Towards Implementation of the Many-Body Expansion to Interaction Energies of Large Atmospheric Aerosol Clusters

PAC Gym

The role of aerosols on the global climate is largely unknown; understanding aerosol formation pathways will minimize this uncertainty and provide knowledge for their potential in mitigating global warming. The growth of atmospheric aerosols and cloud droplets in the micrometer range from nanoscale gas phase clusters has been investigated utilizing models based on molecular clusters. With the current canonical supermolecular approach, calculations of interaction energies involve the entire cluster with its 3N degrees of freedom for N electrons, which becomes expensive as the cluster grows. To reduce computational expense while retaining chemical accuracy, the many-body expansion of the interaction energy is ideal. Before implementing the many-body expansion; however, old data needs to be adapted. The aim is to break apart large amounts of data into individual monomers, using a python script to automate the process. This python implementation will extend to the overall method. The overall program, including the automation and the many-body expansion, will use previously calculated genetic algorithm calculations for large clusters to calculate accurate interaction energies for each monomer.