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Hydrogen fuel cells have long been regarded as a more environmentally friendly alternative to traditional fossil fuels. Ethanol steam reforming (ESR) is a promising long-term, safe method of producing carbon-neutral hydrogen. ESR products are (CeCO2) support generate hydrogen (H2) with byproducts such as carbon dioxide (CO2) and carbon monoxide (CO). The researchers are interested in the quantification and estimation of syngas components. The current article introduces the Johnsen index-based measure in partial least squares (PLS) for predicting ESR products with cube, polyhydra, and rod morphologies, based on FTIR. The proposed method makes use of existing filter measures such as loading weights, variable importance on projection, and significant correlation. The proposed PLS measures based on the Johnsen index outperform the existing methods for predicting ESR products based on FTIR spectroscopic data. For (H2) conversion percent prediction with cube and polyhedra morphologies, the functional compounds (C-O), (C=O), (CH), and (C-H,=CH2) are common. Similarly, the functional compound (s-RCH=CHR) is frequently used for (H2) conversion percent prediction with polyhedra and rod morphologies. Moreover, on simulated data, the proposed Johnsen measure in PLS demonstrates higher sensitivity and accuracy. Furthermore, the proposed Johnsen measure in PLS identifies influential wavenumbers that map over the functional compounds.

Predicting Ethanol Steam Reforming Products of Au-Cu Supported over Nano-Shaped CeO2 Using the Johnsen Measure in PLS