Extended cross correlation (XCC), originally implemented by Professor Robert Field at MIT, is an analytical technique that extracts subgroups of related data to provide separated spectra for different species. XCC correlates the intensities of peaks between two spectra recorded with one varying experimental parameter in order to identify patterns of transitions for which this variation leads to similar changes in intensities. Efficiently analyzing the components of complex mixtures has many different applications, such as determination of impurities that may result during pharmaceutical synthesis. This project investigated automation of the XCC method by implementing programming in Mathcad, Python, and Excel. The developed XCC tools were applied to spectra of clusters containing 1,1-difluoroethylene and CO2. The separation of experimental microwave spectroscopy data for different sized clusters, when comparing spectra recorded with varying CO2 concentrations, was probed.

Implementing extended cross correlation as a tool to identify patterns in microwave spectra, and its application to fluoroethylene/CO2 clusters

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.