A KINETIC DATABASE FOR ASTROCHEMISTRY (KIDA)

Users can find two different types of data in KIDA. Some data are related to chemical species and others are related to chemical reactions. In the first type, one can find InChI codes, CAS registry numbers, electronic states, polarizabilities, dipole moments, and enthalpies of formation. InChI codes (for International Chemical Identifier, http://www.iupac.org/inchi/) are character chains defined by IUPAC to identify any chemical species. The InChI code of OCS for instance is InChI = 1S/COS/c2-1-3. These codes are needed for clear identification, especially in the context of interoperability of databases. Free software is available to draw the structure of the molecule from the InChI code. CAS registry numbers are numeric identifiers from the American Chemical Society. These numbers exist, however, only for chemical species used in industry. Most of these data in KIDA have been collected from other databases such as the NIST Chemistry Webbook (http://webbook.nist.gov/chemistry/form-ser.html), CCCBDB (http://cccbdb.nist.gov/), and Woon & Herbst (2009). JPEG images of the structures of the species, drawn with the JMOL free software (http://jmol.sourceforge.net/index.fr.html), are also displayed.

For chemical reactions, rate coefficients are stored in the form of three parameters (A, B, and C), which can be used to compute the rate coefficients using different formulas depending on the process considered and the range of temperatures desired. Rate coefficients define the intrinsic velocity of chemical reactions; the units in which they are expressed depend on the order of the reaction. The overall rate of a reaction is given by the product of the rate coefficient and the densities of the reactants. There are nine classes of reactions in KIDA, which are listed and described in Table 1. The first three classes can be thought of as unimolecular processes induced by cosmic rays or photons; here the rate coefficient has units of s⁻¹, and reaction rates are computed by multiplying the rate coefficient by the density (in cm⁻³) of the reactant. The next five classes involve bimolecular collisions; in these classes rate coefficients have units of cm³ s⁻¹, and the rate of reaction is computed by multiplying the rate coefficient by the densities (in cm⁻³) of the two reactants. The last type is composed of ter-molecular (three-body) association reactions, which are processes where two reactants associate to form a product that is stabilized by collision with a third species, which can be a reactant or an inert atom or molecule. In the low-density limit, the rate of reaction is given by a rate coefficient in units of cm⁶ s⁻¹ multiplied by the product of the densities of the three species involved in the reaction. A more general rate law involves a more complex dependence on density, which eventually saturates into a bimolecular rate law (Anicich 1993). Three-body association reactions are effective in "very dense" sources by interstellar if not terrestrial standards (>10¹¹ cm⁻³) and are generally considered in the atmospheres of planets. This type of reaction will be included later into KIDA.

The rate coefficients for bimolecular processes involving two heavy species or one heavy species and an electron are each given a certain range of temperature in which the parameters are applicable. By default, the rate coefficients are valid between 10 and 300 K. For updated rate coefficients, the temperature range is given by the results of experiments or the estimates of experts. Extrapolations outside this range of temperature are not recommended unless the rate coefficient is predicted to be totally independent of temperature, as occurs for the Langevin model of exothermic ion–non-polar-neutral reactions. Temperature-dependent rate coefficients, at a specific temperature T, can often be fitted to the Arrhenius–Kooij formula:

$$\begin{equation} k_{{\rm Kooij}}(T) = A (T/300)^B \exp (-C/T) \ {\rm cm}^3\ {\rm s}^{-1}, \end{equation} \tag{ 1 }$$

where A, B, and C are parameters. Several sets of rate coefficients for the same reaction can exist for different ranges of temperature or even the same range. If this happens for identified key reactions, KIDA experts can give recommendations on which values to use (see Section 2.3).

Rate coefficients for unmeasured reactions between ions and neutral species with a dipole moment are computed using the Su–Chesnavich capture approach as discussed in Woon & Herbst (2009) and Wakelam et al. (2010b). Here, the rate coefficient k_D is expressed in terms of the temperature-independent Langevin rate coefficient k_L using two formulas, one for lower and one for higher temperatures. The temperature ranges are divided by that temperature for which a parameter x, defined by the relation

$$\begin{equation} x = \frac{\mu _{\rm D}}{(2\alpha kT)^{1/2}}, \end{equation} \tag{ 2 }$$

where (in cgs-esu units) μ_D is the dipole moment and α, the dipole polarizability, is equal to 2. The formulas for k_D/k_L at the lower and higher temperature ranges are respectively

$$\begin{equation} k_{\rm D}/k_{\rm L} = 0.4767x + 0.6200 \end{equation} \tag{ 3 }$$

and

$$\begin{equation} k_{\rm D}/k_{\rm L} = (x + 0.5090)^{2}/10.526 + 0.9754. \end{equation} \tag{ 4 }$$

