Microstructural properties and evolution of nanoclusters in liquid Si during a rapid cooling process
- Autores: Gao T.1, Ren L.1, Luo X.1, Liang Y.1, Chen Q.1, Xie Q.1, Tian Z.1, Li Y.1, Hu X.1, Luo J.1
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Afiliações:
- Guizhou Provincial Key Laboratory of Public Big Data, Institute of New Type Optoelectronic Materials and Technology, College of Big Data and Information Engineering
- Edição: Volume 106, Nº 10 (2017)
- Páginas: 667-671
- Seção: Condensed Matter
- URL: https://journals.rcsi.science/0021-3640/article/view/160564
- DOI: https://doi.org/10.1134/S0021364017220015
- ID: 160564
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Resumo
The formation of amorphous structures in Si during the rapid quenching process was studied based on molecular dynamics simulation by using the Stillinger–Weber potential. The evolution characteristics of nanoclusters during the solidification were analyzed by several structural analysis methods. The amorphous Si has been formed with many tetrahedral clusters and few nanoclusters. During the solidification, tetrahedral polyhedrons affect the local structures by their different positions and connection modes. The main kinds of polyhedrons randomly linked with one another to form an amorphous network structures in the system. The structural evolution of crystal nanocluster demonstrates that the nanocluster has difficulty to growth because of the high cooling rate of 1012 K/s.
Sobre autores
T. Gao
Guizhou Provincial Key Laboratory of Public Big Data, Institute of New Type Optoelectronic Materials and Technology, College of Big Data and Information Engineering
Autor responsável pela correspondência
Email: gaotinghong@sina.com
República Popular da China, Guiyang, 550025
L. Ren
Guizhou Provincial Key Laboratory of Public Big Data, Institute of New Type Optoelectronic Materials and Technology, College of Big Data and Information Engineering
Email: gaotinghong@sina.com
República Popular da China, Guiyang, 550025
X. Luo
Guizhou Provincial Key Laboratory of Public Big Data, Institute of New Type Optoelectronic Materials and Technology, College of Big Data and Information Engineering
Email: gaotinghong@sina.com
República Popular da China, Guiyang, 550025
Y. Liang
Guizhou Provincial Key Laboratory of Public Big Data, Institute of New Type Optoelectronic Materials and Technology, College of Big Data and Information Engineering
Email: gaotinghong@sina.com
República Popular da China, Guiyang, 550025
Q. Chen
Guizhou Provincial Key Laboratory of Public Big Data, Institute of New Type Optoelectronic Materials and Technology, College of Big Data and Information Engineering
Email: gaotinghong@sina.com
República Popular da China, Guiyang, 550025
Q. Xie
Guizhou Provincial Key Laboratory of Public Big Data, Institute of New Type Optoelectronic Materials and Technology, College of Big Data and Information Engineering
Email: gaotinghong@sina.com
República Popular da China, Guiyang, 550025
Z. Tian
Guizhou Provincial Key Laboratory of Public Big Data, Institute of New Type Optoelectronic Materials and Technology, College of Big Data and Information Engineering
Email: gaotinghong@sina.com
República Popular da China, Guiyang, 550025
Y. Li
Guizhou Provincial Key Laboratory of Public Big Data, Institute of New Type Optoelectronic Materials and Technology, College of Big Data and Information Engineering
Email: gaotinghong@sina.com
República Popular da China, Guiyang, 550025
X. Hu
Guizhou Provincial Key Laboratory of Public Big Data, Institute of New Type Optoelectronic Materials and Technology, College of Big Data and Information Engineering
Email: gaotinghong@sina.com
República Popular da China, Guiyang, 550025
J. Luo
Guizhou Provincial Key Laboratory of Public Big Data, Institute of New Type Optoelectronic Materials and Technology, College of Big Data and Information Engineering
Email: gaotinghong@sina.com
República Popular da China, Guiyang, 550025
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