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

The replacement of fossil carbon sources with green bio-oils promotes the importance several hundred oxygenated hydrocarbons, which substantially increases analytical effort in catalysis research. A multilinear regression is performed to correlate retention indices (RIs) and response factors (RFs) structural properties. model includes a variety possible products formed during hydrodeoxygenation good accuracy (RRF2 0.921 RRI2 0.975). GC parameters are related detailed hydrocarbon analysis (DHA) method, commonly used for non-oxygenated hydrocarbons. RIs determined from paraffin standard (C5–C15), RFs calculated ethanol 1,3,5-trimethylbenzene as internal standards. method presented here can, therefore, be together DHA expanded further. In addition regression, an increment system has been developed aromatic oxygenates, further improves prediction respect molecular constitution (R2 0.958). Both predictive models designed exclusively on ensure effortless application. All experimental under identical conditions. Moreover, folded Plackett–Burman screening design demonstrates general applicability datasets independent method- or device-specific parameters.