At the lowest temperatures in the region of validity for Equation (3) (T ⩾ 10 K), k_D goes as T^−1/2, whereas at the highest temperatures, k_D approaches the Langevin value. The rate coefficients are valid in the so-called semiclassical region, before they level off with decreasing temperature near 10 K or below (Troe 1996).

Rate coefficients for photo-processes by UV photons, k_photo, are normally computed as a function of the visual extinction A_v:

$$\begin{equation} k_{{\rm photo}} = A \exp (-C A_v)\ {\rm s}^{-1}. \end{equation} \tag{ 5 }$$

The rate is obtained by multiplying k_photo by the density of the reactant. The parameter A for k_photo represents the unattenuated photodissociation rate in a reference radiation field whereas exp (− CA_v) takes into account the continuum attenuation from the dust. Since dust particles tend to attenuate light at shorter wavelengths more strongly, values of C are larger for species that have thresholds for photodissociation/photoionization farther into the UV (van Dishoeck 1988). Photoinduced rates depend on the external UV radiation field assumed. For example, the so-called average interstellar radiation field differs from the radiation field around a specific type of star. It is possible in KIDA to specify which field will be used. The data included in KIDA have been computed for the interstellar radiation field (Draine 1978). Data computed with other fields will be included in the future.

Cosmic rays, chiefly protons and alpha particles with energies above 1 MeV, interact with gas-phase atoms and molecules in two ways. First, these high-energy particles can directly ionize a species. This direct process is dominant for H₂, H, O, N, He, and CO. Electrons produced in the direct process can cause secondary ionization before being thermalized. The secondary process is taken into account in most treatments by a factor of 5/3 (Dalgarno et al. 1999; Rimmer et al. 2012) while the effect of ionization by alpha particles is taken account of by a separate factor of 1.8. The total ionization rate coefficient including these two factors is computed by

$$\begin{equation} k_{{\rm CR},i} = A_i \zeta \end{equation} \tag{ 6 }$$

where ζ (s⁻¹) incorporates the flux of cosmic rays and secondary electrons and normally refers to atomic hydrogen (Cravens & Dalgarno 1978). In the udfa, OSU, and KIDA networks, however, ζ refers to molecular hydrogen ($\zeta _{{\rm H_2}}$) and is approximately twice the value for atomic hydrogen. The rate coefficients for different species can be obtained by including a factor A_i.

In addition to secondary ionization, the electrons produced in direct cosmic-ray ionization can electronically excite both molecular and atomic hydrogen. The radiative relaxation of H₂ (and H) produces UV photons that ionize and dissociate molecules. This indirect process is known as the Prasad–Tarafdar mechanism (Prasad & Tarafdar 1983). It represents a source of UV photons inside dense clouds. The rate coefficients of dissociation or ionization that proceed via excitation of molecular hydrogen are given by

$$\begin{equation} k_{{\rm CRP},{i}} = \frac{A_i}{(1-\omega)} \frac{n{\rm (H_2)}}{(n({\rm H}) + 2n{\rm (H_2)})} \zeta _{{\rm H_2}} \end{equation} \tag{ 7 }$$

where $\zeta _{{\rm H_2}}$ is the total ionization rate for H₂, ω is the albedo of the grains in the far ultraviolet, n(H) is the density of atomic hydrogen, and n(H₂) is the density of molecular hydrogen (see also Gredel et al. 1989). In the OSU network (and subsequently in KIDA), it is assumed that ω is 0.5 and that the abundance of atomic hydrogen is negligible compared to molecular hydrogen. The rate then simplifies to $k_{{\rm CRP},{i}} = A_i \zeta _{{\rm H_2}}$. This of course is only valid in dense sources. Unlike the case for direct cosmic-ray ionization, the factor A_i can be quite large, often in the range 10³–10⁴. The case of CO must be treated individually because of self-shielding (Gredel et al. 1987).

