Microstructural properties and evolution of nanoclusters in liquid Si during a rapid cooling process
- Authors: 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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Affiliations:
- Guizhou Provincial Key Laboratory of Public Big Data, Institute of New Type Optoelectronic Materials and Technology, College of Big Data and Information Engineering
- Issue: Vol 106, No 10 (2017)
- Pages: 667-671
- Section: Condensed Matter
- URL: https://journals.rcsi.science/0021-3640/article/view/160564
- DOI: https://doi.org/10.1134/S0021364017220015
- ID: 160564
Cite item
Abstract
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.
About the authors
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
Author for correspondence.
Email: gaotinghong@sina.com
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
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
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
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
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
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
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
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
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
China, Guiyang, 550025
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