Can Özkan

PhD Candidate


C.Ozkan@tudelft.nl


Materials Science & Engineering Department

Delft University of Technology

Building 34 H-1-230
Mekelweg 2
2628 CD Delft



Outreach


Articles

Laying the experimental foundation for corrosion inhibitor discovery through machine learning. C. Özkan, L. Sahlmann, C. Feiler, M. Zheludkevich, S. Lamaka, P. Sewlikar, A. Kooijman, P. Taheri, J.M.C. Mol. npj Materials Degradation (2024).

Artificial Intelligence, Machine Learning, And Big Data For Corrosion Control–Quo Vadis? D.A. Winkler, A.E. Hughes, C. Özkan, J.M.C. Mol, T. Würger, C. Feiler, S. Lamaka. The Australasian Corrosion Association (2024).

From experimental and computational inhibitor screening to advanced characterization of active protective coatings. C. Özkan, J.M.C. Mol. The Australasian Corrosion Association (2023).

Properties of passive films formed on ferrite-martensite and ferrite-pearlite steel microstructures. A. Yılmaz, C. Özkan, J. Sietsma, Y. Gonzalez-Garcia. Metals (2021).

Talks

Machine learning and 'small' data for hexavalent-chromium-free corrosion inhibition of airplanes. Studiekern Corrosie 75 year Anniversary Event (Delft, the Netherlands,  2023).

Evaluating organic corrosion inhibitors as chromate replacements through electrochemical experiments. C. Özkan, P. Visser, A. Cervellera-Dominguez, P. Taheri, J.M.C. Mol. EUROCORR 20223Annual European Corrosion Congress (Brussels, Germany,  2023).

Time-resolved electrochemical studies of AA2024-T3 corrosion inhibition: sodium dichromate vs. high-performing organic inhibitors. C. Özkan, P. Visser, A. Cervellera-Dominguez, P. Taheri, J.M.C. Mol. ASST 2023 Aluminum Surface Science and Technology Symposium (Stockholm, Sweden,  2023).

‘Small data’s big potential for functional molecule discovery. C. Özkan, P. Taheri, J.M.C. Mol. Delft University of Technology Materials Science & Engineering Department Performance & Recycling Talks (Online, 2022).

Time-resolved analysis of corrosion inhibitor layer irreversibility. C. Özkan, P. Visser, H. Terryn, P. Taheri, J.M.C. Mol. EUROCORR 2022 Annual European Corrosion Congress (Berlin, Germany,  2022).

Laying the experimental foundation for machine learning in corrosion inhibitor discovery. C. Özkan, L. Sahlmann, C. Feiler, M. Zheludkevich, P. Taheri, J.M.C. Mol. Corrosion and Materials Degradation Web Conference (Online,  2022).

Towards linking electrochemical and machine learning based assessment of corrosion inhibitor efficiency. C. Özkan, L. Sahlmann, C. Feiler, M. Zheludkevich, P. Taheri, J.M.C. Mol.  AETOC 2022 12th International Workshop on Application of Electrochemical Techniques to Organic Coatings (Val di Fiemme, Italy,  2022).

Posters

Molecule Discovery: Man vs. the Machine. C. Özkan, L. Sahlmann, C. Feiler, M. Zheludkevich, P. Sewlikar, A. Kooijman, P. Taheri, J.M.C. Mol.  OIP-2023 Open Innovation and collaborative decision making for materials design and manufacturing Conference (Belval, Luxembourg, 2023), GC-MAC Material Acceleration Consortium Summer School (Karlsruhe, Germany, 2023), TU Delft Materials Science and Engineering Department Materials Technology Day 2023 Artificial Intelligence (Delft, the Netherlands,  2023).

Hexavalent-chromium-free corrosion inhibitor performance for active protective coatings. C. Özkan, P. Taheri, J.M.C. Mol. Delft University of Technology Materials Science & Engineering Department Performance & Recycling Talks (Online, 2021).
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