Prediction of Retention Indices and Response Factors of Oxygenates for GC-FID by Multilinear Regression

Nils Kretzschmar, Markus Seifert, Oliver Busse and Jan J. Weigand ()
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Nils Kretzschmar: Faculty of Chemistry and Food Chemistry, Technische Universität Dresden, 01062 Dresden, Germany
Markus Seifert: Faculty of Chemistry and Food Chemistry, Technische Universität Dresden, 01062 Dresden, Germany
Oliver Busse: Faculty of Chemistry and Food Chemistry, Technische Universität Dresden, 01062 Dresden, Germany
Jan J. Weigand: Faculty of Chemistry and Food Chemistry, Technische Universität Dresden, 01062 Dresden, Germany

Data, 2022, vol. 7, issue 9, 1-12

Abstract: The replacement of fossil carbon sources with green bio-oils promotes the importance of several hundred oxygenated hydrocarbons, which substantially increases the analytical effort in catalysis research. A multilinear regression is performed to correlate retention indices (RIs) and response factors (RFs) with structural properties. The model includes a variety of possible products formed during the hydrodeoxygenation of bio-oils with good accuracy (R RF 2 0.921 and R RI 2 0.975). The GC parameters are related to the detailed hydrocarbon analysis (DHA) method, which is commonly used for non-oxygenated hydrocarbons. The RIs are determined from a paraffin standard (C5–C15), and the RFs are calculated with ethanol and 1,3,5-trimethylbenzene as internal standards. The method presented here can, therefore, be used together with the DHA method and be expanded further. In addition to the multilinear regression, an increment system has been developed for aromatic oxygenates, which further improves the prediction accuracy of the response factors with respect to the molecular constitution (R 2 0.958). Both predictive models are designed exclusively on structural factors to ensure effortless application. All experimental RIs and RFs are determined under identical conditions. Moreover, a folded Plackett–Burman screening design demonstrates the general applicability of the datasets independent of method- or device-specific parameters.

Keywords: response factors; retention indices; gas chromatography (GC); flame ionization detector (FID); detailed hydrocarbon analysis (DHA); oxygenated hydrocarbons; predictive modelling (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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