Automated processing of chromatograms: a comprehensive python package with a GUI for intelligent peak identification and deconvolution in chemical reaction analysis
Name
d4dd00214h.pdf
Description
Published version
Size
1.97 MB
Format
Adobe PDF
Checksum (MD5)
25a330a46737b7759fc6979023e66421
Author(s)
Obořil, Jan
Haas, Christian P
Lübbesmeyer, Maximilian
Nicholls, Rachel
Gressling, Thorsten
Jensen, Klavs F
Volpin, Giulio
Hillenbrand, Julius
Date Issued
2024
Journal
Digital Discovery
Publisher
Royal Society of Chemistry
Citation
Obořil, Jan, Haas, Christian P, Lübbesmeyer, Maximilian, Nicholls, Rachel, Gressling, Thorsten et al. 2024. "Automated processing of chromatograms: a comprehensive python package with a GUI for intelligent peak identification and deconvolution in chemical reaction analysis." Digital Discovery, 3 (10).
Version
Final published version
Abstract
Reaction screening and high-throughput experimentation (HTE) coupled with liquid chromatography (HPLC and UHPLC) are becoming more important than ever in synthetic chemistry. With a growing number of experiments, it is increasingly difficult to ensure correct peak identification and integration, especially due to unknown side components which often overlap with the peaks of interest. We developed an improved version of the MOCCA Python package with a web-based graphical user interface (GUI) for automated processing of chromatograms, including baseline correction, intelligent peak picking, peak purity checks, deconvolution of overlapping peaks, and compound tracking. The individual automatic processing steps have been improved compared to the previous version of MOCCA to make the software more dependable and versatile. The algorithm accuracy was benchmarked using three datasets and compared to the previous MOCCA implementation and published results. The processing is fully automated with the possibility to include calibration and internal standards. The software supports chromatograms with photo-diode array detector (DAD) data from most commercial HPLC systems, and the Python package and GUI implementation are open-source to allow addition of new features and further development.
MIT Department
Massachusetts Institute of Technology. Department of Chemical Engineering
Terms of Use
Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1039/d4dd00214h
