Chemical domain structure and its formation kinetics in CrCoNi medium-entropy alloy. (November 2022)

• Record Type: Journal Article
• Authors: Du, Jun-Ping; Yu, Peijun; Shinzato, Shuhei; Meng, Fan-Shun; Sato, Yuji; Li, Yangen; Fan, Yiwen; Ogata, Shigenobu
• Is Part Of: Acta materialia. Volume 240(2022)
• Publication Date: 2022-11
• Subjects: Atomic ordering -- Kinetic Monte Carlo -- Artificial neural networks -- Atomistic modeling -- Atomic structure; Materials -- Periodicals; Materials science -- Periodicals; Materials -- Mechanical properties -- Periodicals; Metallurgy -- Periodicals; Chemistry, Inorganic -- Periodicals; 620.112
• DOI: 10.1016/j.actamat.2022.118314
• Languages: English
• ISSNs: 1359-6454

Abstract

Graphical abstract: Abstract: The formation of local chemical order in medium-entropy alloys and high-entropy alloys (MEAs/HEAs) has been strongly suggested in recent experimental observations. Since chemical order can lead to changes in mechanical and functional properties, tailoring of chemical order is a promising approach for further improving those properties of MEAs and HEAs. However, details remain unclear regarding the atomic structure of the chemical order and the formation kinetics. Here, employing a large-scale Monte Carlo/molecular dynamics hybrid annealing simulation with a neural network potential, we find a chemical-domain structure (CDS) after annealing below 800 K in FCC CrCoNi MEA. In addition, the formation kinetics, such as the formation time and process and time–temperature–chemical-order diagrams of the CDS, were successfully obtained using a kinetic Monte Carlo simulation with artificial neural network acceleration. The findings provide key information for controlling chemical order via thermal processing.