No abstract

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

openAccessArticle: FalsePage Range: 245-245doi: 10.1016/j.parco.2011.08.005Harvest Date: 2016-01-12 15:10:37issueName:cover date: 2012-04-01pubType

We report our study of a silica-water interface using reactive molecular dynamics. This first-of-its-kind simulation achieves length and time scales required to investigate the detailed chemistry of the system. Our molecular dynamics approach is based on the ReaxFF force field of van Duin et al. ͓J. Phys. Chem. A 107, 3803 ͑2003͔͒. The specific ReaxFF implementation ͑SERIALREAX͒ and force fields are first validated on structural properties of pure silica and water systems. Chemical reactions between reactive water and dangling bonds on a freshly cut silica surface are analyzed by studying changing chemical composition at the interface. In our simulations, reactions involving silanol groups reach chemical equilibrium in ϳ250 ps. It is observed that water molecules penetrate a silica film through a proton-transfer process we call "hydrogen hopping," which is similar to the Grotthuss mechanism. In this process, hydrogen atoms pass through the film by associating and dissociating with oxygen atoms within bulk silica, as opposed to diffusion of intact water molecules. The effective diffusion constant for this process, taken to be that of hydrogen atoms within silica, is calculated to be 1.68ϫ 10 −6 cm 2 / s. Polarization of water molecules in proximity of the silica surface is also observed. The subsequent alignment of dipoles leads to an electric potential difference of ϳ10.5 V between the silica slab and water.

SUMMARYWe describe an efficient and scalable symmetric iterative eigensolver developed for distributed memory multi‐core platforms. We achieve over 80% parallel efficiency by major reductions in communication overheads for the sparse matrix‐vector multiplication and basis orthogonalization tasks. We show that the scalability of the solver is significantly improved compared to an earlier version, after we carefully reorganize the computational tasks and map them to processing units in a way that exploits the network topology. We discuss the advantage of using a hybrid OpenMP/MPI programming model to implement such a solver. We also present strategies for hiding communication on a multi‐core platform. We demonstrate the effectiveness of these techniques by reporting the performance improvements achieved when we apply our solver to large‐scale eigenvalue problems arising in nuclear structure calculations. Because sparse matrix‐vector multiplication and inner product computation constitute the main kernels in most iterative methods, our ideas are applicable in general to the solution of problems involving large‐scale symmetric sparse matrices with irregular sparsity patterns. Copyright © 2013 John Wiley & Sons, Ltd.