Diagnostics for the elemental composition of protostellar objects View Full Text


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Article Info

DATE

2017-02-23

AUTHORS

O. V. Kochina, D. S. Wiebe

ABSTRACT

The sensitivity of a number of aspects of the chemical evolution of a molecular cloud to its elemental composition is investigated. Four models are considered: one with high metallicity, for which the evolution proceeds exclusively in the gas phase, two with low metallicity, for which processes proceed both in the gas phase and on grain surfaces, and a model with low metallicity and an artificially reduced oxygen content. One of the low-metallicity models initially contains only neutral components, while some initial ionization of atoms of heavy elements is included in the other models. A network of chemical reactions, including a detailed description of the chemistry of deuterium compounds, is used to analyze this sensitivity. It is shown that the initial composition affects the chemical evolution of most components in some way, but this influence is sometimes negligible. The inclusion of certain chemical factors can be important, such as surface reactions and the loss of a substantial fraction of atoms of heavy elements that are in grains. However, some components are influenced by even small variations in the initial and elemental compositions. One such component is the DCO+ ion, whose evolution is sensitive to the initial degree of ionization of atoms of heavy elements, even if the set of reactions included and the elemental composition are the same in different cases. The possible use of HD and HF as indicators of the presence of molecular hydrogen is also considered. HF reliably traces H2 at times exceeding 105 years under the physical conditions considered. However,HD is not a reliable indicator of H2 at the densities characteristic for protostellar clouds. More... »

PAGES

103-114

Identifiers

URI

http://scigraph.springernature.com/pub.10.1134/s1063772917020019

DOI

http://dx.doi.org/10.1134/s1063772917020019

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1083916552


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