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Neural-network assisted study of nitrogen atom dynamics on amorphous solid water – I. adsorption and desorption.
- Source :
- Monthly Notices of the Royal Astronomical Society; Nov2020, Vol. 499 Issue 1, p1373-1384, 12p
- Publication Year :
- 2020
-
Abstract
- Dynamics of adsorption and desorption of (<superscript>4</superscript>S)-N on amorphous solid water are analysed using molecular dynamic simulations. The underlying potential energy surface was provided by machine-learned interatomic potentials. Binding energies confirm the latest available theoretical and experimental results. The nitrogen sticking coefficient is close to unity at dust temperatures of 10 K but decreases at higher temperatures. We estimate a desorption time-scale of 1 μ s at 28 K. The estimated time-scale allows chemical processes mediated by diffusion to happen before desorption, even at higher temperatures. We found that the energy dissipation process after a sticking event happens on the picosecond time-scale at dust temperatures of 10 K, even for high energies of the incoming adsorbate. Our approach allows the simulation of large systems for reasonable time-scales at an affordable computational cost and ab initio accuracy. Moreover, it is generally applicable for the study of adsorption dynamics of interstellar radicals on dust surfaces. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00358711
- Volume :
- 499
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Monthly Notices of the Royal Astronomical Society
- Publication Type :
- Academic Journal
- Accession number :
- 146608351
- Full Text :
- https://doi.org/10.1093/mnras/staa2891