April 6, 2015
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
• ECSS Team
- Sudhakar Pamidighantam at NCSA
- Yang Wang at PSC,
- Mark Vanmoer at NCSA
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Metastable Alumina
Because of their fine particle size, high surface area, and
catalytic activity of their surfaces, the transition aluminas
(especially the g form) 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.
Stable
a Form
J. Am. Ceram. Soc., 81 [8] 1995–2012 (1998)
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Solid State Structure Determination and Function
X-Ray
Crystal Lattice
4
Molecular and Solid
State Structure
Function
Characterization and
Crystal Engineering
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.
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
Structure Factors
Atomic Scattering Factor
(x-ray)
Parallel Approach to the Simulation of Diffraction
Pattern
•
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
Scaling and Memory Characteristics of
Lammps_DS on Gordon Before Optimization
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
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
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Virtual Electron Diffraction Pattern
and Visualization
Diffraction Intensity
Lorentz 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
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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.
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SEAGrid Access to Lammps_DS
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SEAGrid- Lammps_DS Results
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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.
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SEAGrid- Lammps_DS Postprocessing
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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
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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
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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,
Modelling Simul. Mater. Sci. Eng. 21 (2013) 055020 (16pp)
• Please contact Prof. Doug Spearot (dspearot@uark.edu) for more
information
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Future Directions in Visualization
• (Plugin to load saed directly into VisIt)
• Other rendering techniques – point sprites,
volume rendering
• Computation, visualization on different
resources
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Future directions
• Other rendering techniques – point sprites,
volume rendering
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