Data provided in KIDA are associated with a reference. This reference can be bibliographic, another database, or a datasheet, as discussed in Section 2.3. All the reactions from the low-temperature OSU database osu-01-2009 have been included, even reactions involving anionic species (Harada & Herbst 2008). Many updates concerning photoinduced rates are currently being undertaken based on results from van Dishoeck et al. (2006) and van Hemert & van Dishoeck (2008). Branching ratios for the dissociation of carbon clusters by both external UV radiation and cosmic-ray-induced photons have been added based on Chabot et al. (2010). Reactions necessary for primordial chemistry, collected by D. Galli, will be included before the end of 2012. Finally, many other additions have been made, in particular for neutral–neutral reactions, based on new experimental and/or theoretical results. All the original bibliographic references listed in KIDA are given in the Appendix to this paper.

For all the rate coefficients in KIDA, a status is indicated. There are four possible recommendations, which are listed below.

• 1.  
  Not recommended. This status strongly suggests that the reaction should not be included.
• 2.  
  Unknown. This status is mainly for reactions from other databases that have not been looked at by KIDA experts.
• 3.  
  Valid. This is a status meant for reactions that are associated with a bibliographic reference.
• 4.  
  Recommended. Recommended rate coefficients are mainly deduced from a variety of sources (experimental or theoretical) but can also just be educated guesses. The recommended status must be justified by a datasheet and can evolve with time when new data are available. Datasheets are pdf files stored in KIDA (http://kida.obs.u-bordeaux1.fr/publications#span_datasheets) summarizing the information available on a reaction. These datasheets are inspired from the work done by the IUPAC subcommittee for Gas Kinetic Data Evaluation (http://www.iupac-kinetic.ch.cam.ac.uk/). Datasheets, of which there are currently more than 40, are signed by one or more authors and are reviewed internally by KIDA experts.

The reliability of any reaction rate coefficient stored in KIDA is expressed in terms of an estimated uncertainty over the temperature range covered by the recommendation. This uncertainty is specified by three fields, two of which are shown in Table 2.

• 1.  
  The type of the statistical distribution representing the uncertainty. The preferred distribution, and the default, is the Lognormal (default = logn). This choice enforces the positivity of the rate coefficient, even for large uncertainty factors (F₀ ⩾ 2) (Thompson & Stewart 1991; Hébrard et al. 2009). Other distributions are implemented to accommodate the most common uncertainty representations: Normal (norm), Uniform (unif), and Loguniform (logu) (Table 2).
• 2.  
  The uncertainty parameter F₀. By default, it is the standard geometric deviation for the Lognormal distribution, but has no default value. It defines a standard "1σ" confidence interval around the reference value k₀ (Sander et al. 2011), with the probability of assertion (Pr) defined by Pr(k₀/F₀ ⩽ k ⩽ k₀*F₀) ≃ 0.68. For other distributions than the Lognormal, F₀ has different meanings and units, as specified in Table 2.
• 3.  
  The expansion parameter g (default = 0, units: Kelvin). It is used to parameterize a possible temperature dependence of the uncertainty, according to the formula F(T) = F₀*exp (g|1/T − 1/T₀|) (Sander et al. 2011). In KIDA, the reference temperature T₀ is fixed at 300 K (Hébrard et al. 2009).

More details on how to use, choose, and specify uncertainty representations in KIDA, notably for data providers, are given in http://kida.obs.u-bordeaux1.fr/help/helpUncert.html.

In order to be able to interact effectively with KIDA, users need to first register by providing an e-mail address and a password. They will then have access to a member area where they can submit rate coefficients to KIDA experts and see the history of their downloads. To improve the updating of KIDA, we have designed an online interface to upload data. Any user registered with KIDA can submit rate coefficients (with a temperature range of validity, an uncertainty, and a reference). These data will then be sent to the "super-expert" of the type of reaction, who will then consult his/her experts to see if the data have been correctly included or not. Lists of KIDA super-experts and experts with terms until 2013 are given in http://kida.obs.u-bordeaux1.fr/contact.

