Kinetic analysis for catalytic co-pyrolysis of palm kernel shell and plastic waste mixtures with bifunctional HZSM-5 and mussel shell catalyst
The present study is dedicated to investigate the kinetic analysis for catalytic co-pyrolysis of palm kernel shell (PKS) and polyethylene waste (HDPE) mixtures with bifunctional HZSM-5 and mussel shell (MS) catalyst. Artificial neural network (ANN) modeling through 17 models based on the functions o...
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description | The present study is dedicated to investigate the kinetic analysis for catalytic co-pyrolysis of palm kernel shell (PKS) and polyethylene waste (HDPE) mixtures with bifunctional HZSM-5 and mussel shell (MS) catalyst. Artificial neural network (ANN) modeling through 17 models based on the functions of reaction mechanism denoted as chemical reactions, diffusion reactions, nucleation and growth reactions, interfacial phase reactions and power law reactions was used in this study to achieve a suitable order of reaction promoting higher rate of accuracy based on the data achieved. It was found that the 2
nd
order,
3rd
order, anti jander, jander and ginsling were selected as the suitable models out of 17 reaction mechanism kinetic models due to the giving a positive values produced. And also, it was observed that 3
rd
order reaction mechanism model provided higher activation energy (
E
A
) and
A
values for all feedstock used. Comparison between experimental data and predicted data using Logsig-Tansig (LT) and Tansig-Tansig (TT) were carried out and it was observed that the predicted results from ANN showed similar trend as experimental data with minimal error of 0.67%, 6.61%, and 2.46% for PKS, HDPE, and mixture of PKS and HDPE with the presence of MS and HZSM-5 catalyst, respectively. From the kinetic analysis,
E
A
and
A
value of PKS, HDPE, and of PKS and HDPE with the presence of bifunctional of HZSM-5/MS catalyst are 196.93 kJ/mol, 388.00 kJ/mol, 147.12 kJ/mol, 3.24×1013 s
-1
, 6.00×1026 s
-1
, and 1.72×10-1 s
-1
, respectively. |
doi_str_mv | 10.1088/1757-899X/1257/1/012016 |
format | Article |
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nd
order,
3rd
order, anti jander, jander and ginsling were selected as the suitable models out of 17 reaction mechanism kinetic models due to the giving a positive values produced. And also, it was observed that 3
rd
order reaction mechanism model provided higher activation energy (
E
A
) and
A
values for all feedstock used. Comparison between experimental data and predicted data using Logsig-Tansig (LT) and Tansig-Tansig (TT) were carried out and it was observed that the predicted results from ANN showed similar trend as experimental data with minimal error of 0.67%, 6.61%, and 2.46% for PKS, HDPE, and mixture of PKS and HDPE with the presence of MS and HZSM-5 catalyst, respectively. From the kinetic analysis,
E
A
and
A
value of PKS, HDPE, and of PKS and HDPE with the presence of bifunctional of HZSM-5/MS catalyst are 196.93 kJ/mol, 388.00 kJ/mol, 147.12 kJ/mol, 3.24×1013 s
-1
, 6.00×1026 s
-1
, and 1.72×10-1 s
-1
, respectively.</description><identifier>ISSN: 1757-8981</identifier><identifier>EISSN: 1757-899X</identifier><identifier>DOI: 10.1088/1757-899X/1257/1/012016</identifier><language>eng</language><publisher>Bristol: IOP Publishing</publisher><subject>Artificial neural networks ; Catalysts ; Chemical reactions ; High density polyethylenes ; Kernels ; Mixtures ; Nucleation ; Pyrolysis ; Reaction mechanisms</subject><ispartof>IOP conference series. Materials Science and Engineering, 2022-10, Vol.1257 (1), p.12016</ispartof><rights>Published under licence by IOP Publishing Ltd</rights><rights>Published under licence by IOP Publishing Ltd. