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ABSTRACT

Classification of Crystallographic Groups of Alloy Systems by Isomap and Modularity Methods

Kuan-Peng Chen1,3, An-Cheng Yang1,3, Wen-Jay Lee1, Yi-Ming Tseng2, Nien-Ti Tsou2, Nan-Yow Chen1,*

1 National Center for High-performance Computing, National Applied Research Laboratories, Hsin-Chu300, Taiwan.
2 Department of Materials Science and Engineering, National Chiao Tung University, Hsin-Chu300, Taiwan.
3 Authors are contributed equally to this work.
* Corresponding Author: Nan-Yow Chen. Email: nanyow@nchc.narl.org.tw.

The International Conference on Computational & Experimental Engineering and Sciences 2019, 21(3), 54-54. https://doi.org/10.32604/icces.2019.05401

Abstract

Crystallographic classification of microstructure is a very important issue in material science especially numerous data were generated by experiments or Molecular Dynamic (MD) simulations. Some analysis tools were purposed, such as coordination analysis and Honeycutt-Anderson (HA) pair analysis [1], however, to analyze these huge amounts of data is still quite difficult. Sometimes, crystallography prior knowledge of their structures is also desired in the classification procedures. Not only the task is very labor intensive but also the result is susceptible to errors and is usually lack of objectivity. In this study, we developed a computational workflow which can get characteristic quantities of microstructures and identify different crystal structures without prior knowledge of crystallography. These characteristic quantities (a.k.a. Characteristic Indexes) are, for example, coordination number, local ordering, and local coordinate information, etc. After Characteristic Indexes of local structures were obtained, isomap [2] and modularity [3] methods are applied to classify their structures and to get their structural phase diagrams. The isomap method can define the similarity between different crystal structures by geodesic paths in a high-dimensional data manifold as well as the modularity method can find the best community structure of classification by optimization, i.e., to maximize the intra module connections as many as possible and to minimize the inter module connections as few as possible. With these tools, we can obtain the atomic structure evolution of alloy system during deformation. This method is verified and is useful for the structural Identification of the simulations results.

Cite This Article

APA Style
Chen, K., Yang, A., Lee, W., Tseng, Y., Tsou, N. et al. (2019). Classification of crystallographic groups of alloy systems by isomap and modularity methods. The International Conference on Computational & Experimental Engineering and Sciences, 21(3), 54-54. https://doi.org/10.32604/icces.2019.05401
Vancouver Style
Chen K, Yang A, Lee W, Tseng Y, Tsou N, Chen N. Classification of crystallographic groups of alloy systems by isomap and modularity methods. Int Conf Comput Exp Eng Sciences . 2019;21(3):54-54 https://doi.org/10.32604/icces.2019.05401
IEEE Style
K. Chen, A. Yang, W. Lee, Y. Tseng, N. Tsou, and N. Chen, “Classification of Crystallographic Groups of Alloy Systems by Isomap and Modularity Methods,” Int. Conf. Comput. Exp. Eng. Sciences , vol. 21, no. 3, pp. 54-54, 2019. https://doi.org/10.32604/icces.2019.05401



cc Copyright © 2019 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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