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RSM-based optimization and predictive modelling of the gravimetric corrosion behaviour of solution-treated copper-based shape memory alloy in HCl solution

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Abstract

Gravimetric weight loss analysis, response surface optimization, and predictive modeling techniques were used to study the corrosion resistance behavior of quenched Cu–Zn–Al alloys in 0.5 m HCl solution. Cu–Zn–Al alloy with 20 and 6 weight percent Zn and Al respectively, was developed by casting method. Prior to being machined to specifications for the corrosion resistance test, the alloy underwent a solutionizing treatment at 850 °C. During the corrosion weight loss measurement, the immersion time and operation temperature ranged from 1 to 4 h and 35 to 60 °C respectively. The corrosion rate of the solution-treated Cu–20Zn–6Al alloy in 0.5 m HCl dropped from 120.189 to 1.603 mm/year with increasing operation temperature and immersion time, according to the corrosion test findings. Thus the Cu–Zn–Al alloy demonstrated strong resistance to corrosion in 0.5 m HCl solution within the boundaries of the considered process parameters. RSM optimization of the experimental process revealed that all the generated model terms are significant with P values less than 0.05. Derived regression model capable of predicting the optimal corrosion rate correlates the corrosion immersion time and operating temperature with the corrosion rate of the solution-treated Cu–20Zn–6Al alloy within the studied conditions. Numerical optimization of the process parameters reveal that at 60 °C and 4 h maximum operating temperature and immersion time, minimal corrosion rate with 0.990 high degree of desirability would be obtained. The as-quenched Cu–20Zn–6Al alloy could be applied in the design of components for elevated temperature acidic environments.

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Authors and Affiliations

  1. Department of Metallurgical and Materials Engineering, Nnamdi Azikiwe University, Awka, Nigeria

    Francis Odikpo Edoziuno, Cynthia Chinasa Nwaeju & Eugene Ekedumogwu Nnuka

  2. Department of Metallurgical Engineering Technology, Delta State Polytechnic, P.M.B. 1030, Ogwashi-Uku, Nigeria

    Francis Odikpo Edoziuno

  3. Department of Mechanical Engineering, Landmark University, Omu-Aran, Kwara State, Nigeria

    Adeolu Adesoji Adediran

  4. Department of Mechanical and Mechatronics Engineering, Afe Babalola University, Ado Ekiti, Nigeria

    Adedotun Adetunla

  5. Department of Mechanical Engineering, Nigeria Maritime University, Okerenkoko, Delta State, Nigeria

    Cynthia Chinasa Nwaeju

  6. Department of Mechanical Engineering Science, University of Johannesburg, Johannesburg, South Africa

    Adeolu Adesoji Adediran

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  1. Francis Odikpo Edoziuno
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Edoziuno, F.O., Adediran, A.A., Adetunla, A. et al. RSM-based optimization and predictive modelling of the gravimetric corrosion behaviour of solution-treated copper-based shape memory alloy in HCl solution. Int J Interact Des Manuf 18, 1131–1139 (2024). https://doi.org/10.1007/s12008-022-01163-x

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