The present work proposes a methodology to improve the computational requirements of molecular dynamics simulations while maintaining or improving the fidelity of the obtained results. The most common method of molecular dynamics simulation at present is the multi-force, constant time-step, explicit computation, which advances a single time step at a time to determine the next state of the system. The present work proposes a variable time-step strategy, where a single large simulation is subdivided into multiple time domains which redistribute computational resources where they are needed the most: in areas of higher than average potential or kinetic energy or highly dynamic areas around impurity clusters, void formations and crack propagations. The research focuses on the simulation of metallic compounds, as these form the basis of most common molecular dynamics simulations, and have been very thoroughly investigated over the years, thus providing a very extensive body of work for the purpose of comparison and validation of the proposed methodology. The novel methodology presented in this work allows to alleviate some of the limitations associated with the molecular dynamics methodologies and go beyond traditional scales of simulation. The proposed method has been observed to deliver 5 to 20 percent increase in simulation size domain while maintaining or improving the accuracy and computational cycle time. The benefits were observed to be greater for large simulations with one or more areas of higher than average kinetic or potential energy levels, such as those found during crack initiation and propagation, coating-substrate interface, localized pressure application or large thermal gradient. The large difference allows for very clear prioritization of computational resources for high energy areas and as a result provides for faster and more accurate simulation even with increased domain size. Conversely, this method has been observed to provide little to no benefit when simulating stable systems that are undergoing very slow change, such as (relatively) slow change in ambient temperature or pressure, or otherwise homogeneous internal and external boundary conditions. However, for the majority of applications described above, including coating deposition and additive manufacturing, the proposed methodology will yield substantial increase in both simulation size and accuracy, since in the aforementioned processes kinetic and potential energy gradients across the simulation are typically very significant
Multiple time step algorithms for molecular dynamics simulations of proteins: How good are they?
