Chemical sensing on oxide sensors is a complex phenomenon involving catalytic activity as well as electronic properties. Thus, the properties of oxide sensors are highly sensitive towards structural changes. Effects like surface area, grain size, and, in addition, the occurrence of defects give separate contributions to the current. Structure–property–function relationships can be elucidated using a combination of state‐of‐the‐art analytical techniques. It is shown, that impurity atoms in the oxide lattice influence the performance of ZnO sensors more strongly than the other factors.

The Dual Population Balance Monte Carlo Method (DPBMC) takes into account the full size spectrum of the droplet and particle phase. Droplet and particle size distributions are rendered by weighted simulation particles. This allows for an accurate description of particle nucleation and coagulation and droplet combustion, simultaneously. Internal droplet properties such as temperature and concentrations fields are used to define criteria for the onset of droplet breakage in the framework of weighted Monte Carlo droplets. We discuss the importance of droplet polydispersity on particle formation in metal oxide particle synthesis, which is shown to strongly affect particle formation and growth. The method is applied to particle synthesis from metal nitrate precursor solutions with flame spray pyrolysis (FSP) and compared to experiments from literature.