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

In 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...

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Published inMaterials characterization Vol. 142; pp. 77 - 85
Main Authors Dele-Afolabi, T.T., Azmah Hanim, M.A., Norkhairunnisa, M., Sobri, S., Calin, R., Ismarrubie, Z.N.
Format Journal Article
LanguageEnglish
Published United States Elsevier Inc 01.08.2018
Subjects
Agro-waste PFA
ALUMINIUM OXIDES
ANN modelling
CERAMICS
COMPOSITE MATERIALS
Composites
COMPUTERIZED SIMULATION
CORROSION
CORROSION RESISTANCE
MASS TRANSFER
MATERIALS SCIENCE
NICKEL
Porous alumina
POROUS MATERIALS
STABILITY
Porous alumina
Corrosion resistance
Composites
ANN modelling
Agro-waste PFA
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Abstract In 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 (R2) of approximately 0.99. •Porous Al2O3/Ni composites were developed with agro-waste pore-forming agents.•The RH and SCB graded composites showed Ni3Al2SiO8 and NiAl2O4 spinels respectively.•Superior chemical stability was demonstrated by the Al2O3-2Ni-RH composite.•The ANN model demonstrated a good performance with R2 value of approx. 0.99.
AbstractList In 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 (R2) of approximately 0.99. •Porous Al2O3/Ni composites were developed with agro-waste pore-forming agents.•The RH and SCB graded composites showed Ni3Al2SiO8 and NiAl2O4 spinels respectively.•Superior chemical stability was demonstrated by the Al2O3-2Ni-RH composite.•The ANN model demonstrated a good performance with R2 value of approx. 0.99.
Highlights: • Porous Al{sub 2}O{sub 3}/Ni composites were developed with agro-waste pore-forming agents. • The RH and SCB graded composites showed Ni{sub 3}Al{sub 2}SiO{sub 8} and NiAl{sub 2}O{sub 4} spinels respectively. • Superior chemical stability was demonstrated by the Al{sub 2}O{sub 3}-2Ni-RH composite. • The ANN model demonstrated a good performance with R{sup 2} value of approx. 0.99. - Abstract: In 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 Al{sub 2}O{sub 3}-xNi-PFA; x = 0, 2, 4, 6 and 8 wt%. Results showed that the emergence of a highly stable Ni{sub 3}Al{sub 2}SiO{sub 8} spinelloid phase in the RH-graded composites enhanced their chemical stability in the corrosive mediums (10 wt% NaOH and 20 wt% H{sub 2}SO{sub 4}) 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{sup 2}) of approximately 0.99.
Author Dele-Afolabi, T.T.
Azmah Hanim, M.A.
Calin, R.
Ismarrubie, Z.N.
Norkhairunnisa, M.
Sobri, S.
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Snippet In the present study, an analysis on the combined effect of nickel (Ni) reinforcement and pore former type in characterizing the corrosion behavior of...
Highlights: • Porous Al{sub 2}O{sub 3}/Ni composites were developed with agro-waste pore-forming agents. • The RH and SCB graded composites showed Ni{sub...
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SubjectTerms Agro-waste PFA
ALUMINIUM OXIDES
ANN modelling
CERAMICS
COMPOSITE MATERIALS
Composites
COMPUTERIZED SIMULATION
CORROSION
CORROSION RESISTANCE
MASS TRANSFER
MATERIALS SCIENCE
NICKEL
Porous alumina
POROUS MATERIALS
STABILITY
Title Agro-waste shaped porous Al2O3/Ni composites: Corrosion resistance performance and artificial neural network modelling
URI https://dx.doi.org/10.1016/j.matchar.2018.05.026
https://www.osti.gov/biblio/22805072
Volume 142
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