Finding ways of efficient water splitting is one of the key goals of modern energy research. The process relies on the efficient reduction of water hydrogen and oxidation of water oxygen. For long it has been known that electrons solvated in water are the most ideal and direct agents to induce the reduction, but typically their generation in sufficient amounts seemed to be limited by harsh reaction conditions. Only very recently a relatively mild production process was realized experimentally on hydrogenated bulk diamond surfaces under UV (sunlight) illumination. The process is imagined as this: (1) diamond is excited into a state with high electron density on the surface which allows (2) the electron to transfer into the interfacial water and (3) to diffuse into the solution where (4) it eventually reacts. Still we are far from understanding the mechanism and from being able to improve its performance.
Ideas came up that nanodiamonds, i.e., nanometer-sized diamond particles, will be suitable electron emitters due to their extremely large surface area per total mass, as well as special interface properties absent in the bulk material. In particular, surface curvature and functionalization with heteroatoms rather than hydrogen may have a positive impact.
To learn more about the electron generating processes, we plan to model the electron transfer and solvation dynamics (steps (1)-(3) above) by coupled multi-scale electron and nuclear dynamics methods. Steps (1-2) require intricate quantum electron dynamics (ED) calculations, which can be done only for a small number of molecular conformations. Steps (2-3) rely on electron hopping/transfer rates in conjunction with statistical interface physics and molecular dynamics (MD) simulations of the diamond/water interface. Deep learning will be used to approximate results from ED to parametrize MD simulation to create a time-dependent multi-physics description of the full process that giving a significantly better understanding of the system. Finally, we will employ an optimal control scheme to find the most efficient electron solvation process where optimal control parameters are surface decoration, UV pulse (intensity, duration, shape), and temperature.