It is also possible to download lists of reactions from KIDA using an online form (http://kida.obs.u-bordeaux1.fr/astrophysicist). In this form, the user can select (1) the elements and/or species he/she is interested in, (2) the types of reactions, and (3) the range of temperature. This last choice can be used, for instance, as a filter to remove some of the high-temperature reactions if one is interested in modeling the cold ISM. If no recommended rate coefficients exist in the full range of temperature asked by the user, several rate coefficients for the same reaction may be available in the downloaded file. These reactions are included in the readme file downloaded at the same time, and the user has to deal with them. If rate coefficients are defined over complementary ranges of temperature, the user may want to keep them and take this information into account in the model (see Section 3.1). Temperature ranges are indicated in the network along with the status of the KIDA recommendation (see Section 2.3). In any case, we do not recommend the extrapolation of rate coefficients outside this range. If this procedure must be undertaken, we recommend instead using the results at the relevant extremum of temperature or consulting an expert or super-expert from the KIDA lists.

For each reaction, KIDA stores up to three reactants, up to five products, the values of the kinetic parameters A, B, and C, the uncertainty parameters F₀, g and the type of uncertainty, the temperatures T_min and T_max, which define the range of temperatures over which the rate coefficient is defined, the name of the formula used to compute the rate coefficient or the external UV field used to compute the photoinduced rates, the number of the reaction in the network, another number that represents a particular choice of A, B, and C when more than one possibility has been included, and a numerical recommendation given by KIDA experts and discussed in the next section. When there is no relevant temperature range, −9999 and 9999 default values are used for the minimum and maximum temperatures.

The numerical code Nahoon is publicly available on KIDA to compute the gas-phase chemistry for astrophysical objects (http://kida.obs.u-bordeaux1.fr/models/). The program is written in Fortran 90 and uses the DLSODES (double precision) solver from the ODEPACK package (http://www.netlib.org/odepack/opkd-sum) to solve the coupled stiff differential equations. The solver computes the chemical evolution of gas-phase species at a fixed temperature and density (commonly referred to as zero dimension, or 0D) but can be used in one dimension (1D) if a grid of temperature, density, and visual extinction is provided. Nahoon is formatted to read chemical networks downloaded from KIDA. It contains a test to check the temperature range of the validity of the rate coefficients and avoid extrapolations outside this range. A test is also included to check for duplication of chemical reactions, defined over complementary ranges of temperature. In that case, Nahoon chooses the recommended rate coefficient. Some reactions, although important for the ISM, are not included in KIDA such as H₂ formation on grains or recombination of cations with negatively charged grains. These reactions are, however, provided in a set of user instructions associated with Nahoon. This code represents a new version of the one that was put online in 2007 (Wakelam & Herbst 2008). Grains, both neutral and negatively charged, and electrons are considered as chemical species and their concentrations are computed at the same time as those of the other species.

KIDA is a non-selective database. It may not be easy for all users to select the most appropriate list of reactions. For this reason, we will release every year a standard list of reactions for the dense ISM between 10 and 300 K. This network will be available on the same page as Nahoon (http://kida.obs.u-bordeaux1.fr/models). To treat the formation of molecular hydrogen on granular surfaces, the OSU database uses the approximation from Hollenbach & Salpeter (1971), which neglects any details of the process, and contains the assumption that the formation rate of H₂ is equal to 1/2 the collision rate of H atoms with grains (see also Leung et al. 1984). This approximation can induce some numerical problems during the computation because the elemental abundance of hydrogen is not rigorously conserved by the rather complex procedure used by the authors of the code. Rather than improving the procedure, we use a simplified version of the more detailed approach in gas-grain models (Hasegawa et al. 1992). In particular, we have divided the H₂ formation into two reactions and included another species JH, which refers to hydrogen atoms on grains. The first reaction is the sticking of atomic hydrogen onto grains (neutral or negatively charged): H → JH.

The rate of this reaction (in cgs units of cm⁻³ s⁻¹) is

$$\begin{equation} R_{{\rm H, acc}} = \pi a^2 \sqrt{\frac{8 k T}{\pi m_{\rm H}}} n_d n({\rm H}) \end{equation} \tag{ 8 }$$

with a the radius of grains (in cm), k the Boltzmann constant, m_H the atomic mass of hydrogen, n_d the total density of grains, T(K) the temperature, and n(H) the density of atomic hydrogen. For 0.1 μm radius grains, the rate is $7.92\times 10^{-5} \sqrt{T/300} n_d n({\rm H})$.

The second reaction is the formation of H₂ on grains: JH + JH → H₂. We assume here that H₂ formed on grains is directly released in the gas phase. Since desorption of JH is not included, the process has an efficiency of 100%. The rate of this reaction is given by the expression

$$\begin{equation} R_{{\rm H_2, form}} = \frac{ \nu _0 \exp {(-E_b/kT)}}{N_s n_d}n({\rm JH})^2 \end{equation} \tag{ 9 }$$

with N_s the number of binding sites on a grain, ν₀ the characteristic or trial vibrational frequency, and E_b the potential energy barrier between two adjacent surface potential wells.

