Nickel based super alloy, Inconel 718, is known for its strength, creep resistance, fatigue life, high temperature oxidation resistance, and corrosion resistance to aggressive aqueous environments. As a γ’ and γ’’ precipitation strengthened alloy, a number of compositional modifications through alloying elements are made in this material for improving its environmental degradation resistance. Electrochemical corrosion of Ni based super alloys, in particular, poses continuous challenges, for improving service life, due to variety of harsh environments, the structural components constituting these alloys are exposed to, especially in aeroengines & chemical processing plants. The literature is scarce on aqueous corrosion behaviour of Laser Powder Bed Fusion (LPBF) fabricated Inconel 718. Hence, the present work was focused to investigate the aqueous corrosion behavior of as built and post-processed Inconel 718 using electrochemical techniques. The test coupons of Inconel 718 were built using optimized process parameters and subsequently, they were subjected to heat treatment and shot peening for tailoring the microstructure. The heat treatment techniques chosen are stress relieving, solutionizing and ageing.
Surface roughness analysis on all the processed specimens was performed in order to assess the influence of shot peening on the overall surface topology. Optical microscopic imaging was performed to study the specific features of LPBF, such as melt pool tracks, hatch patterns, differences in mesostructure during deposition. In order to understand the evolution of microstructural characteristics such as formation of precipitates, grain morphology, and grain boundary networks in Inconel 718, SEM ,TEM, EDS & XRD analysis were performed. Corrosion testing of the specimens were carried out in both acidic and alkaline environment using the potentiodynamic polarization and electrochemical impedance spectroscopy techniques. The corrosion mechanism of each specimen condition is discussed and supported with pitting analysis from post corrosion SEM imaging. The role the evolving phases such as γ’, γ”, metallic carbides and Laves phase governing the corrosion mechanisms is elucidated. The optimum heat treatment procedure for elevated corrosion resistance was proposed for an additively manufactured component of Inconel 718.
In addition to experimental work, Machine learning based models (ML) such as Support vector machines, Extreme gradient boosting, and Decision trees were used to predict corrosion behavior of Inconel 718. These ML models were trained using the corrosion data collected from literature and experimental data generated in the present work. In the first part, Iso corrosion data of different nickel-based alloys were collected and utilized in classification-based ML modelling to predict the Iso corrosion curve of Inconel 718. In the second part, experimental corrosion data of additively manufactured specimens were utilized to predict the electrochemical behavior of both as built and post processed conditions. Further, the parameters that influence the corrosion behavior were identified by the ML models and cross verified with the available literature.