S. Rajendran

Papers

Total Citations

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About

Dr. S. Rajendran is an emerging voice at the intersection of materials science and artificial intelligence, with a focused expertise in corrosion inhibition. His most-cited work, "Application of machine learning in corrosion inhibition study" (2022, 8 citations), pioneers the integration of machine learning—a branch of AI that enables computers to learn and act without explicit programming—into the traditionally empirical field of corrosion science. By demonstrating how algorithms can predict inhibitor performance and accelerate materials discovery, Rajendran has opened a new computational pathway for designing more durable metals and coatings. Though early in his career, his contributions are already shaping how researchers approach corrosion protection, moving from trial-and-error experiments to data-driven models. His work signals a broader shift toward intelligent, automated materials design, positioning him as a key figure in the growing field of AI-assisted corrosion engineering. For students and researchers, Rajendran’s research offers a compelling blueprint for merging classical chemistry with modern machine learning techniques to solve long-standing industrial challenges.