Optimization and development of predictive models for the corrosion inhibition of mild steel in sulphuric acid by methyl-5-benzoyl-2-benzimidazole carbamate (mebendazole). Issue 1 (1st January 2020)

• Record Type: Journal Article
• Authors: Edoziuno, F. O.; Adediran, A. A.; Odoni, B.U.; Akinwekomi, A.D.; Adesina, O.S.; Oki, M.
• Editors: Brando, Giuseppe
• Is Part Of: Cogent engineering. Volume 7:Issue 1(2020)
• Publication Date: 2020-01-01
• Subjects: mebendazole -- optimization -- corrosion inhibition -- predictive modelling -- response surface methodology; Engineering -- Periodicals; Technology -- Periodicals; Engineering; Technology; Periodicals; 620
• DOI: 10.1080/23311916.2020.1714100
• Languages: English
• ISSNs: 2331-1916

Abstract

Abstract: In this paper, we report the optimization and development of predictive models for the corrosion inhibition of mild steel in sulphuric acid by Methyl-5-benzoyl-2-benzimidazole Carbamate (Mebendazole). Design expert was used to analyze the corrosion inhibition related process parameters, such as corrosion penetration rate, inhibition efficiency, inhibitor concentration, acid concentration, weight loss, and their relationships. An attempt is made to obtain the optimal settings for this corrosion inhibition related process parameters. Design methodology, weight loss measurement, open-circuit potential analysis, Tafel polarization, etc. were used for the evaluation of inhibition efficiency of mebendazole for mild steel in H2 SO4 . The corrosion inhibition process parameters were optimized and predictive mathematical models developed using the Response Surface Methodology (RSM) using the central composite design (CCD) tool of Design Expert software version 11. Experimental and theoretical corrosion inhibition parameters were used to develop a nonlinear regression model to predict the optimal inhibition efficiency. Also, a quadratic model was generated, with predicted optimum inhibition efficiency of 88.4095% obtained having very near unity desirability of 0.914. The developed model shows that inhibition efficiency is related to the inhibitor concentration, immersion time, and acid concentration. The regression models generated are successfully used to predict the corrosion inhibition behaviour of mebendazole for low carbon steel in sulphuric acid medium.