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c2576-5cb0d7bb7090826b66f3d94cc735b650156df87d2b34e98f4becc2371a5466503</citedby><cites>FETCH-LOGICAL-c2576-5cb0d7bb7090826b66f3d94cc735b650156df87d2b34e98f4becc2371a5466503</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://iopscience.iop.org/article/10.1088/1757-899X/1257/1/012016/pdf$$EPDF$$P50$$Giop$$Hfree_for_read</linktopdf><link.rule.ids>314,776,780,27903,27904,38847,38869,53818,53845</link.rule.ids></links><search><creatorcontrib>Kumar, A N</creatorcontrib><creatorcontrib>Chin, B L F</creatorcontrib><creatorcontrib>Chee, A L K</creatorcontrib><title>Kinetic analysis for catalytic co-pyrolysis of palm kernel shell and plastic waste mixtures with bifunctional HZSM-5 and mussel shell catalyst</title><title>IOP conference series. Materials Science and Engineering</title><addtitle>IOP Conf. Ser.: Mater. Sci. Eng</addtitle><description>The present study is dedicated to investigate the kinetic analysis for catalytic co-pyrolysis of palm kernel shell (PKS) and polyethylene waste (HDPE) mixtures with bifunctional HZSM-5 and mussel shell (MS) catalyst. Artificial neural network (ANN) modeling through 17 models based on the functions of reaction mechanism denoted as chemical reactions, diffusion reactions, nucleation and growth reactions, interfacial phase reactions and power law reactions was used in this study to achieve a suitable order of reaction promoting higher rate of accuracy based on the data achieved. It was found that the 2
nd
order,
3rd
order, anti jander, jander and ginsling were selected as the suitable models out of 17 reaction mechanism kinetic models due to the giving a positive values produced. And also, it was observed that 3
rd
order reaction mechanism model provided higher activation energy (
E
A
) and
A
values for all feedstock used. Comparison between experimental data and predicted data using Logsig-Tansig (LT) and Tansig-Tansig (TT) were carried out and it was observed that the predicted results from ANN showed similar trend as experimental data with minimal error of 0.67%, 6.61%, and 2.46% for PKS, HDPE, and mixture of PKS and HDPE with the presence of MS and HZSM-5 catalyst, respectively. From the kinetic analysis,
E
A
and
A
value of PKS, HDPE, and of PKS and HDPE with the presence of bifunctional of HZSM-5/MS catalyst are 196.93 kJ/mol, 388.00 kJ/mol, 147.12 kJ/mol, 3.24×1013 s
-1
, 6.00×1026 s
-1
, and 1.72×10-1 s
-1
, respectively.</description><subject>Artificial neural networks</subject><subject>Catalysts</subject><subject>Chemical reactions</subject><subject>High density polyethylenes</subject><subject>Kernels</subject><subject>Mixtures</subject><subject>Nucleation</subject><subject>Pyrolysis</subject><subject>Reaction mechanisms</subject><issn>1757-8981</issn><issn>1757-899X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>O3W</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNqFkN9KwzAUxoMoOKfPYMArL2qT_knaSxnTiRteTEG8CU2asMx2qUnL3Ev4zKZWJoIguThJzvf7TvIBcI7RFUZZFmKa0iDL8-cQRykNcYhwhDA5AKN953C_z_AxOHFujRChSYJG4ONeb2SrBSw2RbVz2kFlLBRF60_9tTBBs7NmaBkFm6Kq4au0G1lBt5JV5cESNlXhevXWFwlr_d52Vjq41e0Kcq26jWi18QPg7GW5CNIvpu6c25sMA117Co5UUTl59l3H4Olm-jiZBfOH27vJ9TwQ_o8kSAVHJeWcohxlEeGEqLjMEyFonHKSIpySUmW0jHicyDxTCZdCRDHFRZoQ34_H4GLwbax566Rr2dp01r_QsYj6FZEc515FB5WwxjkrFWusrgu7YxixPnzWx8r6iFkfPsNsCN-T8UBq0_xY_09d_kEtltPfOtaUKv4EJVeWYg</recordid><startdate>20221001</startdate><enddate>20221001</enddate><creator>Kumar, A N</creator><creator>Chin, B L F</creator><creator>Chee, A L K</creator><general>IOP Publishing</general><scope>O3W</scope><scope>TSCCA</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>KB.