High strength aluminum alloys design via explainable artificial intelligence
  • Park, Seobin
  • Kayani, Saif Haider
  • Euh, Kwangjun
  • Seo, Eunhyeok
  • Kim, Hayeol
  • 외 5명
Citations

WEB OF SCIENCE

43
Citations

SCOPUS

51

초록

Here, we have approached to discover new aluminum (Al) alloys with the assistance of artificial intelligence (A.I.) for the enhanced mechanical property. A high prediction rate of 7xxx series Al alloy was achieved via the Bayesian hyperparameter optimization algorithm. With the guide of A.I.-based recommendation algorithm, new Al alloys were designed that had an excellent combination of strength and ductility with a yield strength (YS) of 712 MPa and elongation (EL) of 19%, exhibiting a homogeneous distribution of nanoscale precipitates hindering dislocation movement during deformation. Adding Mg and Cu was found to be the critical factor that decides the relative ratio of strength and EL. We also demonstrate an explainable A.I. (XAI) system that reveals the relationship between input and output parameters. Our A.I. assistant system can accelerate the search for high-strength Al alloys for both experts and non-experts in the field of Al alloy design. (c) 2022 Published by Elsevier B.V.

키워드

Alloy designDeep neural networks7xxx aluminum alloysHyperparameter tuningExplainable artificial intelligenceAI-based recommendation algorithmZR-TI ALLOYSMG-CU ALLOYMICROSTRUCTURAL EVOLUTIONPRECIPITATION EVOLUTIONMECHANICAL-BEHAVIORCORROSION BEHAVIORHEAT-TREATMENTPROCESS MODELSTEEL WIRESAS-CAST
제목
High strength aluminum alloys design via explainable artificial intelligence
저자
Park, SeobinKayani, Saif HaiderEuh, KwangjunSeo, EunhyeokKim, HayeolPark, SangeunYadav, Bishnu NandPark, Seong JinSung, HyokyungJung, Im Doo
DOI
10.1016/j.jallcom.2022.163828
발행일
2022-05
유형
Article
저널명
Journal of Alloys and Compounds
903