Modelling is a proven powerful tool in materials research, providing key information for the design of new materials and materials processes. In particular, molecular simulations provide a bridge between the microscopic properties of individual atoms and molecules and the macroscopic bulk properties of materials. However, we are not yet in a situation in which industries can effectively design new materials or materials processes based purely on molecular modelling. Present simulation techniques cannot reach the time and length scales that are required for complex chemical processes, or are based on inaccurate oversimplified models that make them unreliable. Traditional molecular simulations can, without special techniques, simulate events efficiently up to the pico- or nanosecond scale. However, many industrially relevant processes, such as diffusions and chemical reactions, involve physical and chemical events that happen at the time scale of milliseconds, seconds or even hours or days.
Current modelling platforms are either unable to address such long scales, or require expensive supercomputer facilities. This provides a business opportunity for methodological developments that would make possible running such simulations. The ReaxFF method is an ideal candidate to address that need. It is an approximate, fast methods, capable of dealing with relatively long time scales and large system sizes. It is a force field method that employs a series of empirical relations to describe the energy and forces of the materials, also describing bond-breaking reactions. ReaxFF is arguably the most transferable reactive empirical force field method (it has been applied to virtually all classes of materials and its current development covers most of the elements in the periodic table) and its balance of accuracy and speed makes it the computational method of choice for atomistic-scale dynamical simulations of chemical reactions. However, meeting the demands of materials modellers will require important developments. Namely, it will require extending ReaxFF to drastically longer time scales, in order to achieve large time and length scales with high-accuracy atomistic resolution, currently a major bottleneck for industrial modellers. SCM has addressed such demand by extending ReaxFF into a robust, accurate and predictive method for modelling reaction dynamics at industrially relevant scales, without the need for supercomputing resources. This required the implementation of acceleration techniques, coupling molecular dynamics and statistical mechanics models.
