Agro-waste shaped porous Al2O3/Ni composites: Corrosion resistance performance and artificial neural network modelling

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dc.contributor.authorDele-Afolabi, T. T.
dc.contributor.authorHanim, M. A. Azmah
dc.contributor.authorNorkhairunnisa, M.
dc.contributor.authorSobri, S.
dc.contributor.authorCalin, R.
dc.contributor.authorIsmarrubie, Z. N.
dc.date.accessioned2020-06-25T18:29:31Z
dc.date.available2020-06-25T18:29:31Z
dc.date.issued2018
dc.departmentKırıkkale Üniversitesi
dc.descriptionTemitope, Dele-Afolabi/0000-0003-0187-9208; Sobri, Shafreeza/0000-0002-5675-2186
dc.description.abstractIn the present study, an analysis on the combined effect of nickel (Ni) reinforcement and pore former type in characterizing the corrosion behavior of composite porous alumina ceramics was performed. In order to showcase the potential of the new porous ceramics, pore-forming agents (PFAs) from rice husk (RH) and sugarcane bagasse (SCB) were used in shaping the plain and composite porous alumina samples having sample formulation of Al2O3-xNi-PFA; x = 0, 2, 4, 6 and 8 wt%. Results showed that the emergence of a highly stable Ni3Al2SiO8 spinelloid phase in the RH-graded composites enhanced their chemical stability in the corrosive mediums (10 wt% NaOH and 20 wt% H2SO4) relative to the plain and the corresponding SCB-graded counterparts. An artificial neural network (ANN) model has been developed for predicting the corrosion behavior of the plain and composite porous alumina ceramics based on the experimental data. The developed ANN model satisfactorily predicted the percent mass losses of the porous ceramics in strong alkali and strong acid solutions with coefficient of determination (R-2) of approximately 0.99.en_US
dc.description.sponsorshipResearch Management Center of Universiti Putra Malaysia [GP-IPS/2016/9486500]; Department of Metallurgy and Materials Engineering, Kirikkale University, Turkey [2016/44]en_US
dc.description.sponsorshipThe authors are thankful to the Research Management Center of Universiti Putra Malaysia for providing financial support (GP-IPS/2016/9486500) to carry out this research study. The authors also acknowledge the Department of Metallurgy and Materials Engineering, Kirikkale University, Turkey for the ongoing partnership, financial support (project number of 2016/44) and fruitful feedback.en_US
dc.identifier.citationclosedAccessen_US
dc.identifier.doi10.1016/j.matchar.2018.05.026
dc.identifier.endpage85en_US
dc.identifier.issn1044-5803
dc.identifier.issn1873-4189
dc.identifier.scopus2-s2.0-85047405613
dc.identifier.scopusqualityQ1
dc.identifier.startpage77en_US
dc.identifier.urihttps://doi.org/10.1016/j.matchar.2018.05.026
dc.identifier.urihttps://hdl.handle.net/20.500.12587/7353
dc.identifier.volume142en_US
dc.identifier.wosWOS:000440527300010
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier Science Incen_US
dc.relation.ispartofMaterials Characterization
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectPorous aluminaen_US
dc.subjectCompositesen_US
dc.subjectAgro-waste PFAen_US
dc.subjectCorrosion resistanceen_US
dc.subjectANN modellingen_US
dc.titleAgro-waste shaped porous Al2O3/Ni composites: Corrosion resistance performance and artificial neural network modellingen_US
dc.typeArticle

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