A useful approximate formula is $\nu _0 = \sqrt{2 n_s E_D k_B/ (\pi m_{\rm H})}$ (Tielens & Allamandola 1987), where n_s is the surface density of sites on a grain in cm⁻² and E_D is the adsorption energy of H in erg. The reader can find a detailed explanation in Hasegawa et al. (1992) and Semenov et al. (2010). Assuming grains of 0.1 μm radius, the number of sites per grain of 10⁶ (Hasegawa et al. 1992), E_D/k = 450 K, and E_b/k = 225 K, n_s is 7.96 × 10¹⁴ cm⁻², ν₀ is 4.32 × 10¹² s⁻¹, and the rate of H₂ formation is 8.64 × 10⁶exp (− 225/T)n(JH)²/n_d cm³ s⁻¹. See Garrod & Herbst (2006) for a discussion concerning the values of E_D and E_b, which depend upon the surface. The value of n_d should obey the constraint that πa² n_d ≈ (1–2) × 10⁻²¹n_H, so that here n_d ≈ 5 × 10⁻¹²n_H, where a is the granular radius and n_H is the total hydrogen nuclear density.

The second class of processes involves electron attachment to grains and the recombination of cations with negatively charged grains. Rate coefficients for such processes can be obtained in the ballistic approximation from the following equation:

$$\begin{equation} k_{{\rm coll}} = \pi a^2 \sqrt{\frac{8 k T}{\pi m_i}}, \end{equation} \tag{ 10 }$$

where m_i is the mass (g) of the impacting species (electrons or ions). We make the approximation that the mass of the impactor is negligible compared to the grain mass, so that the reduced mass is then approximately the mass of the lighter collider. For collisions between two charged species (cations and negatively charged grains), this rate can be multiplied by (1 + Ze²/akT) to account for the Coulomb attraction, with e the elemental electronic charge and Z the number of negative charges on the grain (Weisheit & Upham 1978). It is typically assumed, however, that, in dense clouds, grains can be neutral or singly negatively charged only, reflecting the possibility that the trajectory of an electron nearing a negatively charged grain is repulsive. Following Leung et al. (1984), we neglect any surface electronic charge, based on the assumption that the negative charge/charges on a grain remain localized so the additional factor does not play an important role in the dynamics of the recombination with cations. If the negative charges on a grain were delocalized, then the Coulomb interaction should be included. We have listed in Table 3 the minimum set of reactions with grains that should be included in a network for dense clouds. The rate coefficients (cm³ s⁻¹) for these processes are computed from the A and B listed in the table using the equation k = A(T/300)^B, where A is obtained for a grain radius of 0.1 μm and B = 0.5. For grains of different radii, the ballistic rate coefficients simply scale as the square of the radius. The referee has noted correctly that reactions involving gaseous ions and neutral grains are not included in the KIDA network. They are not included because the only reactive gas-grain processes in the network involve charge neutralization of negatively charged grains.

In the ISM, molecules can be dissociated by absorption of UV photons via electronic continua or through lines. The photodissociation of the dominant species H₂ and CO is dominated by line absorption (although the mechanisms are different) so that H₂ and CO self-shielding is an important process. To avoid a detailed treatment of radiative transfer, we adopted the approximation from Lee et al. (1996), which gives H₂ and CO photodissociation rates as a function of A_v, as well as the H₂ and CO column densities. To include self-shielding, the user of Nahoon has to set the conditions at the border of the cloud, including the abundances of H₂ and CO even when working in 0D. In 1D, a plane parallel geometry is assumed and the UV photons enter the cloud from one direction. Photodissociation rates at a spatial point are then computed using the column densities of H₂ and CO according to the computed abundances and physical structure in front of this point. The visual extinction is then computed using the H₂ column density and the standard ratio between this column density and visual extinction. This geometry is not correct for clouds where UV photons can penetrate from both sides of the cloud. Note that new shielding functions have been published by Visser et al. (2009) and will be included in Nahoon in the future.

