Modeling atomic and molecular systems requires computation-intensive quantum mechanical methods such as, but not limited to, density functional theory (DFT) . These methods have been successful in predicting various properties of chemical systems at atomistic detail. Due to the inherent nonlocality of quantum mechanics, the scalability of these methods ranges from O(N3) to O(N7) depending on the method used and approximations involved. This significantly limits the size of simulated systems to a few thousands of atoms, even on large scale parallel platforms. On the other hand, classical approximations of quantum systems, although computationally (relatively) easy to implement, yield simpler models that lack essential chemical properties such as reactivity and charge transfer. The recent work of van Duin et al  overcomes the limitations of classical molecular dynamics approximations by carefully incorporating limited nonlocality (to mimic quantum behavior) through empirical bond order potential. This reactive molecular dynamics method, called ReaxFF, achieves essential quantum properties, while retaining computational simplicity of classical molecular dynamics, to a large extent. Implementation of reactive force fields presents significant algorithmic challenges. Since these methods model bond breaking and formation, efficient implementations must rely on complex dynamic data structures. Charge transfer in these methods is accomplished by minimizing electrostatic energy through charge equilibriation. This requires the solution of large linear systems (108 degrees of freedom and beyond) with shielded electrostatic kernels at each timestep. Individual timesteps are themselves typically in the range of tenths of femtoseconds, requiring optimizations within and across timesteps to scale simulations to nanoseconds and beyond, where interesting phenomena may be observed. In this paper, we present implementation details of sPuReMD (serial Purdue Reactive Molecular Dynamics) program, a unique reactive molecular dynamics code. We describe various data structures, and the charge equilibration solver at the core of the simulation engine. This Krylov subspace solver relies on an ILU-based preconditioner, specially targeted to our application. We comprehensively validate the performance and accuracy of sPuReMD on a variety of hydrocarbon systems. In particular, we show excellent per-timestep time, linear time scaling in system size, and a low memory footprint. sPuReMD is available over the public domain and is currently being used to model diverse
Reactive Molecular Dynamics, Bond Order Potentials, ReaxFF, Charge Equilibration.
Date of this Version