Modelling the influence of pH, fluoride, and caffeine on the corrosion resistance of TiMo alloys by artificial neural networks developed with differential evolution algorithm
Abstract
Titanium (Ti) and its alloys are widely used in dental applications due to the excellent corrosion resistance and mechanical properties. However, it has been reported that Ti is sensitive to fluor ions (F-) and lactic acid. Corrosion behaviour of the TiMo alloys, together with the currently used metallic biomaterial commercial pure titanium (Cp-Ti), was investigated considering the use of alloys for dental applications. All the samples were examined using electrochemical impedance spectroscopy (EIS) in acidic artificial saliva with NaF and/or caffeine, at 37 °C. Equivalent circuits were used for modeling EIS data, in order to characterize samples surface and better understanding the effect of Mo addition on Cp-Ti. The TiMo alloys appear to possess superior corrosion resistance than Cp-Ti in all electrochemical media. In addition, a modelling technique based on differential evolution and artificial neural network was applied. The scope of this procedure was to determine an efficient model of the process and to eliminate the need for new experiments based on the predictions provided by the developed models