Hydrogen Diffusion in Nickel Superalloys: Electrochemical Permeation Study and Computational AI Predictive Modeling

Area of Science:

• Materials Science
• Metallurgy
• Corrosion Science

Background:

• Nickel-based superalloys are critical for high-performance applications due to their corrosion resistance and mechanical properties.
• Hydrogen embrittlement (HE) poses a significant risk to metallic materials, impacting their integrity.
• Understanding hydrogen diffusion in superalloys is crucial for preventing HE.

Purpose of the Study:

• To investigate the effect of chromium content on hydrogen diffusivity in Ni-based superalloys.
• To develop artificial intelligence (AI)-based predictive models for hydrogen diffusion parameters.
• To analyze hydrogen interaction with microstructural features in superalloys.

Main Methods:

• Permeability testing using the Devanathan-Stachurski double cell method.
• Characterization of superalloys via EDS, XRD, OM, and SEM.
• Development of artificial neural networks (ANNs) for predictive modeling.

Main Results:

• Effective diffusion coefficient (D_eff), steady-state flux (J_ss), and trap density (N_T) were quantified.
• D_eff, J_ss, and N_T values were found to be higher than typical Ni alloy reports.
• ANN models achieved high linear correlation coefficients (0.96 for D_eff, 0.80 for J_ss).

Conclusions:

• Chromium content in solid solution does not significantly affect hydrogen diffusion in these Ni-based superalloys.
• The developed AI models provide a reliable method for estimating D_eff and J_ss.
• This research contributes to understanding and mitigating hydrogen embrittlement in critical superalloy applications.