Exploring Amorphous Alloys: Advanced Electron Microscopy and Cluster Analysis

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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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作者简介

Dilla Dagim Sileshi

Far Eastern Federal University

编辑信件的主要联系方式.
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

俄罗斯联邦, Vladivostok

Evgeniy 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”

俄罗斯联邦, Vladivostok

Alexander 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

俄罗斯联邦, Vladivostok

Anatoliy 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

俄罗斯联邦, Vladivostok

参考

  1. 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.
  2. Turnbull D., Cohen M.H. Under what conditions can a glass be formed? Contemporary Physics. 1970. No. 11 (5). Pp. 473–488.
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. Kuleshov E.L. Interval estimation of the probability distribution function. Optoelectronics, Instrumentation and Data Processing. 2015. No. 51 (2). Pp. 120–123.
  8. 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.
  9. 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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2. Fig. 1. Examples of HRTEM images and scatterplot graph: a – HRTEM image CoP; b – HRTEM image-NiW; c – Scatterplot graph of the NiW sample

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3. Fig. 2. Cluster visualizations for clusters of sizes 4, 5, and 6

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4. Fig. 3. Cluster points distribution for multiple samples, illustrating the relationship between cluster size and orderedness

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5. Fig. 4. Linearized Kullback–Leibler divergence for bonds to vertices ratio CDF (Div (SP(B/V) on left axis) and for Lebesgue measure for bonds to vertices ratio (Div (Mu(B/V) on right axis) depending on level of ordering in the images

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6. Fig. 5. Probability distributions of angles for six samples, with a reference sample characterized by a high degree of orderedness

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7. Fig. 6. Radial distribution function for amorphous alloys

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