Molecular Simulations for the Spectroscopic Detection of Atmospheric Gases
Clara Sousa-Silva, Janusz J Petkowski, Sara Seager

TL;DR
This paper introduces RASCALL, a rapid computational method that generates approximate molecular spectra to aid atmospheric gas detection, addressing the scarcity of complete spectral data for many molecules.
Contribution
The paper presents RASCALL 1.0, a novel approach combining experimental, organic, and quantum data to produce quick, approximate spectra for thousands of molecules, expanding available spectral databases.
Findings
RASCALL 1.0 provides spectra for more molecules than existing databases.
The method estimates band positions and qualitative intensities efficiently.
The spectral catalog is freely accessible and regularly updated.
Abstract
Unambiguously identifying molecules in spectra is of fundamental importance for a variety of scientific and industrial uses. Interpreting atmospheric spectra for the remote detection of volatile compounds requires information about the spectrum of each relevant molecule. However, spectral data currently exist for a few hundred molecules and only a fraction of those have complete spectra (e.g. HO, NH). Consequently, molecular detections in atmospheric spectra remain vulnerable to false positives, false negatives, and missassignments. There is a key need for spectral data for a broad range of molecules. Given how challenging it is to obtain high-resolution molecular spectra, there is great value in creating intermediate approximate spectra that can provide a starting point for the analysis of atmospheric spectra. Using a combination of experimental measurements, organic…
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