Predicting Ethanol Steam Reforming Products of Au-Cu Supported over Nano-Shaped CeO<sub>2</sub> Using the Johnsen Measure in PLS

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 (CeCO<inline-formula><math xmlns="http://ww...

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Autores principales:	Chen Zhi, Muhammad Tahir, Tahir Mehmood
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	prediction <i>PLS</i> hydrogen fuel environment friendly FTIR spectroscopy Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/ef3c375ec9b34606ac29833d99dfea63
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spelling	oai:doaj.org-article:ef3c375ec9b34606ac29833d99dfea632021-11-11T15:24:00ZPredicting Ethanol Steam Reforming Products of Au-Cu Supported over Nano-Shaped CeO<sub>2</sub> Using the Johnsen Measure in PLS10.3390/app1121104022076-3417https://doaj.org/article/ef3c375ec9b34606ac29833d99dfea632021-11-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/21/10402https://doaj.org/toc/2076-3417Hydrogen 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 (CeCO<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mn>2</mn></msub></semantics></math></inline-formula>) support generate hydrogen (H<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mn>2</mn></msub></semantics></math></inline-formula>) with byproducts such as carbon dioxide (CO<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mn>2</mn></msub></semantics></math></inline-formula>) 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 (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>P</mi><mi>L</mi><mi>S</mi></mrow></semantics></math></inline-formula>) 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 <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>P</mi><mi>L</mi><mi>S</mi></mrow></semantics></math></inline-formula> measures based on the Johnsen index outperform the existing methods for predicting ESR products based on FTIR spectroscopic data. For (H<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mn>2</mn></msub></semantics></math></inline-formula>) conversion percent prediction with cube and polyhedra morphologies, the functional compounds (C-O), (C=O), (CH), and (C-H,=CH<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mn>2</mn></msub></semantics></math></inline-formula>) are common. Similarly, the functional compound (s-RCH=CHR) is frequently used for (H<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mn>2</mn></msub></semantics></math></inline-formula>) conversion percent prediction with polyhedra and rod morphologies. Moreover, on simulated data, the proposed Johnsen measure in <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>P</mi><mi>L</mi><mi>S</mi></mrow></semantics></math></inline-formula> demonstrates higher sensitivity and accuracy. Furthermore, the proposed Johnsen measure in <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>P</mi><mi>L</mi><mi>S</mi></mrow></semantics></math></inline-formula> identifies influential wavenumbers that map over the functional compounds.Chen ZhiMuhammad TahirTahir MehmoodMDPI AGarticleprediction<i>PLS</i>hydrogen fuelenvironment friendlyFTIR spectroscopyTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10402, p 10402 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	prediction <i>PLS</i> hydrogen fuel environment friendly FTIR spectroscopy Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	prediction <i>PLS</i> hydrogen fuel environment friendly FTIR spectroscopy Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Chen Zhi Muhammad Tahir Tahir Mehmood Predicting Ethanol Steam Reforming Products of Au-Cu Supported over Nano-Shaped CeO<sub>2</sub> Using the Johnsen Measure in PLS
description	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 (CeCO<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mn>2</mn></msub></semantics></math></inline-formula>) support generate hydrogen (H<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mn>2</mn></msub></semantics></math></inline-formula>) with byproducts such as carbon dioxide (CO<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mn>2</mn></msub></semantics></math></inline-formula>) 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 (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>P</mi><mi>L</mi><mi>S</mi></mrow></semantics></math></inline-formula>) 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 <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>P</mi><mi>L</mi><mi>S</mi></mrow></semantics></math></inline-formula> measures based on the Johnsen index outperform the existing methods for predicting ESR products based on FTIR spectroscopic data. For (H<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mn>2</mn></msub></semantics></math></inline-formula>) conversion percent prediction with cube and polyhedra morphologies, the functional compounds (C-O), (C=O), (CH), and (C-H,=CH<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mn>2</mn></msub></semantics></math></inline-formula>) are common. Similarly, the functional compound (s-RCH=CHR) is frequently used for (H<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mn>2</mn></msub></semantics></math></inline-formula>) conversion percent prediction with polyhedra and rod morphologies. Moreover, on simulated data, the proposed Johnsen measure in <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>P</mi><mi>L</mi><mi>S</mi></mrow></semantics></math></inline-formula> demonstrates higher sensitivity and accuracy. Furthermore, the proposed Johnsen measure in <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>P</mi><mi>L</mi><mi>S</mi></mrow></semantics></math></inline-formula> identifies influential wavenumbers that map over the functional compounds.
format	article
author	Chen Zhi Muhammad Tahir Tahir Mehmood
author_facet	Chen Zhi Muhammad Tahir Tahir Mehmood
author_sort	Chen Zhi
title	Predicting Ethanol Steam Reforming Products of Au-Cu Supported over Nano-Shaped CeO<sub>2</sub> Using the Johnsen Measure in PLS
title_short	Predicting Ethanol Steam Reforming Products of Au-Cu Supported over Nano-Shaped CeO<sub>2</sub> Using the Johnsen Measure in PLS
title_full	Predicting Ethanol Steam Reforming Products of Au-Cu Supported over Nano-Shaped CeO<sub>2</sub> Using the Johnsen Measure in PLS
title_fullStr	Predicting Ethanol Steam Reforming Products of Au-Cu Supported over Nano-Shaped CeO<sub>2</sub> Using the Johnsen Measure in PLS
title_full_unstemmed	Predicting Ethanol Steam Reforming Products of Au-Cu Supported over Nano-Shaped CeO<sub>2</sub> Using the Johnsen Measure in PLS
title_sort	predicting ethanol steam reforming products of au-cu supported over nano-shaped ceo<sub>2</sub> using the johnsen measure in pls
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/ef3c375ec9b34606ac29833d99dfea63
work_keys_str_mv	AT chenzhi predictingethanolsteamreformingproductsofaucusupportedovernanoshapedceosub2subusingthejohnsenmeasureinpls AT muhammadtahir predictingethanolsteamreformingproductsofaucusupportedovernanoshapedceosub2subusingthejohnsenmeasureinpls AT tahirmehmood predictingethanolsteamreformingproductsofaucusupportedovernanoshapedceosub2subusingthejohnsenmeasureinpls
_version_	1718435403372953600

Predicting Ethanol Steam Reforming Products of Au-Cu Supported over Nano-Shaped CeO<sub>2</sub> Using the Johnsen Measure in PLS

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