In addition to these processes, which are downloaded with the new Nahoon, we have downloaded our first annual network of gas-phase chemical reactions necessary to compute the chemistry in the ISM where the temperature is between 10 and 300 K and where surface chemistry is not critical. Approximations for the depth-dependent photodissociation rates are valid for A_v above 5 (van Dishoeck 1988). The full network, designated kida.uva.2011, and the associated list of species are available at http://kida.obs.u-bordeaux1.fr/models. This list contains 6090 reactions involving 474 species, including neutral and negatively charged grains, as well as electrons. Elements that are included are H, He, C, N, O, Si, S, Fe, Na, Mg, Cl, P, and F. Anionic chemistry from Harada & Herbst (2008) has also been included. For temperatures in the range 300 K–800 K, modelers can use the high-temperature OSU network osu-09-2010-ht, found and discussed on the URL http://www.physics.ohio-state.edu/~eric/research.html.

Using uncertainty information in chemical modeling is vital, notably for the extreme environments targeted by KIDA, where many reaction rate coefficients are known with little accuracy, either estimated or extrapolated. Uncertainty management has two goals:

• 1.  
  Uncertainty propagation. To estimate the precision of the model outputs; and
• 2.  
  Sensitivity analysis. To identify key reactions, i.e., those contributing notably to the uncertainty of model outputs and for which better experimental or theoretical estimations are needed (Dobrijevic et al. 2010).

Improvement of data in KIDA is based on an iterative strategy involving uncertainty propagation and sensitivity analysis (Wakelam et al. 2010b).

The interstellar chemical model defined by both the numerical program Nahoon and the osu.uva.2011 network takes into account a limited number of processes, which makes its use valid only over a limited range of temperature, density, and visual extinction. This model is meant to compute the gas-phase chemistry in regions where the visual extinction is larger than ≈3–4. For smaller A_v, detailed PDR codes, such as the Meudon code (Le Petit et al. 2009), are more appropriate. Also, this model does not take into account positively charged grains, which play a major role at low extinction. The temperature limit is set by the network to the range 10–300 K, as already discussed. For higher temperatures, one should adapt an expanded gas-phase network developed by Harada et al. (2010), which can be utilized up to gas temperatures of 800 K. The accretion timescale onto grains of radius 0.1 μm is roughly 10⁹/n_H(cm⁻³) yr. At times larger than this, the gas phase can be significantly depleted of heavy species if the temperature lies below the evaporation temperature of easily vaporized species such as CO and CH₄. At lower temperatures, non-thermal desorption mechanisms, such as photodesorption, can still maintain a residual gas phase. Models including interactions with grains and grain surface processes (Garrod et al. 2007) are, however, based on many uncertain processes. In addition their use and the analysis of the results are more difficult. For this reason, pure gas-phase models can still be useful even for dense cloud conditions but users have to be careful when they compare their results with observations.

The computation of H₂ formation on grains and the recombination of negative grains with cations, presented here, depend on the size of the grains. We have computed the rate coefficients for these processes for a single grain size of 0.1 μm, which with a typical grain density of 2.5 g cm⁻³ can explain observed extinctions with a gas-to-dust mass ratio of about 0.01, a reasonable value considering heavy elemental depletions in diffuse clouds (Tielens 2005). The effects of using a detailed grain size distribution on the rates of surface processes and on the chemical results for a full gas-grain model can be found in Acharyya et al. (2011); these authors included grains large enough to have a constant rather than stochastic temperature and used a variety of size distributions (Weingartner & Draine 2001; Mathis et al. 1977). They found little effect on the overall chemical results for a cold core with the OSU gas-grain network. The relationship between granular size and rates of assorted processes is a complex one, because the rates can depend upon a number of parameters in addition to surface area, such as whether the system lies in the accretion or diffusion limit and, for cold dense cores, the depth of the ice mantle.

The temperature dependence of the rate of H₂ formation on grains is a rather complex issue and depends strongly on how rough the dust surface is and the availability of chemisorption sites, both of which can allow the process to continue up to much higher temperatures than the standardly assumed Langmuir–Hinshelwood mechanism based on physisorption on smooth surfaces (Cuppen & Herbst 2005; Cazaux & Tielens 2010). The net result is that for systems with both physisorption and chemisorption sites, the efficiency of H₂ formation can remain high at all relevant interstellar dust temperatures, although this result is not guaranteed. For small particles, in which the temperature is stochastic, the situation is more complex but has also been studied via Monte Carlo techniques (Cuppen et al. 2006). For dust particles with well-defined temperatures up to 50 K, the physisorption mechanism assumed here should be adequate for rough particles.

