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Reactive Molecular Dynamics Simulations, Data Analytics and Visualization

Published online by Cambridge University Press:  27 February 2015

Priya Vashishta ,
Rajiv K. Kalia ,
Aiichiro Nakano ,
Ying Li ,
Ken-ichi Nomura ,
Adarsh Shekhar ,
Fuyuki Shimojo ,
Kohei Shimamura  and
Manaschai Kunaseth
Priya Vashishta
Affiliation:
Collaboratory for Advanced Computation and Simulations, Departments of Chemical Engineering and Materials Science, Physics and Astronomy, and Computer Science, University of Southern California, Los Angeles, CA 90089-0242, USA
Rajiv K. Kalia
Affiliation:
Collaboratory for Advanced Computation and Simulations, Departments of Chemical Engineering and Materials Science, Physics and Astronomy, and Computer Science, University of Southern California, Los Angeles, CA 90089-0242, USA
Aiichiro Nakano
Affiliation:
Collaboratory for Advanced Computation and Simulations, Departments of Chemical Engineering and Materials Science, Physics and Astronomy, and Computer Science, University of Southern California, Los Angeles, CA 90089-0242, USA
Ying Li
Affiliation:
Collaboratory for Advanced Computation and Simulations, Departments of Chemical Engineering and Materials Science, Physics and Astronomy, and Computer Science, University of Southern California, Los Angeles, CA 90089-0242, USA Argonne Leadership Computing Facility, Argonne National Laboratory, Argonne, IL 60439, USA
Ken-ichi Nomura
Affiliation:
Collaboratory for Advanced Computation and Simulations, Departments of Chemical Engineering and Materials Science, Physics and Astronomy, and Computer Science, University of Southern California, Los Angeles, CA 90089-0242, USA
Adarsh Shekhar
Affiliation:
Collaboratory for Advanced Computation and Simulations, Departments of Chemical Engineering and Materials Science, Physics and Astronomy, and Computer Science, University of Southern California, Los Angeles, CA 90089-0242, USA
Fuyuki Shimojo
Affiliation:
Collaboratory for Advanced Computation and Simulations, Departments of Chemical Engineering and Materials Science, Physics and Astronomy, and Computer Science, University of Southern California, Los Angeles, CA 90089-0242, USA Department of Physics, Kumamoto University, Kumamoto 860-8555, Japan
Kohei Shimamura
Affiliation:
Collaboratory for Advanced Computation and Simulations, Departments of Chemical Engineering and Materials Science, Physics and Astronomy, and Computer Science, University of Southern California, Los Angeles, CA 90089-0242, USA Department of Physics, Kumamoto University, Kumamoto 860-8555, Japan
Manaschai Kunaseth
Affiliation:
Collaboratory for Advanced Computation and Simulations, Departments of Chemical Engineering and Materials Science, Physics and Astronomy, and Computer Science, University of Southern California, Los Angeles, CA 90089-0242, USA National Nanotechnology Center (NANOTEC), Thailand Science Park, Pathumthani 12120, Thailand
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Abstract

Multimillion-atom reactive molecular dynamics (RMD) and large quantum molecular dynamics (QMD) simulations are used to investigate structural and dynamical correlations under highly nonequilibrium conditions and reactive processes in nanostructured materials under extreme conditions. This paper discusses four simulations:

  1. 1. RMD simulations of heated aluminum nanoparticles have been performed to study the fast oxidation reaction processes of the core (aluminum)-shell (alumina) nanoparticles and small complexes.

  2. 2. Cavitation bubbles readily occur in fluids subjected to rapid changes in pressure. We have used billion-atom RMD simulations on a 163,840-processor Blue Gene/P supercomputer to investigate chemical and mechanical damages caused by shock-induced collapse of nanobubbles in water near silica surface. Collapse of an empty nanobubble generates high-speed nanojet, resulting in the formation of a pit on the surface. The gas-filled bubbles undergo partial collapse and consequently the damage on the silica surface is mitigated.

  3. 3. Our QMD simulation reveals rapid hydrogen production from water by an Al superatom. We have found a low activation-barrier mechanism, in which a pair of Lewis acid and base sites on the Aln surface preferentially catalyzes hydrogen production.

  4. 4. We have introduced an extension of the divide-and-conquer (DC) algorithmic paradigm called divide-conquer-recombine (DCR) to perform large QMD simulations on massively parallel supercomputers, in which interatomic forces are computed quantum mechanically in the framework of density functional theory (DFT). A benchmark test on an IBM Blue Gene/Q computer exhibits an isogranular parallel efficiency of 0.984 on 786,432 cores for a 50.3 million-atom SiC system. As a test of production runs, LDC-DFT-based QMD simulation involving 16,661 atoms was performed on the Blue Gene/Q to study on-demand production of hydrogen gas from water using LiAl alloy particles.

Keywords

simulationnanoscaleoxidation
Type
Articles
Information
MRS Online Proceedings Library (OPL) , Volume 1756: Symposium SS – Informatics and Genomics for Materials Development , 2015 , mrsf14-1756-ss06-01
Copyright
Copyright © Materials Research Society 2015 

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References

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