Microstructural properties and evolution of nanoclusters in liquid Si during a rapid cooling process
- 作者: 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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隶属关系:
- Guizhou Provincial Key Laboratory of Public Big Data, Institute of New Type Optoelectronic Materials and Technology, College of Big Data and Information Engineering
- 期: 卷 106, 编号 10 (2017)
- 页面: 667-671
- 栏目: 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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详细
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.
作者简介
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
编辑信件的主要联系方式.
Email: gaotinghong@sina.com
中国, 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
中国, 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
中国, 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
中国, 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
中国, 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
中国, 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
中国, 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
中国, 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
中国, 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
中国, Guiyang, 550025
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