Chemical modeling of Infrared Dark Clouds: the Role of Surface Chemistry

TL;DR

This study models the chemistry of infrared dark clouds using gas-phase, accretion, and surface chemistry networks, successfully matching observed molecular abundances and highlighting the importance of surface processes in IRDCs.

Contribution

It introduces a comprehensive gas-grain chemical model for IRDCs and demonstrates its effectiveness in reproducing observed molecular abundances.

Findings

Complete gas-grain model fits observed data well.

Surface chemistry is crucial for explaining N$_2$H$^+$ abundance.

0-D model suffices for single-dish observational data.

Abstract

We simulate the chemistry of infrared dark clouds (IRDCs) with a model in which the physical conditions are homogeneous and time-independent. The chemistry is solved as a function of time with three networks: one purely gas-phase, one that includes accretion and desorption, and one, the complete gas-grain network, that includes surface chemistry in addition. We compare our results with observed molecular abundances for two representative IRDCs -- IRDC013.90-1 and IRDC321.73-1 -- using the molecular species N$_2$H$^+$, HC$_3$N, HNC, HCO$^+$, HCN, C$_2$H, NH$_3$ and CS. IRDC013.90-1 is a cold IRDC, with a temperature below 20 K, while IRDC321.73-1 is somewhat warmer, in the range 20 - 30 K. We find that the complete gas-grain model fits the data very well, but that the goodness-of-fit is not sharply peaked at a particular temperature. Surface processes are important for the explanation of the high gas-phase abundance of N$_2$H$^+$ in IRDC321.73-1. The general success of the 0-D model in reproducing single-dish observations of our limited sample of 8 species shows that it is probably sufficient for an explanation of this type of data. To build and justify more complicated models, including spatial temperature and density structure, contraction, and heating, we require high-resolution interferometric data.