Comparative Modeling, Optimization and Optimal Corrosion Inhibition Studies of Aspilia-Africana Leaf Extract on Mild Steel and Aluminum Metal in Acid Medium

• DOI: 10.2139/ssrn.4132384
• Publication Date: 2022-06-15T17:00:33Z
• Authors: Paschal Ohale; Loveth Nwanneka E...; Chijioke E. Onu; Nonye Jennifer Ohale

In this work, the predictive capabilities of response surface methodology (RSM) and adaptive neuro fuzzy inference systems (ANFIS) in modeling Aluminum (Al) mild steel corrosion inhibition by Aspilia Africana ( A.Africana ) were comparatively analyzed. Phytochemical FTIR characterization leaf extract indicated that inhibitor possessed high value flavonoids, Tannins dominant functional groups necessary for promoting sustainable inhibition. While statistical parameters verified applicability RSM ANFIS techniques Al steel, error indices illustrated dominance (R 2 = 0.9917) 0.9905) predicting efficiency respectively. Analysis variance (ANOVA) showed acid concentration (F-value 191.23) was most influential process parameter process, while presented an F-value 160.5 to maintain its superior position among other factors coupled genetic algorithm optimization (ANFIS-GA) validated be 80.01% at HCl conc. 0.7 M, 0.59 g/L immersion time 6.2 h. Similarly, optimized using RSM-GA 77.3% (HCl 0.5 0.37 4.8 h). Post electrochemical studies demonstrated close agreement with obtained gravimetric technique. Furthermore, polarization acted as a mixed type species.