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ナンダル ヴィッキー
305-0044 茨城県つくば市並木1-1 [アクセス]



Artificial Intelligence, Machine Learning, Materials Integration by Network Technology (MInt), Ni-based Superalloys, Advanced Characterization Techniques, High Entropy Alloys, Advanced Alloys

Recently, we have utilized a state-of-the-art Artificial Intelligence (AI) technique for a precipitation hardenable Ni-based alloy to predict more flexible non-isothermal aging (NIA) and to examine the possible routes for the enhancement in mechanical strength that may be practically achieved. Furthermore, AI is used to integrate with Materials Integration by Network Technology (MInt) system, which is a computational workflow utilized to model the microstructure evolution and evaluate the 0.2% proof stress for isothermal aging and NIA. Employing the essence from AI, we have succeeded in designing an optimum aging route (i.e., AI-inspired expert design) in which we attained an outperformed 0.2% proof stress to AI-designed NIA best case. (Nandal et al., Scientific Reports, Vol. 13, 12660, 2023)




The Japan Institute of Metals and Materials (JIMM) Japan, The Indian Institute of Metals (IIM) India, The Minerals, Metals & Materials Society (TMS) USA