The computational study of the formation and growth of atmospheric aerosols requires an accurate Gibbs free energy surface, which can be obtained from gas phase electronic structure and vibrational frequencies. These quantities are valid for only those atmospheric clusters whose geometries correspond to a minimum on the potential energy surface of that particular cluster. The Gibbs free energy of the minimum energy structure can be used to predict atmospheric concentrations of the cluster under a variety of conditions such as altitute and humidity level. We present a computationaly-inexpensive procedure built on a genetic algorithm-based configurational sampling followed by a series of increasingly-accurate screening calculations. The procedure starts by generating and evolving the geometries of a large set of configurations using semi-empirical models then refines the resulting unique structures at a series of high-level ab intio levels of theory. Finally, thermodynamic corrections are computed for the resulting set of minimum-energy structures and used to compute the Gibbs free energies of formation, equilibrium constants, and atmospheric concentrations. We present the application of this procedure to the study of the nucleation of atmospheric aerosols on various inorganic and organic molecules in the atmosphere. Specifically, we present our results for the computation of the atmospheric content of hydrated amino acids.

Configurational sampling based on a genetic algorithm applied to the study of hydrated amino acids in the atmosphere

Macromolecular Chemistry: The Second Century

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ACS Spring 2020 National Meeting & Expo

The official archive and repository for all ACS Meetings & Expositions abstracts and select posters or presentations.