State-of-the-art progress on artificial intelligence and machine learning in accessing molecular coordination and adsorption of corrosion inhibitors
Taiwo W. Quadri, Ekemini D. Akpan, Saheed E. Elugoke, Lukman O. Olasunkanmi, Sheetal, Ashish Kumar Singh, Balaram Pani, Jaya Tuteja, Sudhish Kumar Shukla, Chandrabhan Verma, Hassane Lgaz, Valentine Chikaodili Anadebe, Rakesh Chandra Barik, Lei Guo, Akram Alfantazi, B.M. Mothudi, Eno E. Ebenso
Abstract
Artificial intelligence (AI) and machine learning (ML) have attracted the interest of the research community in recent years. ML has found applications in various areas, especially where relevant data that could be used for algorithm training and retraining are available. In this review article, ML has been discussed in relation to its applications in corrosion science, especially corrosion monitoring and control. ML tools and techniques, ML structure and modeling methods, and ML applications in corrosion monitoring were thoroughly discussed. Furthermore, detailed applications of ML in corrosion inhibitor design/modeling coupled with associated limitations and future perspectives were reported.