Advanced Electron Microscopy Image Processing for Analyzing Amorphous Alloys: Electron Microscopy Image Cluster Analyzer (EMICA). Tool and Results

Cover Page

Cite item

Full Text

Open Access Open Access
Restricted Access Access granted
Restricted Access Subscription Access

Abstract

This article unveils EMICA, a Python-based software tool revolutionizing electron microscopy image processing for amorphous alloys. EMICA addresses the unique challenges posed by these materials, which lack long-range order, by providing specialized capabilities for cluster analysis and spatial pattern recognition. This research explored software tool development and application through illustrative examples, answering the key question of how they enhance amorphous alloy analysis. By integrating advanced image processing techniques and algorithms, EMICA uncovers hidden patterns, offering quantitative insights into cluster distributions. The key message emphasizes the application’s transformative impact on material science research, providing a specialized solution for electron microscopy image analysis in the amorphous alloy domain. Our key findings, presented through real-world examples and case studies, attest to the efficacy of the software in revealing nuanced details of amorphous alloy structures. From identifying subtle variations in atomic configurations to quantifying cluster distributions, EMICA represents a significant leap forward in the field of advanced electron microscopy image processing, contributing significantly to the advancement of this domain.

Full Text

Restricted Access

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, Vladivostok

Evgeniy V. Pustovalo

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, Vladivostok

Alexander 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 Technologie

Russian Federation, Vladivostok

References

  1. Klement W., Willens R.H., Duwez P. Nature. 1960. No. 187. P. 869.
  2. Egami T., Maed K., Srolovitz D., Vitek V. J. Phys. Colloques. 1980. No. 41. Pp. 8–272.
  3. Fratila A., Jimenez-Marcos C., Mirza-Rosca J.C., Saceleanu A. Mat. Chem. Phys. 2023. No. 304. P. 127867.
  4. Modin E.B., Pustovalov E.V., Fedorets A.N. et al. J. Alloys Comp. 2015. No. 641. Pp. 139–143.
  5. Pustovalov E.V., Modin E.B., Frolov A.M. et al. J. Surf Invest: X-Ray, Synchrotron and Neutron Techniques. 2019. No. 13. Pp. 600–608.
  6. Pustovalov E.V., Modin, E.B., Kirillov A.V. et al. Bulletin of the Russian Academy of Sciences: Physics. 2014. No. 78 (9). Pp. 890–893.
  7. Jena P., Castleman A.W. Jr. Nanoclusters: A bridge across disciplines. Burlington, MA: Elsevier, 2010. 593 p.
  8. Sørensen K.H., Jørgensen M.S., Bruix A., Hammer B. J. Chem. Phys. 2018. No. 148 (24). P. 241734.
  9. Ranita, P., Arpita P., Chattaraj P.K. Frontiers in Chemistry. 2021. No. 9. P. 730548.

Supplementary files

Supplementary Files
Action
1. JATS XML
2. Fig. 1. Original electron microscopy image of the amorphous alloys CoP and NiW

Download (474KB)
3. Fig. 2. Cluster point distribution

Download (481KB)
4. Fig. 3. Cluster visualizations for clusters

Download (18KB)
5. Fig. 4. Probability distribution of angle

Download (33KB)
6. Fig. 5. Cluster point distribution probability chart

Download (37KB)


This website uses cookies

You consent to our cookies if you continue to use our website.

About Cookies