</scope><scope>L6V</scope><scope>M7S</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20221001</creationdate><title>Kinetic analysis for catalytic co-pyrolysis of palm kernel shell and plastic waste mixtures with bifunctional HZSM-5 and mussel shell catalyst</title><author>Kumar, A N ; Chin, B L F ; Chee, A L K</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2576-5cb0d7bb7090826b66f3d94cc735b650156df87d2b34e98f4becc2371a5466503</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Artificial neural networks</topic><topic>Catalysts</topic><topic>Chemical reactions</topic><topic>High density polyethylenes</topic><topic>Kernels</topic><topic>Mixtures</topic><topic>Nucleation</topic><topic>Pyrolysis</topic><topic>Reaction mechanisms</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kumar, A N</creatorcontrib><creatorcontrib>Chin, B L F</creatorcontrib><creatorcontrib>Chee, A L K</creatorcontrib><collection>IOP Publishing Free Content</collection><collection>IOPscience (Open Access)</collection><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>Materials Science Database</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Materials Science Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><jtitle>IOP conference series. Materials Science and Engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kumar, A N</au><au>Chin, B L F</au><au>Chee, A L K</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Kinetic analysis for catalytic co-pyrolysis of palm kernel shell and plastic waste mixtures with bifunctional HZSM-5 and mussel shell catalyst</atitle><jtitle>IOP conference series. Materials Science and Engineering</jtitle><addtitle>IOP Conf. Ser.: Mater. Sci. Eng</addtitle><date>2022-10-01</date><risdate>2022</risdate><volume>1257</volume><issue>1</issue><spage>12016</spage><pages>12016-</pages><issn>1757-8981</issn><eissn>1757-899X</eissn><abstract>The present study is dedicated to investigate the kinetic analysis for catalytic co-pyrolysis of palm kernel shell (PKS) and polyethylene waste (HDPE) mixtures with bifunctional HZSM-5 and mussel shell (MS) catalyst. Artificial neural network (ANN) modeling through 17 models based on the functions of reaction mechanism denoted as chemical reactions, diffusion reactions, nucleation and growth reactions, interfacial phase reactions and power law reactions was used in this study to achieve a suitable order of reaction promoting higher rate of accuracy based on the data achieved. It was found that the 2
nd
order,
3rd
order, anti jander, jander and ginsling were selected as the suitable models out of 17 reaction mechanism kinetic models due to the giving a positive values produced. And also, it was observed that 3
rd
order reaction mechanism model provided higher activation energy (
E
A
) and
A
values for all feedstock used. Comparison between experimental data and predicted data using Logsig-Tansig (LT) and Tansig-Tansig (TT) were carried out and it was observed that the predicted results from ANN showed similar trend as experimental data with minimal error of 0.67%, 6.61%, and 2.46% for PKS, HDPE, and mixture of PKS and HDPE with the presence of MS and HZSM-5 catalyst, respectively. From the kinetic analysis,
E
A
and
A
value of PKS, HDPE, and of PKS and HDPE with the presence of bifunctional of HZSM-5/MS catalyst are 196.93 kJ/mol, 388.00 kJ/mol, 147.12 kJ/mol, 3.24×1013 s
-1
, 6.00×1026 s
-1
, and 1.72×10-1 s
-1
, respectively.</abstract><cop>Bristol</cop><pub>IOP Publishing</pub><doi>10.1088/1757-899X/1257/1/012016</doi><tpages>6</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Artificial neural networks Catalysts Chemical reactions High density polyethylenes Kernels Mixtures Nucleation Pyrolysis Reaction mechanisms |
title | Kinetic analysis for catalytic co-pyrolysis of palm kernel shell and plastic waste mixtures with bifunctional HZSM-5 and mussel shell catalyst |
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