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Modelling the influence of pH, fluoride, and caffeine on the corrosion resistance of TiMo alloys by artificial neural networks developed with differential evolution algorithm

机译:用微分进化算法开发的人工神经网络模拟pH,氟化物和咖啡因对TiMo合金耐蚀性的影响

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摘要

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 degrees 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.
机译:钛(Ti)及其合金由于其优异的耐腐蚀性和机械性能而广泛用于牙科应用。但是,据报道,Ti对氟离子(F-)和乳酸敏感。考虑到将合金用于牙科应用,研究了TiMo合金以及当前使用的金属生物材料商业纯钛(Cp-Ti)的腐蚀行为。使用电化学阻抗谱(EIS)在37°C的NaF和/或咖啡因的酸性人工唾液中检查所有样品。使用等效电路建模EIS数据,以表征样品表面并更好地理解Mo的作用在Cp-Ti上添加。在所有电化学介质中,TiMo合金似乎都比Cp-Ti具有更好的耐腐蚀性。此外,还应用了基于差分进化和人工神经网络的建模技术。该程序的范围是确定过程的有效模型,并根据已开发模型提供的预测消除对新实验的需求。

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