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Advanced Chemometric analysis of photoemission Electron microscopy imaging for detecting non-metallic inclusions in steel materials

Kharbach, Mourad ; Rani, Ekta ; Mansouri, Mohammed Alaoui ; Singh, Harishchandra ; Alatarvas, Tuomas ; Sarpi, Brice LU ; Zhu, Lin LU orcid ; Niu, Yuran LU ; Zakharov, Alexei LU and Launonen, Ilkka , et al. (2024) In Materials Characterization 215.
Abstract

The accurate identification of non-metallic inclusions (NMIs) within steel matrices is critical for high-quality steel production. This study employs synchrotron radiation-based X-ray absorption photoemission electron microscopy (X-PEEM) to investigate NMIs in ultra-high-strength steels. Ca-L2,3-edge X-ray absorption spectra were acquired for six NMIs at both room temperature and 400 °C, allowing a comprehensive exploration of structural changes, chemical compositions, and phases. Complex X-PEEM images were analyzed using advanced chemometric techniques, including Principal Component Analysis (PCA), K-means clustering, Fuzzy-means clustering (FMC), and Multivariate Curve Resolution–Alternating Least Squares (MCR-ALS). These... (More)

The accurate identification of non-metallic inclusions (NMIs) within steel matrices is critical for high-quality steel production. This study employs synchrotron radiation-based X-ray absorption photoemission electron microscopy (X-PEEM) to investigate NMIs in ultra-high-strength steels. Ca-L2,3-edge X-ray absorption spectra were acquired for six NMIs at both room temperature and 400 °C, allowing a comprehensive exploration of structural changes, chemical compositions, and phases. Complex X-PEEM images were analyzed using advanced chemometric techniques, including Principal Component Analysis (PCA), K-means clustering, Fuzzy-means clustering (FMC), and Multivariate Curve Resolution–Alternating Least Squares (MCR-ALS). These methods allowed for the segmentation of X-PEEM images into distinct compositional zones. K-means clustering effectively identified regions of interest (ROIs) within NMIs, while PCA facilitated the microstructure variances of NMIs. Additionally, K-means and FMC revealed detailed compositional variations at the nanoscale. MCR-ALS proved particularly useful in uncovering changes in NMIs after annealing. This study pioneers the integration of X-PEEM with advanced chemometric methodologies, providing qualitative and quantitative spectromicroscopic insights. It significantly enhances our understanding of NMIs formation and alteration processes in ultra-high-strength steels, contributing to the advancement of materials science and steel production optimization. Furthermore, the methodologies and findings presented here serve as a guide for analyzing similar data sets of steel samples, offering valuable insights for future research and industrial applications in steel engineering.

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publication status
published
subject
keywords
Chemometric data analysis, Non-metallic inclusions, Photoemission electron microscopy, Steel properties, Synchrotron X-ray absorption
in
Materials Characterization
volume
215
article number
114114
publisher
Elsevier
external identifiers
  • scopus:85197426317
ISSN
1044-5803
DOI
10.1016/j.matchar.2024.114114
language
English
LU publication?
yes
id
86953584-c450-4f57-97bf-f85f21d3ab75
date added to LUP
2024-09-10 16:23:40
date last changed
2025-04-04 14:56:15
@article{86953584-c450-4f57-97bf-f85f21d3ab75,
  abstract     = {{<p>The accurate identification of non-metallic inclusions (NMIs) within steel matrices is critical for high-quality steel production. This study employs synchrotron radiation-based X-ray absorption photoemission electron microscopy (X-PEEM) to investigate NMIs in ultra-high-strength steels. Ca-L<sub>2,3</sub>-edge X-ray absorption spectra were acquired for six NMIs at both room temperature and 400 °C, allowing a comprehensive exploration of structural changes, chemical compositions, and phases. Complex X-PEEM images were analyzed using advanced chemometric techniques, including Principal Component Analysis (PCA), K-means clustering, Fuzzy-means clustering (FMC), and Multivariate Curve Resolution–Alternating Least Squares (MCR-ALS). These methods allowed for the segmentation of X-PEEM images into distinct compositional zones. K-means clustering effectively identified regions of interest (ROIs) within NMIs, while PCA facilitated the microstructure variances of NMIs. Additionally, K-means and FMC revealed detailed compositional variations at the nanoscale. MCR-ALS proved particularly useful in uncovering changes in NMIs after annealing. This study pioneers the integration of X-PEEM with advanced chemometric methodologies, providing qualitative and quantitative spectromicroscopic insights. It significantly enhances our understanding of NMIs formation and alteration processes in ultra-high-strength steels, contributing to the advancement of materials science and steel production optimization. Furthermore, the methodologies and findings presented here serve as a guide for analyzing similar data sets of steel samples, offering valuable insights for future research and industrial applications in steel engineering.</p>}},
  author       = {{Kharbach, Mourad and Rani, Ekta and Mansouri, Mohammed Alaoui and Singh, Harishchandra and Alatarvas, Tuomas and Sarpi, Brice and Zhu, Lin and Niu, Yuran and Zakharov, Alexei and Launonen, Ilkka and Huttula, Marko and Sillanpää, Mikko J. and Urpelainen, Samuli}},
  issn         = {{1044-5803}},
  keywords     = {{Chemometric data analysis; Non-metallic inclusions; Photoemission electron microscopy; Steel properties; Synchrotron X-ray absorption}},
  language     = {{eng}},
  publisher    = {{Elsevier}},
  series       = {{Materials Characterization}},
  title        = {{Advanced Chemometric analysis of photoemission Electron microscopy imaging for detecting non-metallic inclusions in steel materials}},
  url          = {{http://dx.doi.org/10.1016/j.matchar.2024.114114}},
  doi          = {{10.1016/j.matchar.2024.114114}},
  volume       = {{215}},
  year         = {{2024}},
}