Dawei Zhang， Lingwei Ma, Dongmei Fu, Xiaogang Li
Beijing Advanced Innovation Center for Materials Genome Engineering, University of Science and Technology Beijing, Beijing 100083, China;
National Materials Corrosion and Protection Data Center, Beijing 100083, China;
Institute of Materials Intelligent Technology, Liaoning Academy of Materials, Shenyang 110004, China
School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China
EXTENDED ABSTRACT: Materials corrosion is a complex failure process affected by many factors and can seriously jeopardize the service safety of infrastructure and equipment. The estimated costs of corrosion losses add up to more than 3 trillion yuan in China every year. The emergent materials genome engineering research field has spurred development in intelligent methodology that is transforming the corrosion research paradigm. For example, high-throughput and automated experiments are employed to substantially accelerate the screening of corrosion-resistant materials and the evaluation of corrosion behaviors under complex/combinatorial influencing factors. Machine learning tools are revealing their power to predict corrosion rates and rapidly discover optimized materials composition out of large search spaces, thereby reducing the time and cost associated with traditional'trial-and-error'corrosion evaluation methods. This talk will summarize several latest works from this group on the application of data-driven and intelligent technologies towards accelerated discovery and evaluation of materials for corrosion protection.
Keywords: Corrosion and Protection; Corrosion Big Data; Machine Learning; Corrosion Prediction
Dawei Zhang is a professor at University of Science and Technology Beijing (USTB). He serves as Director of Office of International Affairs of USTB, Deputy Director of National Materials Corrosion and Protection Data Center and Associate Director of Beijing Advanced Innovation Center for Materials Genome Engineering. He is the Chair of International Advisory Council of Association for Materials Protection and Performance (AMPP). His research interests are smart protective coatings, microbial corrosion and data-driven corrosion modelling. He has published over 200 papers with 11,000 citations and an h-index of 55. He is currently an Editor of Corrosion Science, and an editorial board member of several journals including Materials Genome Engineering Advances, npj Materials Degradation, and International Journal of Mining, Metallurgy and Materials.