AI Approaches for Finding Efficient Corrosion Inhibitors

Corrosion inhibitors, whether integrated into protective coatings or directly applied to corrosive environments, play a pivotal role in safeguarding metals. Despite this, identifying effective inhibitors within the vast chemical landscape remains a formidable challenge. Over the past decades, numerous research papers have explored the inhibitory effects of individual compounds on various metals across diverse corrosive conditions, creating an extensive body of knowledge.
Recent advancements in machine learning (ML) techniques offer promising avenues for streamlining the search and identifying potential candidates more efficiently. In this study, we focus on rapidly screening organic compounds as potential corrosion inhibitors for magnesium (Mg) and aluminum (Al) alloys. Our approach involves developing quantitative structure-property relationship (QSPR) models using ML algorithms, specifically support vector regression and kernel ridge regression. These models learn from existing data and generalize to predict the behavior of new compounds. To validate their robustness, we conducted experimental blind testing.
In summary, ML-driven approaches hold great promise for accelerating the discovery of corrosion inhibitors. By harnessing computational tools, researchers can efficiently explore the vast chemical space and make informed decisions regarding the selection of corrosion inhibitors for specific applications.

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Biography

Prof. Mikhail Zheludkevich currently serves as the Director of the Institute of Surface Science at Helmholtz-Zentrum Hereon, Germany. Additionally, he holds a full professorship at the University of Kiel. His research interests revolve around electrochemistry, multi-functional surfaces, and the active protection of lightweight materials and multi-material systems.
In 2002, Prof. Zheludkevich earned his PhD in Physical Chemistry from the Belarusian State University, specializing in the interaction of atomic gases with metallic surfaces. Following a decade of diverse roles at the University of Aveiro, ranging from post-doctoral researcher to group leader, he joined Helmholtz Zentrum Geesthacht as the head of the Corrosion and Surface Technology Department. In 2021, he established the Institute of Surface Science, a position he continues to lead.
Prof. Zheludkevich’s contributions have garnered recognition, including the Tajima Prize from the International Society of Electrochemistry in 2016 and the distinction of Person of the Year 2023 by the International Mg Society. Furthermore, he serves as the chairman of the Aerospace Working Party at the European Federation of Corrosion.