Broadband microwave spectra have been recorded for weakly bound clusters formed from mixtures containing fluoroethylene (FE) or 1,1-difluoroethylene (DFE) and varying percentages of CO2. These clusters serve as simple models for behavior of supercritical CO2 as a solvent. Analysis of changes in rotational transition intensities as CO2 concentration is systematically varied allows identification and assignment of spectra for a multitude of different clusters, with at least 15 species identified in FE/CO2 mixtures, and 4 species so far identified in DFE/CO2 mixtures. Graphical representation of the different transition intensity behaviors facilitates assignment of multiple species from the dense data sets, and forms the basis of methods that may be more widely applied to complex mixtures in industrial or environmental applications. Currently, the biggest challenge of the analysis process is not spectroscopic assignment, but rather determination of the most likely formulae and structures for the identified clusters. This presentation will address visual and quantitative analysis of the data plots to assist in characterization of assigned clusters. Spectroscopic results are combined with rapid, artificial intelligence assisted calculations to estimate the most likely orientations for clusters of a particular composition. The visual aspects of the research process, and the accessibility of coding tools such as Mathcad, Python and even Excel, make this work particularly appropriate to undergraduate students, including those with little or no previous physical chemistry experience.

Investigating the structures of small CO2-containing clusters using graphical approaches to data analysis and artificial intelligence-based optimizations

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.