSessionWithDifferentSources() Otherwise scene rendered with default threshold, clips and camera.

  16. SEAGrid- Lammps_DS Postprocessing

  17. Visualization • Reciprocal space of diffractions yields a point cloud in a spherical volume. Scalar threshold, clipped and color mapped. • Discovered multi-window sessionfile rendering bug (#1472), testing tiled images instead

  18. Next Phase in The ECSS Project Deploy same Workflow under apache Airavata-Xbaya Deploy modified workflow to use stampede for computation (Lammps_DS and XRD) and pipe data for VisIT visualization on Gordon Extend the infrastructure for VisIT session less and sessioned visualizations If time permits provide interactive VisIT steering by launching local VisIT application and contacting VisIT server at Gordon

  19. Status of the Software The diffraction code is not yet available in the full release of LAMMPS Similarly this implementation of the code is also not accessible to community from SEAGrid Gateway Details of some of the methods implemented are in the recent paper Virtual diffraction analysis of Ni [0 1 0] symmetric tilt grain boundaries S P Coleman , D E Spearot and L Capolungo, ModellingSimul. Mater. Sci. Eng. 21 (2013) 055020 (16pp) Please contact Prof. Doug Spearot (dspearot@uark.edu) for more information

  20. Future Directions in Visualization (Plugin to load saed directly into VisIt) Other rendering techniques – point sprites, volume rendering Computation, visualization on different resources

  21. Future directions Other rendering techniques – point sprites, volume rendering

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