Reactive Molecular Dynamics Simulations, Data Analytics and Visualization
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Reactive Molecular Dynamics Simulations, Data Analytics and Visualization Priya Vashishta1 Rajiv K. Kalia,1 Aiichiro Nakano,1 Ying Li,1,2 Ken-ichi Nomura,1 Adarsh Shekhar,1 Fuyuki Shimojo,1,3 Kohei Shimamura,1,3 Manaschai Kunaseth1,4 1 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 2 Argonne Leadership Computing Facility, Argonne National Laboratory, Argonne, IL 60439, USA 3 Department of Physics, Kumamoto University, Kumamoto 860-8555, Japan 4 National Nanotechnology Center (NANOTEC), Thailand Science Park, Pathumthani 12120, Thailand 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. 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. 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 highspeed 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. 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. 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. INTRODUCTION In broad areas such as physics, chemistry, biology, and materials science, there is urgent need for performing large quantum molecular dynamics (QMD) simulations, which follow the trajectories of all atoms while computing interatomic forces quantum mechanically from first principles based on the density functional theory (DFT) [1-5]. Computational scientists are also