Quantification of the Role of Chemical Desorption in Molecular Clouds

Abstract

ConspectusDark molecular clouds have low temperatures of approximately 10 K and experience very little UV irradiation. These clouds are the birthplace of new stars and consist of gas and dust particles. The latter can act as a meeting place to facilitate surface chemistry to form saturated molecules such as formaldehyde, methyl formate, and dimethyl ether. These complex organic molecules or COMs become encapsulated in the ice that forms on the dust grains, and these ices are the precursor for cometary ices and other icy bodies. They likely played a role in bringing material to the early earth.Although these COMs are likely formed on the surfaces of dust grains, several of them have been detected in the gas phase. This means that they have desorbed from the grain under these cold, dark conditions where thermal desorption and photodesorption are negligible. It has been speculated that reactive, or chemical, desorption is responsible for the high gas-phase abundance. After a surface reaction, its products might be vibrationally, translationally, and/or rotationally excited. Dissipation of the excess energy to translational energy can briefly increase the desorption rate, leading to chemical desorption. Astrochemical modellers have added terms to their rate equations to account for this effect. These terms, however, have had little experimental or theoretical verification.In this Account, we use classical molecular dynamics (MD) simulations to give adsorbed molecules a fixed amount of energy as a proxy for excess energy and to record whether this leads to desorption. The excitation energy can be varied freely while keeping all other variables constant. This allows for the study of trends rather than being limited to a single reaction and a single system. The focus is on the dependence of the chemical desorption on the excitation energy, excitation type, and binding energy. Rotational and vibrational excitation was explicitly taken into account. An analytical expression for the chemical desorption probability was obtained in this way. It depends on the binding energy and reaction enthalpy. This expression was then implemented in a gas-grain astrochemical code to simulate the chemical evolution of a dark molecular cloud, and the results were compared against observational abundances of COMs in three different molecular clouds. The results with our new expression based on the MD simulations show good agreement for all species except H₂CO, which has both gas-phase and surface-formation routes. This is a significant improvement over models without chemical desorption or with other expressions for chemical desorption, as frequently used by other authors. It is encouraging to see that a general description with a firmer theoretical basis leads to a significant improvement. Understanding chemical desorption can help to explain the unexpectedly high gas-phase abundance of some COMs, and chemical desorption also provides a link between the gas phase and the ice mantle, and its understanding might help in creating a diagnostic tool to learn more about the ice composition.

Figure 1

Desorption probability of the three admolecules (CO₂, H₂O, and CH₄) as a function of the additional energy. Each curve represents a different set of simulations with a different type of energy contribution. The red, yellow, and green curves are for pure translational, rotational, or vibrational excitation, respectively. The two blue curves represent simulations of translational energy in combination with 1 eV of either vibrational or rotational energy that has been put into the molecule. The purple curve represents simulations where a total of 5 eV is given to the admolecule in a combination of rotational and vibrational excitation. Here the additional rotational energy is used on the x axis instead of the additional total energy to distinguish the simulations. The dashed line represents eq 1.

Figure 2

Time evolution of the abundances of selected species in the gas phase (left panels) and on the grain surface (right panels) for three simulations with χ₁ = 0.05, 0.1, and 0.2. The value for χ₂ is set to 0.2 for all simulations, and only phase 2 is shown.