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High-Performance Liquid Chromatography (HPLC) and Gas Chromatography are analytical techniques which allow for the quantitative characterization of the chemical components of mixtures. Technological advancements in sample preparation and mechanical automation have allowed HPLC to become a high-throughput tool which poses new challenges for reproducible and rapid analysis of the resulting chromatograms. Here we present hplc-py, a Python package that permits rapid and reliable quantitation of component signals within a chromatogram for pipelined workflows. This is achieved by a signal detection and quantitation algorithm which i) identifies windows of time which contain peaks and ii) infers the parameters of a mixture of amplitude-weighted skew-normal distributions which sum to reconstruct the observed signal. This approach is particularly effective at deconvolving highly overlapping signals, allowing for precise absolute quantitation of chemical constituents with similar chromatographic retention times.
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Online sensing of palladium in flowing streams
Rapid palladium (Pd) catalyzed deallylation of an uncoloured reagent within a flowing stream affords a dose dependent colour formation that can be used for convenient online analysis of trace levels of Pd contamination using a modified HPLC instrument. An application to the online sensing of Pd breakthrough from a flow through Pd adsorption cartridge is described. An alternative configuration of the instrumentation allows the rapid (<1 min) and accurate measurement of Pd levels within samples injected via a conventional HPLC autosampler.
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- Award ID(s):
- 1506942
- PAR ID:
- 10283981
- Date Published:
- Journal Name:
- Chemical Communications
- Volume:
- 53
- Issue:
- 4
- ISSN:
- 1359-7345
- Page Range / eLocation ID:
- 720 to 723
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1039/c6cc08562h
