Solving the reaction mechanisms of oxidation reaction pathways. This includes using quantum chemical calculations, exploitation of machine learning approaches and kinetics modeling. Aim is to connect obtained reaction mechanisms with rate coefficients for chemistry transport models to obtain deep understanding oxidized organic compounds formation in the Earth’s atmosphere.
Utilizing a novel instrumentation for gaining structural information of the oxidation reaction products directly from the reaction chamber. This includes development of mass selection techniques as well as measuring and analyzing matrix isolated vibrational spectrum. Aim is to develop a technique to obtaining exact molecular structures from oxidation reaction studies.
Modeling the chemical composition and stability of atmospheric clusters. Methods include quantum chemistry, quantum machine learning, and cluster dynamics. Aim is to solve mechanisms and compounds responsible of atmospheric aerosol particle formation.
Finding the molecular properties of oxidized organic compounds which best describe the particle formation ability and deriving a parametrization, which can be used in climate models. Aim is to understand how changes in emissions of the precursor compounds will affect the climate.