Modeling Differential Mobility from First Principles

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This research project will deal with the speed with which ions can move through a gas when dragged by an electrical field - in dependence of the ion itself, the composition of the gas and the electrical field strength. The field dependence of the so called ion mobility is used in Differential Mobility Spectrometry (DMS), a tool in analytical chemistry, to separate complex mixtures of analyte molecules. A fundamental understanding of the processes leading to separation is of great interest.Preceding work (in particular J. Am. Soc. Mass Spectrom. 30, 2711 (2019)) already revealed important parameters: The interaction between the ion and the background gas shows a characteristic field dependence. Additionally, the background gas particles can bind to the ion (clustering). The portion of bound/unbound ions is then again a field dependent quantity. Using elaborate calculations, implementing these effects, we were able to qualitatively reproduce experimental data. This already improved our fundamental understanding of differential mobility. However, because we introduced many simplifications and assumptions, a quantitative agreement was not yet achieved.It is the goal of this project to study these simplifications in greater detail and, if possible, replace them by more elaborate methods. With this, a quantitative prediction capability is aimed to achieve. In particular, we will 1) develop a better model for the description of the cluster portion, 2) consider the dynamics of the processes for fast varying fields (as applied in DMS) and 3) expand our model to more complicated, but widely used analyte molecules such as peptide or proteins.This will not only increase the fundamental understanding of the processes happening and will thus help to interpret experimental data, not yet understood; but it is also a goal to develop a tool, people can use to to design their experiments for the task given. Consequently, a program will be developed and distributed in the community.