Finally, despite their possible impact on the interstellar chemistry of cold dense cores, as shown by Wakelam & Herbst (2008), polycyclic aromatic hydrocarbons are not included in this model because of the strong uncertainties that still remain (1) on the size and abundance of these species in dense regions and (2) on their reactions with other species.

To compare the abundances computed with the kida.uva.2011 network and other public networks, we have considered the case of dark molecular clouds using Nahoon in 0D. The temperature is set to 10 K, the proton density to 2 × 10⁴ cm⁻³, the total H₂ cosmic-ray ionization to 1.3 × 10⁻¹⁷ s⁻¹, and the visual extinction to 30. Initial abundances are taken from Wakelam et al. (2010a). The results for selected molecular abundances, as computed with the kida.uva.2011 list of reactions, are displayed in Figure 1 with the results of the uncertainty propagation of rate coefficients. For comparison, abundances computed using the udfa06 network (http://www.udfa.net/) and osu-01-2009 network (http://www.physics.ohio-state.edu/~ric/research.html) are also included. Contrary to the publicly available udfa06 network, the OSU network used also contains anions.

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The particular molecular abundances plotted have been selected because they show some variation in their abundances with the database used. The OSU and kida.uva networks lead to similar results since KIDA is mainly based on the OSU compilation although a number of updates have been performed. Abundances computed with udfa06 on the contrary can be different, as shown especially for CS and the cations in Figure 1. Model predictions done with the different networks are however within the 2σ error bars computed from the uncertainty propagation of rate coefficients, which are typically an order of magnitude in both directions.

Original references for kinetic data in KIDA are: Adams & Smith (1976, 1984), Amano (1990), Anicich & Huntress (1986), Anicich et al. (1976), Antipov et al. (2009), Atkinson et al. (2004), Chenel et al. (2010), Barckholtz et al. (2001), Barlow & Dunn (1987), Baulch et al. (2005), Becker et al. (1989, 2000), Bedjanian et al. (1999), Bergeat et al. (2009), Berkowitz et al. (1986), Berteloite et al. (2010a, 2010b), Bettens et al. (1999), Bettens & Herbst (1995), Bohme et al. (1988), Brown et al. (1983), Brownsword et al. (1997, 1996), Canosa et al. (1997), Carty et al. (2006), Chabot et al. (2010), Costes et al. (2009), Daugey et al. (2005), Davidson & Hanson (1990), Deeyamulla & Husain (2006), Defrees & McLean (1989), Derkatch et al. (1999), Dorthe et al. (1991), Duff & Sharma (1996), Ehlerding et al. (2004), Eichelberger et al. (2007), Fehsenfeld et al. (1975), Gamallo et al. (2006), Geppert et al. (2000, 2004a, 2004b), Grebe & Homann (1982), Gredel et al. (1989), Gu et al. (2006), Sun & Li (2004), Harada & Herbst (2008), Herbst (1985, 1987); Herbst et al. (1989a, 1989b, 2000), Jensen et al. (2000), Kaiser et al. (2002), Kalhori et al. (2002), Lee et al. (1978), Lilenfeld & Richardson (1977), Lique et al. (2009), Loison & Bergeat (2009), Marquette et al. (1988), Martinet et al. (2004), Martinez et al. (2008, 2010), Mayer et al. (1967), McGowan et al. (1979), Mebel & Kaiser (2002), Messing et al. (1980), Millar & Herbst (1990), Montaigne et al. (2005), Neufeld et al. (2005), Ozeki et al. (2004), Parisel et al. (1996), Prasad & Huntress (1980), Huo et al. (2011), Sablier & Fujii (2002), Sander et al. (2011), Shin & Beauchamp (1986), Sims et al. (1994), Smith & Adams (1981), Smith (1989), Smith et al. (2001), Snow et al. (2009), Stevens et al. (2010), Talbi & Smith (2009), Thorne et al. (1983, 1984), Tuna et al. (2008), van Dishoeck et al. (2006), van Dishoeck (1988), Van Harrevelt et al. (2002), van Hemert & van Dishoeck (2008), Vazquez et al. (2009), Viggiano et al. (2005), Vinckier (1979), Vroom & de Heer (1969), Wakelam et al. (2009), Wennberg et al. (1994), Woon & Herbst (2009), and Zabarnick et al. (1989).