Modern computational science has established itself as a key contributor to the understanding and interpretation of complex processes in physics, chemistry, and
materials science. The key challenge in the quest for quantitative understanding lies in a coherent treatment of molecular-level mechanisms underlying macroscopic phenomena in chemical processing. These efforts are supported by the fundamental energy science perspective, which will ultimately enable the rational design of novel catalysts, efficient energy sources, and improved production strategies.
Efforts combined across multiple disciplines are the key to comprehensively linking the insights that modeling and simulations can provide across all relevant length and time scales: at the molecular level, first-principles electronic-structure calculations unravel the making and breaking of chemical bonds. At the mesoscopic scale, statistical simulations account for the interplay between all elementary steps involved in catalytic and energy processes. Finally, at the macroscopic scale, continuum theories yield the effect of heat and mass transfer, ultimately scaling up to a plant or device-wide simulation. Multi-scale modeling thus finds its strength in a diversity of scientific backgrounds that range from physics and theoretical chemistry to chemical engineering. This diversity, however, also renders the promotion of internal communication and scientific exchange all the more essential.
