Lorentz Center - Grain-Surface Networks and Data for Astrochemistry from 28 Jul 2014 through 1 Aug 2014
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    Grain-Surface Networks and Data for Astrochemistry
    from 28 Jul 2014 through 1 Aug 2014

 

The 'space' between the stars is far from empty; known as the interstellar medium (ISM), it contains the dust and gas from which stars are ultimately formed. Much of this material resides in large clouds of relatively cold molecular gas; to date, more than 180 different molecules have been detected in these regions, including stable molecules, radicals, cations, and anions. Gas-phase chemical pathways appear inefficient for the production of saturated, pre-biotic species. The available gas-phase mechanisms require high temperatures and/or three-body reactions -- conditions that are not met in cold molecular clouds.

 

As a result, the most recent models of interstellar chemistry also simulate processes that occur on the surfaces of dust grains that permeate the ISM. The grains can act as a third body, facilitating addition reactions that lead to the formation of saturated molecules. The thick icy mantles that coat the grain surfaces may also act as a reservoir of molecular material which can be processed by the heating and irradiation associated with the star-formation process. A wealth of evidence suggests that dust-grain surface processes are important over a wide range of interstellar conditions and star-formation environments, while models and observations are rapidly advancing to trace this chemical evolution through at least to the protoplanetary disk phase. The new Atacama Large Millimeter/Submillimeter Array (ALMA) will also give us an unprecedented view of prebiotic and biologically-relevant molecules in many different objects over the coming years.

 

Unfortunately, a major stumbling block in our understanding of prebiotic chemistry in the ISM is the lack of a standardised and comprehensive network of surface reactions and corresponding data for use in simulations. In the case of gas-phase chemistry, several databases with reactions and their corresponding rate coefficients exist, of which the UMIST Database for Astrochemistry (UDfA) and the KInetic Database for Astrochemistry (KIDA) are the most widely used. The quality of the data in these databases is regularly reviewed and some consensus on a standardised model has been reached. However, for grain-surface chemistry, this is not the case: modellers often compile their own grain-surface reaction networks and most are not publicly available.

 

Our aim is to standardise the most important chemical and physical data used in the models, for use by all those working in the community. This would include, for example, surface diffusion barriers of reactants, activation energy barriers for key reactions, as well as clearly-defined methods for their implementation in models. Furthermore, the reaction network with its rates does not solely define the grain-surface chemistry, unlike for the gas phase. Adsorption and desorption mechanisms, binding energies of species on the grain, and choices of how to treat the inner layers of the ice mantle, all determine the outcomes of the models. We aim to bring together modellers who will be the end users of the databases and experimentalists and theoretical chemists. The former are able to identify the most critical parameters for use in models, whereas the latter can provide the data which will be contained in the database. The program contains several discussion or break-out sessions to allow us to really produce some initial results and strategies. One of the key questions is how to parameterise experimental or computational results for use in (sometimes necessarily simplified) astrochemical models. The final output of the longer-term project will be a public and user-friendly database, available through the same websites as the databases for gas-phase networks. During this initial workshop we will work towards a general consensus about which information these databases should contain and a detailed strategy to obtain this information.



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