This will be a 1 hour Zoom webinar as part of the RSC Process Chemistry and Technology group's monthly webinar programme.
The productive use of automation and data science to accelerate chemical synthesis and optimization remains inhibited by severe integration and interoperability constraints. High-performance liquid chromatography (HPLC) is ubiquitously used to analyze chemical reactions, yet the generated data remains locked in vendors’ hardware and software components, thus limiting their potential in automated workflows and data science applications. This webinar presents MOCCA: an open-source Python package that provides a comprehensive set of features for the analysis of HPLC–DAD (photodiode array detector) raw data. We show how it can be used in automated workflows and how it introduces FAIR data principles to everyday chemistry laboratories - and how it can contribute to more harmonized data landscapes within organizations.
The productive use of automation and data science to accelerate chemical synthesis and optimization remains inhibited by severe integration and interoperability constraints. High-performance liquid chromatography (HPLC) is ubiquitously used to analyze chemical reactions, yet the generated data remains locked in vendors’ hardware and software components, thus limiting their potential in automated workflows and data science applications. This webinar presents MOCCA: an open-source Python package that provides a comprehensive set of features for the analysis of HPLC–DAD (photodiode array detector) raw data. We show how it can be used in automated workflows and how it introduces FAIR data principles to everyday chemistry laboratories - and how it can contribute to more harmonized data landscapes within organizations.
