Olawale Fatoba
Tshwane University of Technology, South Africa
Title: Improved corrosion and wear resistance of laser alloyed Al-Sn coatings on UNS G10150 steel in acidic environment: Artificial neural model approach
Biography
Biography: Olawale Fatoba
Abstract
Surface deterioration by corrosion is one of the complications associated with ageing facilities and components especially under some service environments. The research work examines the corrosion behaviour of laser alloyed UNS-G10150 steel; coatings have been obtained by laser surface alloying technique. Binary combinations of Al/Sn metallic powders were mixed and injected onto the surface of UNSG10150 mild steel substrate under different laser processing parameters. The steel alloyed samples were cut to corrosion coupons, immersed in hydrochloric acid (1M HCl) solution at 280C using electrochemical and gravimetric techniques and investigated for its corrosion behaviour. The morphologies and microstructures of the developed coatings and uncoated samples were characterized by Optic Nikon Optical microscope (OPM) and scanning electron microscope (SEM/EDS). Moreover, X-ray diffractometer (XRD) was used to identify the phases present. The improved surface properties were attributed to the formation of new intermetallic and corrosion phases (Al3Sn9, Al5Sn6, AlSn(OH)6, Al2SnO4, Al5(OH)8Cl2.H2O, Sn3O(OH)2Cl4, Al4ClO4(OH)7) and fine eutectic microstructures. In addendum, Artificial Neural Network Model [ANN] was used for the optimization and modeling of the laser parameters since processing parameters played an important role in the quality of alloyed coating produced. Corresponding experimental results show a good qualitative conformity with the numerical model predictions.