4.6 Article

Dust in brown dwarfs and extra-solar planets VIII. TiO2 seed formation: 3D Monte Carlo versus kinetic approach

Journal

ASTRONOMY & ASTROPHYSICS
Volume 654, Issue -, Pages -

Publisher

EDP SCIENCES S A
DOI: 10.1051/0004-6361/202140378

Keywords

planets and satellites; atmospheres; planets and satellites; composition; planets and satellites; gaseous planets; opacity; molecular processes

Funding

  1. European Union H2020-MSCA-ITN-2019 [860 470]
  2. St Andrews St Leonard College international scholarship
  3. ERC [646758 AEROSOL]

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The study focuses on modelling the formation of TiO2-cloud condensation nuclei in exoplanet atmospheres using 3D Monte Carlo simulations. They found that the growth efficiency of (TiO2)(N) clusters has a peak temperature at around 1000 K, triggering CCN formation. The onset of cloud formation may be observable through specific vibrational lines of (TiO2)(4), (TiO2)(5), and (TiO2)(6).
Context. Modelling the formation of cloud condensation nuclei (CCNs) is key for predicting cloud properties in planet and brown dwarf atmospheres. The large diversity of exoplanets (rocky planets, mini-Neptunes, giant gas planets) requires a fundamental approach to cloud formation modelling in order to allow a full analysis of observational data contributing to exoplanet characterisation. Aims. We aim to understand the onset of cloud formation and study the formation of TiO2-CCNs. The formation of (TiO2)(N) clusters as precursors to extrasolar cloud formation is modelled by two different methods in order to understand their potential, identify underlying shortcomings, and to validate our methods. We propose potential spectral tracers for TiO2-CCN formation. Methods. We applied three-dimensional Monte Carlo (3D MC) simulations to model the collision-induced growth of TiO2-molecules to (TiO2)(N)-clusters in the free molecular flow regime of an atmospheric gas. We derived individual, time-dependent (TiO2)(N) cluster number densities. For T = 1000 K, the results are compared to a kinetic approach that utilises thermodynamic data for individual (TiO2)(N) clusters. Results. The (TiO2)(N) cluster size distribution is temperature dependent and evolves in time until a steady state is reached. For T = 1000 K, the 3D MC and the kinetic approach agree well regarding the cluster number densities for N = 1 horizontal ellipsis 10, the vivid onset of cluster formation, and the long transition into a steady state. Collision-induced growth and evaporation simulated using a 3D MC approach enables a faster onset of cluster growth through nucleation bursts. Different size distributions develop for monomer-cluster and for cluster-cluster growth, with the largest clusters appearing for cluster-cluster growth. Conclusions. The (TiO2)(N) cluster growth efficiency has a sweet-spot temperature at approximate to 1000 K at which CCN formation is triggered. The combination of local thermodynamic conditions and chemical processes therefore determines CCN formation efficiency. The onset of cloud formation may be observable through the (TiO2)(4), (TiO2)(5), and (TiO2)(6) vibrational lines, which may be detectable with the Mid-Infrared Instrument on the James Webb Space Telescope or the Extremely Large Telescope's mid-IR imager, but more complete line-list data are desirable.

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