Chemistry of Dark Clouds: Databases, Networks, and Models

Abstract

Chemical models have been developed over the years by astrophysicists to study the pro- cesses at play in the various environments of the interstellar medium (ISM) that define the chemical composition of the gas and the dust. These qualitative aspects of the model predictions have been improved from a chemical point of view thanks to many recent developments of the experimental technics and theoretical methods that aim at studying the individual reactions in conditions as close to the ISM conditions as possible and characterize the rate constants of their efficiency. These models have also been more and more associated with dynamical evolution of the ISM physical conditions (for star forming regions for instance) since the chemical composition is far from steady-state in such regions. In this paper, we try to assess the state of the art concerning the chemical modeling of dark clouds, the initial step for the formation of stars and disks.Comment: 61 pages, to be published in Chemical Reviews. This version of the paper may be slightly different from the published one since many modifications have done by the language edito

Grain Surface Models and Data for Astrochemistry

“…As we mentioned above, this may not be the case on a dust-grain surface under particular conditions; hence, using the rate-equation approach to describe interstellar surface chemistry can lead to large errors when compared with results using more realistic stochastic techniques. The main reason why modelers persist with such a method is the convenience, stability, and the rather fast numerical performance of the pure chemical kinetics codes, even for reaction networks which consist of thousands of reactions involving hundreds of molecules (e.g., Dalgarno and Black 1976;Leung et al 1984;D'Hendecourt et al 1985;Brown and Charnley 1990;Hasegawa et al 1992;Bergin et al 1995;Millar et al 1997;Aikawa et al 1996;Willacy et al 1998;Semenov et al 2010;Agúndez and Wakelam 2013;Albertsson et al 2013;McElroy et al 2013;Grassi et al 2014). As an indication, rate equations require CPU time of ∼1-60 seconds.…”

Recent advances in ketene chemistry

“…29 The mechanism for formation of 9 (Scheme 6) is suggested to have a much larger formation constant than used in current models. 30,31 The role of 9 in evaluating the heat release in a bluff-body combustor has also been evaluated. 32 …”

The HIFI spectral survey of AFGL 2591 (CHESS)

“…The neutral "low metals" (model lm) elemental abundances of Graedel et al (1982), Lee et al (1998), and Agúndez & Wakelam (2013) were used, with the solar ratio of C/O = 0.44, initial ortho/para H 2 of 3:1, hydrogen being fully in molecular form, and deuterium locked in HD (see Table 2). The resulting abundances of modeling this pre-AFGL 2591 phase were used as initial abundances for the AFGL 2591 chemical modeling (see Table 3).…”

“…The difficulty of calculating abundance uncertainties is well known in chemical studies of various astrophysical environments, ranging from dark clouds and hot cores to protoplanetary disks and exoplanetary atmospheres (see, e.g., Agúndez & Wakelam 2013;Dobrijevic et al 2003;Vasyunin et al 2004Vasyunin et al , 2008Wakelam et al 2005Wakelam et al , 2006. The error budget of the theoretical abundances is determined by both the uncertainties in physical conditions in the object and, to a larger degree, by uncertainties in the adopted reaction rate coefficients and their barriers.…”

“…Consequently, their abundances are usually accurate within 10−30% in modern astrochemical models. On the other hand, for other diatomic and triatomic species such as CN, HCO + , HCN, and CCH, the uncertainties are usually about a factor of 3−4 (see Vasyunin et al 2008;Agúndez & Wakelam 2013). The chemical uncertainties are even higher for more complex molecules like methanol and probably exceed a factor of 10.…”