Atomistic simulations provide essential mechanistic insights into chemical processes, yet many important phenomena in chemistry and materials science occur on timescales that are inaccessible to molecular dynamics. Existing computational approaches force a choice between atomic resolution on relatively short timescales or phenomenological descriptions of long-time behavior. Compounding this difficulty, state-of-the-art hybrid methods inadequately address common phenomena such as spatial heterogeneity and disparate reaction kinetics landscapes. Here, this gap is addressed with the introduction of the Hybrid kinetic Monte Carlo/Molecular Dynamics (HkMCMD) algorithm, which decouples reactive event selection from vibrational dynamics to enable using kMC for time evolution. The algorithm incorporates three key components: (1) kMC-based timekeeping that advances time according to reactive events rather than atomic vibrations, (2) dynamic reaction rate scaling that detects and escapes pseudo-steady states in which fast reactions dominate, and (3) spatially-resolved diffusion calculations that capture heterogeneous transport with a voxel-based analysis. Validation on model systems demonstrates accurate dynamics across nanosecond to second timescales, computational savings of up to four orders of magnitude for systems with disparate reaction rates, and a quantitatively accurate treatment of diffusion-limited kinetics. This approach enables atomic-scale investigation of previously inaccessible slow chemical processes while retaining full configurational detail between reactive events.
Gilley et al. (Thu,) studied this question.