Prediction of atomic structure of Pt-based bimetallic nanoalloys by using genetic algorithm

• Published in: Metals and materials international Vol. 19; no. 3; pp. 513 - 518
• Main Authors: Oh, Jung Soo, Nam, Ho-Seok, Choi, Jung-Hae, Lee, Seung-Cheol
• Format: Journal Article
• Language: English
• Published: Springer The Korean Institute of Metals and Materials 01.05.2013; Springer Nature B.V; 대한금속·재료학회
• Subjects: Alloying; Alloying elements; Bimetals; Characterization and Evaluation of Materials; Chemistry and Materials Science; Engineering Thermodynamics; Genetic algorithms; Heat and Mass Transfer; Machines; Magnetic Materials; Magnetism; Manufacturing; Materials Science; Metallic Materials; Nanocomposites; Nanomaterials; Nanostructure; Platinum; Processes; Solid Mechanics; 재료공학; composites; genetic algorithm; computer simulation; bonding ordering
• ISSN: 1598-9623; 2005-4149
• DOI: 10.1007/s12540-013-3020-z

The atom-arrangements in Pt-based bimetallic nanoalloys were predicted by the combined use of genetic algorithm (GA) and molecular dynamics (MD) simulations. The nanoparticles of these nanoalloys were assumed to be a 3.5 nm-diameter truncated octahedron with Pt and noble metals of fixed composition ratio of 1:1. For the GA, a Python code, which concurrently linked with the MD method that uses the embedded atom method inter-atomic potentials, was developed for the prediction of the atom arrangements in these bimetallic nanoalloys. Successfully, the GA calculation predicted the core-shell structures for both Pt-Ag and Pt-Au nanoalloy, but an onion-like multilayered core-shell structure for Pt-Cu nanoalloy. The structural characteristics in the bimetallic nanoalloy were mainly due to the differences in the surface energy and cohesive energy between Pt and the other alloying metal elements and their miscibility gap and so on. Briefly, the prediction performance was analyzed to show the superior searching ability of GA.