2020
DOI: 10.1080/23311916.2020.1714100
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Optimization and development of predictive models for the corrosion inhibition of mild steel in sulphuric acid by methyl-5-benzoyl-2-benzimidazole carbamate (mebendazole)

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Cited by 30 publications
(12 citation statements)
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“…An inhibitor’s inhibition efficiency is immensely dependent on the inhibitor dosage and immersion time [ 72 ]. Hence, RSM/CCD optimization was performed to determine an optimum value of dosage and immersion time for maximum efficacy of EFB-H. Table 6 demonstrates the preliminary study result.…”
Section: Resultsmentioning
confidence: 99%
“…An inhibitor’s inhibition efficiency is immensely dependent on the inhibitor dosage and immersion time [ 72 ]. Hence, RSM/CCD optimization was performed to determine an optimum value of dosage and immersion time for maximum efficacy of EFB-H. Table 6 demonstrates the preliminary study result.…”
Section: Resultsmentioning
confidence: 99%
“…The detailed experimental design with the graphical plots, mathematical modelling, optimization, analysis of variance (ANOVA), other statistical evaluations, etc. are reported in [ 33 , 34 ]. The following modelled results ( Table 2 ) experimentally validated were obtained, showing the trend of increase in inhibition efficiency with increasing concentrations of the inhibitor.…”
Section: Resultsmentioning
confidence: 99%
“…Any point on the 3D surface plot can be selected to show details about the response prediction at that levels of the factors. The relative interaction of the factors (reinforcement particle sizes and volume fraction) and their magnitude of influence on the properties of the developed composites could be observed by the nature of 3D surface plots [41]. The peak level and design points above the predicted values for each property analyzed lies in the red colour.…”
Section: Numerical and Graphical Optimization Solutionmentioning
confidence: 99%
“…Response surface methodology (RSM), has been successfully utilized among other experimental design and optimization techniques for the predictive modelling and process factor optimization of composite materials [37][38][39]. RSM is a statistical and experimental design tool in which a specified dependent variable or materials property responds to experimental variations in one or more independent process factors [40][41][42][43]. There is little or no researches on the use of hardwood charcoal to improve the tribological and other mechanical properties of wood charcoal-polymer composites [38,44].…”
Section: Introductionmentioning
confidence: 99%