A divide-and-conquer/cellular-decomposition framework for million-to-billion atom simulations of chemical reactions

Nakano, Aiichiro; Kalia, Rajiv K.; Nomura, Kohji; Sharma, Ashish; Vashishta, Priya; Shimojo, Fuyuki; Duin, Adri C. T. van; Goddard, William A.; Biswas, Rupak; Srivastava, Deepak

doi:10.1016/j.commatsci.2006.04.012

Cited by 100 publications

(86 citation statements)

References 57 publications

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“…Nomura et al have developed a parallel ReaxFF implementation, which has been used in a number of largescale simulations, including high-energy materials, metal grain boundary decohesion, water bubbles and surface chemistry. [153][154][155][156][157][158][159] This Nomura et al code is not publicly available. Figure 6.…”

Section: Future Developments and Outlookmentioning

confidence: 99%

The ReaxFF reactive force-field: development, applications and future directions

et al. 2016

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The reactive force-field (ReaxFF) interatomic potential is a powerful computational tool for exploring, developing and optimizing material properties. Methods based on the principles of quantum mechanics (QM), while offering valuable theoretical guidance at the electronic level, are often too computationally intense for simulations that consider the full dynamic evolution of a system. Alternatively, empirical interatomic potentials that are based on classical principles require significantly fewer computational resources, which enables simulations to better describe dynamic processes over longer timeframes and on larger scales. Such methods, however, typically require a predefined connectivity between atoms, precluding simulations that involve reactive events. The ReaxFF method was developed to help bridge this gap. Approaching the gap from the classical side, ReaxFF casts the empirical interatomic potential within a bond-order formalism, thus implicitly describing chemical bonding without expensive QM calculations. This article provides an overview of the development, application, and future directions of the ReaxFF method. INTRODUCTIONAtomistic-scale computational techniques provide a powerful means for exploring, developing and optimizing promising properties of novel materials. Simulation methods based on quantum mechanics (QM) have grown in popularity over recent decades due to the development of user-friendly software packages making QM level calculations widely accessible. Such availability has proved particularly relevant to material design, where QM frequently serves as a theoretical guide and screening tool. Unfortunately, the computational cost inherent to QM level calculations severely limits simulation scales. This limitation often excludes QM methods from considering the dynamic evolution of a system, thus hampering our theoretical understanding of key factors affecting the overall behaviour of a material. To alleviate this issue, QM structure and energy data are used to train empirical force fields that require significantly fewer computational resources, thereby enabling simulations to better describe dynamic processes. Such empirical methods, including reactive force-field (ReaxFF), 1 trade accuracy for lower computational expense, making it possible to reach simulation scales that are orders of magnitude beyond what is tractable for QM.Atomistic force-field methods utilise empirically determined interatomic potentials to calculate system energy as a function of atomic positions. Classical approximations are well suited for nonreactive interactions, such as angle-strain represented by harmonic potentials, dispersion represented by van der Waals potentials and Coulombic interactions represented by various polarisation schemes. However, such descriptions are inadequate for modelling changes in atom connectivity (i.e., for modelling chemical reactions as bonds break and form). This motivates the

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Section: Future Developments and Outlookmentioning

confidence: 99%

The ReaxFF reactive force-field: development, applications and future directions

et al. 2016

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“…The modeling of the shock passage through the materials of different densities is characterized by a highly non-uniform work load of the processes. To resolve this computational difficulty, we develop a special, very efficient loadbalancing algorithm MPD 3 (material particle dynamic domain decomposition) based on the Voronoi decomposition [10]. The modeling of RMI evolution in the planar 2D geometry is very similar to that in the cylindrical case, except for the difference in the piston potential, the boundary conditions at the infinity and the initial conditions at the material interface.…”

Section: Simulation Modelmentioning

confidence: 99%

“…With a few billions of atoms simulated, MD can grasp at atomistic level the essentials of many non-equilibrium processes in shock physics, detonation and hydrodynamics [2,3]. Several representative examples are the phase transitions under shock compression, chemical reactions, and laser ablation of ultra-fast heated solids [4].…”

Section: Introductionmentioning

confidence: 99%

“…These parameters set the reduced MD units (mdu), which are used hereinafter as basic dimensions. For argon, for instance, the characteristic scales are: the length is σ = 3.405Å, the temperature is ε/k B = 119.8K, the velocity is 1094 m/s, the density is 1.68 g/cm 3 , and the time unit is σ((m a /48)/ε)) 1/2 =3.113x10 -13 . To simulate RMI in cylindrical geometry, we place initially the atoms into a rectangular MD cell inside a cylindrical domain surrounded by a piston as a cylinder wall.…”

Section: Introductionmentioning

confidence: 99%

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Atomistic Dynamics of the Richtmyer-Meshkov Instability in Cylindrical and Planar Geometries

Жаховский¹,

Zybin²,

Abarzhi³

et al. 2006

AIP Conference Proceedings

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Abstract. We apply molecular dynamics (MD) simulations to study the evolution of the shock-driven Richtmyer-Meshkov instability (RMI) in the cylindrical and planar geometries. Compared to traditional hydrodynamic simulations, MD has a number of fundamental advantages: it accounts for strong gradients of the pressure and temperature, and captures accurately the heat and mass transfers at the early stage (shock passage) as well as the late stage (perturbation growth) of the instability evolution. MD has no hydrodynamic limitations for spatial resolution and thermodynamic quasiequilibrium at atomic scale. We study the instability evolution for different perturbation modes and analyze the role of the vorticity production for RMI dynamics.

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“…The DC method has been used for many chemical applications by the Yang laboratory [29][30][31][32][33] and elsewhere. [34][35][36][37][38][39][40][41][42][43][44][45] There are also several approximate fragment approaches. 6,8,12,[46][47][48][49][50][51][52][53] In this paper, we propose a density-fragment interaction ͑DFI͒ approach for large-scale calculations based on a meanfield treatment of the electronic interaction between the fragments.…”

Section: Introductionmentioning

confidence: 99%

Density-fragment interaction approach for quantum-mechanical/molecular-mechanical calculations with application to the excited states of a Mg2+-sensitive dye

Fujimoto

Yang

2008

The Journal of Chemical Physics

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A density-fragment interaction ͑DFI͒ approach for large-scale calculations is proposed. The DFI scheme describes electron density interaction between many quantum-mechanical ͑QM͒ fragments, which overcomes errors in electrostatic interactions with the fixed point-charge description in the conventional quantum-mechanical/molecular-mechanical ͑QM/MM͒ method. A self-consistent method, which is a mean-field treatment of the QM fragment interactions, was adopted to include equally the electron density interactions between the QM fragments. As a result, this method enables the evaluation of the polarization effects of the solvent and the protein surroundings. This method was combined with not only density functional theory ͑DFT͒ but also time-dependent DFT. In order to evaluate the solvent polarization effects in the DFI-QM/MM method, we have applied it to the excited states of the magnesium-sensitive dye, KMG-20. The DFI-QM/MM method succeeds in including solvent polarization effects and predicting accurately the spectral shift caused by Mg 2+ binding.

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A divide-and-conquer/cellular-decomposition framework for million-to-billion atom simulations of chemical reactions

Cited by 100 publications

References 57 publications

The ReaxFF reactive force-field: development, applications and future directions

The ReaxFF reactive force-field: development, applications and future directions

Atomistic Dynamics of the Richtmyer-Meshkov Instability in Cylindrical and Planar Geometries

Density-fragment interaction approach for quantum-mechanical/molecular-mechanical calculations with application to the excited states of a Mg2+-sensitive dye

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