Investigating corrosion resistance in Ni–Al₂O₃ composite coatings: a fuzzy logic-based predictive study

This research explores “Ni–Al₂O₃” composite coatings produced through conventional electrodeposition, examining their corrosion resistance about variations in alumina concentration, bath temperature, and applied electrical current. Unlike previous studies, this research introduces a new fuzzy inference model, used in conjunction with polarization techniques, to analyze the impacts of the parameters. The model closely aligns with experiments, exhibiting 4.336% average error for corrosion rates. Such precision offers a promising pathway for optimizing corrosion resistance, an aspect that has not been sufficiently addressed in previous research. Findings highlight the crucial influence of Al₂O₃, showcasing minimal corrosion rates at 5 g/l at 30 °C and 15 g/l at 40 °C. Optimal corrosion resistance peaks at 15 g/l Al₂O₃, declining beyond this concentration. Elevated temperatures diminish resistance post 40 °C. Increasing Al₂O₃ concentration halves corrosion rates, demonstrating effective Al₂O₃ particle incorporation. Bath temperature and Al₂O₃ concentration synergy significantly reduce corrosion rates until 40 °C. However, beyond 40 °C, corrosion rates rise irrespective of current. The study underscores bath temperature’s dominance over deposition current in influencing Ni–Al₂O₃ coating anti-corrosive properties. Employing fuzzy logic with only 60 experiments provides an economical approach for predicting corrosion rates, marking a substantial stride in developing high-corrosion-resistant metallic composites.