Owing to its very high intrinsic resolution, structural specificity, and very wide instantaneous frequency bandwidth, rotational spectroscopy is an extremely powerful tool to analyze complex mixtures in which potentially hundreds of distinct chemical species are simultaneously present. With the capability of producing information-rich wideband line spectra now fairly routine in many laboratories, spectral assignment — rather than acquisition itself — is often the rate-limiting step in analysis and discovery. To address this pressing issue, we have developed open-source Python tools to streamline and automate large portions of the assignment procedure. For unassigned spectral features, a powerful set of analysis tools, including double resonance microwave spectroscopy, high-speed fitting algorithms, and structural calculations greatly facilitate identification of their carriers. In this talk, the power of these new tools to analyze a range of mixtures and identify entirely new molecules will be demonstrated. Time permitting, efforts to use machine learning algorithms to accelerate further the speed of analysis and assignment of broadband spectra will be discussed.

Next-generation tools to analyze wideband rotational spectra of complex mixtures

ACS Spring Meeting 2021

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