Prediction of atomic structure of Pt-based bimetallic nanoalloys by using genetic algorithm
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...
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| Published in | Metals and materials international Vol. 19; no. 3; pp. 513 - 518 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Springer
The Korean Institute of Metals and Materials
01.05.2013
Springer Nature B.V 대한금속·재료학회 |
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| ISSN | 1598-9623 2005-4149 |
| DOI | 10.1007/s12540-013-3020-z |
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| Abstract | 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. |
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| AbstractList | 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. 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. KCI Citation Count: 3 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.[PUBLICATION ABSTRACT] |
| Author | Lee, Seung-Cheol Choi, Jung-Hae Oh, Jung Soo Nam, Ho-Seok |
| Author_xml | – sequence: 1 givenname: Jung Soo surname: Oh fullname: Oh, Jung Soo organization: Future Convergence Technology Research Division, Korea Institute of Science and Technology – sequence: 2 givenname: Ho-Seok surname: Nam fullname: Nam, Ho-Seok organization: Center for Materials and Processes of Self-Assembly and School of Advanced Materials Engineering, Kookmin University – sequence: 3 givenname: Jung-Hae surname: Choi fullname: Choi, Jung-Hae organization: Future Convergence Technology Research Division, Korea Institute of Science and Technology – sequence: 4 givenname: Seung-Cheol surname: Lee fullname: Lee, Seung-Cheol email: leesc@kist.re.kr organization: Future Convergence Technology Research Division, Korea Institute of Science and Technology |
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| CitedBy_id | crossref_primary_10_1016_j_jallcom_2015_12_146 crossref_primary_10_1016_j_physleta_2014_08_019 crossref_primary_10_1016_j_commatsci_2013_08_054 crossref_primary_10_1016_j_cpc_2014_09_007 crossref_primary_10_1016_j_physe_2015_02_008 crossref_primary_10_1088_0953_8984_27_1_013003 crossref_primary_10_1088_2632_2153_ad69ff crossref_primary_10_1007_s00170_020_05242_9 crossref_primary_10_7498_aps_64_153601 |
| Cites_doi | 10.1016/0009-2614(96)00406-X 10.1039/B709000E 10.1021/jp711702y 10.1166/jnn.2009.dk15 10.1007/s11244-007-9003-x 10.1016/j.actamat.2012.05.032 10.1021/jp8063933 10.1063/1.1898223 10.1098/rspa.2010.0562 10.1088/0953-8984/22/24/245401 10.1088/0953-8984/21/8/084208 10.1016/0039-6028(77)90442-3 10.1021/ja903247x 10.1134/S1063774506020209 10.1007/s12540-009-0797-2 10.1021/jp9006075 10.1016/0039-6028(95)00017-8 10.1103/PhysRevB.76.174208 10.1021/jp100194p 10.3740/MRSK.2011.21.8.425 10.1021/jp802804u 10.1021/j100141a013 10.1166/jctn.2009.1118 10.1016/j.susc.2007.04.250 10.1016/j.commatsci.2008.03.045 10.1039/b707136a 10.1021/jp0518862 10.1021/cr1002529 10.1039/b305686d 10.1063/1.2104487 10.1103/PhysRevB.82.075413 10.1021/cr040090g 10.1016/j.chemphys.2006.09.015 10.1063/1.1448484 |
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| SubjectTerms | 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 |
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| Title | Prediction of atomic structure of Pt-based bimetallic nanoalloys by using genetic algorithm |
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