The influence of neem leaf extract on corrosion inhibition of mild steel in 0.1 M HCl solution was studied using the weight loss method. Neem leaf extract which contains the double bond, carbonyl groups, and aromatic rings functional group as shown by the GCMS, phytochemical test, and FTIR analyses is one of the good natural plant extract that can be used as corrosion inhibitor. The weight loss on surface of mild steel at various inhibitor concentrations was determined. The highest inhibition efficiency of 93.24% was achieved using the neem leaf extract as corrosion inhibitor. Adsorption mechanism was investigated using Langmuir, Temkin, and Freundlich isotherms. Inhibitor adherence on the mild steel surface was spontaneous with the negative Gibb’s free energy value obtained. The mixed type adsorption mechanism (physisorption and chemisorption) is proposed for the inhibitor adsorption on mild steel surface. The inhibitor was adsorbed on the mild steel surface through adsorption of the phytochemical components on the surface of mild steel which protects the metal surface from corroding. The corrosion rate decreases from 0.001 to 0.0002MPY with increase in inhibitor concentrations and exposure time.

Response surface methodology (RSM) and artificial neural network (ANN) on modeling and optimization of corrosion inhibition efficiencies of mild steel using water hyacinth as an inhibitor was carried out in this work. The optimization of the process was done using generic algorithm (GA) and RSM which were subsequently compared. The optimum inhibition efficiency predicted were 87.675924% and 82.89% by ANN and RSM respectively. The value of R2 obtained were 0.9695 and 0.85118 for ANN and RSM models respectively while RMSE values of 3.90 and 4.3089 were gotten for RSM and ANN models respectively. The model regression indicated that RSM best fit the experimental data thus perform better on mild steel corrosion inhibition.