Aarhus Universitets segl


The Computational Atmospheric Chemistry group is always open for new bachelor, project and master students. Under the research page you can draw inspiration to what kind of projects we offer.

To clarify what you can expect of me as a supervisor, and what I expect of you, have a look at our Memorandum of Understanding (MoU).

Below are some potential available projects:

Cluster Formation:

  • Multicomponent clusters.
  • Organic enhanced nucleation.
  • Ion-induced nucleation.
  • Hydration of clusters.
  • Proton transfer dynamics in hydrated clusters.

Freshly Nucleated Particles (FNPs):

  • FNP compositions.
  • Vapour uptake on FNPs.
  • Reactions at the surface or inside FNPs.

Tropospheric Chemistry:

  • Oxidation of biogenic/anthropogenic VOCs
  • Oxidation of first generation biogenic vapours.

Machine Learning:

  • Kernel Ridge Regression models.
  • Neural networks for binding energies and molecular dynamics.

Surface reactions:

  • Catalysis at the cluster interface.
  • Uptake of ozone on clusters.
  • Uptake of isoprene oxidation products on clusters.

Gas-to-particle partitioning:

  • Water displacement reactions with mono/diacids.
  • Micro-solvation environments: Combinations of water, sulfate, nitrate and organics.

Aerosol optical properties:

  • Aerosol scattering/absorption properties.
  • Transition from Rayleigh to Mie scattering.

Method Assessment:

  • Geometric Counterpoise corrections (gcp)
  • Fragmentation approaches for studying large clusters.
  • Semi-Empirical methods performance.
  • Local Energy Decomposition (LED) analysis.
  • Long-range transition state theory for collision rates.
  • Tight d-functions on sulfur.

Method development:

  • DFT level required for Machine Learning.
  • Composite binding free energy methods.
  • Seasonal functions pc basis sets.