Exploring Amorphous Alloys: Advanced Electron Microscopy and Cluster Analysis
- Authors: Sileshi D.1, Pustovalov E.V.1, Fedorets A.N.1, Frolov A.M.1
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Affiliations:
- Far Eastern Federal University
- Issue: Vol 11, No 1 (2024)
- Pages: 112-120
- Section: MATHEMATICAL AND SOFTWARE OF COMPUTЕRS, COMPLEXES AND COMPUTER NETWORKS
- URL: https://journals.eco-vector.com/2313-223X/article/view/631296
- DOI: https://doi.org/10.33693/2313-223X-2024-11-1-112-120
- ID: 631296
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Abstract
In this study, we explored the atomic structure and orderliness of amorphous alloys through advanced electron microscopy and analytical techniques. Amorphous alloys, characterized by disordered atomic structures, exhibit promising applications in technology. The research addresses a crucial knowledge gap by investigating cluster distribution, particle arrangement, and orderliness within the amorphous matrix. High-resolution electron microscopy (HREM) images are analyzed using diverse algorithms and software tools. The study establishes a correlation between angles approaching 180 degrees and increased orderliness within clusters, highlighting the reliability of angle distribution analysis. Robust indicators, including Div (SP(B/V)) and Div (Mu(B/V)) metrics, assess and compare amorphous alloy samples. Kullback–Leibler (K-L) divergence indicates the significance of cluster ordering, validated by the S-K test. Radial Distribution Function (RDF) analysis uncovers local short-range order, deepening understanding despite limited orderliness discernment. These findings not only enhance our understanding of metallic glasses or amorphous alloys but also offer opportunities for tailored design and improved applications across various technological domains.
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About the authors
Dilla Dagim Sileshi
Far Eastern Federal University
Author for correspondence.
Email: dilla.d@dvfu.ru
ORCID iD: 0000-0002-9100-1257
PhD student, Institute of Mathematics and Computer Technologies, research engineer, Electron Microscopy and Imaging Laboratory
Russian Federation, VladivostokEvgeniy V. Pustovalov
Far Eastern Federal University
Email: pustovalov.ev@dvfu.ru
ORCID iD: 0000-0003-1036-3975
Dr. Sci. (Phys.-Math.), Professor, Department of Information and Computer Systems, Institute of Mathematics and Computer Technologies, Head of the educational program 09.03.02 “Information systems and technologies”, profile “Programming of robotic systems”
Russian Federation, VladivostokAlexander N. Fedorets
Far Eastern Federal University
Email: fedorec.an@dvfu.ru
ORCID iD: 0000-0001-9007-3171
senior lecturer, Department of Information and Computer Systems, Institute of Mathematics and Computer Technologies
Russian Federation, VladivostokAnatoliy M. Frolov
Far Eastern Federal University
Email: frolov.am@dvfu.ru
ORCID iD: 0000-0002-5368-5694
Dr. Sci. (Phys.-Math.), associate professor, Department of Information and Computer Systems, Institute of Mathematics and Computer Technologies
Russian Federation, VladivostokReferences
- Modin E.B., Pustovalov E.V., Fedorets A.N. et al. Atomic structure and crystallization processes of amorphous (co, ni)–p metallic alloy. Journal of Alloys and Compounds. 2015. No. 641. Pp. 139–143.
- Turnbull D., Cohen M.H. Under what conditions can a glass be formed? Contemporary Physics. 1970. No. 11 (5). Pp. 473–488.
- Chen D.Z., Qi Y., Shen J. Visualization of the atomic structure of metallic glasses by high-resolution transmission electron microscopy. Nature. 2008. No. 454 (7203). Pp. 892–895.
- Shen J., Ma E., Chen D.Z. Atomic-level structure and structure–property relationship in metallic glasses. Progress in Materials Science. 2014. No. 60. Pp. 284–341.
- Pustovalov E.V., Modin E.B., Frolov A.M. et al. Effect of the process conditions for the preparation of conifesib amorphous alloys on their structure and properties. Journal of Surface Investigation: X-Ray, Synchrotron and Neutron Techniques. 2019. No. 13(4). Pp. 600–608.
- Dokmanic I., Parhizkar R., Ranieri J., Vetterli M. Euclidean distance matrices: Essential theory, algorithms, and applications. IEEE Signal Processing Magazine. 2015. No. 32 (6). Pp. 12–30.
- Kuleshov E.L. Interval estimation of the probability distribution function. Optoelectronics, Instrumentation and Data Processing. 2015. No. 51 (2). Pp. 120–123.
- Kuleshov E.L. Goodness-of-fit test based on the interval estimation. Opto- electronics, Instrumentation and Data Processing. 2016. No. 52 (1). Pp. 24–29.
- Kullback S., Leibler R.A. On information and sufficiency. The Annals of Mathematical Statistics. 1951. No. 22 (1). Pp. 79–86.
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