University of Oulu

Gyakwaa, F., Aula, M., Vuolio, T., Alatarvas, T., Shu, Q., Huttula, M., & Fabritius, T. (2020). Characterization of Multiphase Mixtures of Calcium Aluminates and Magnesium Aluminate Spinel Using Time‐Gated Raman Spectroscopy. Steel Research International, 91(8), 2000084. https://doi.org/10.1002/srin.202000084

Characterization of multiphase mixtures of calcium aluminates and magnesium aluminate spinel using time-gated Raman spectroscopy

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Author: Gyakwaa, Francis1; Aula, Matti1; Vuolio, Tero1;
Organizations: 1Process Metallurgy Research Unit, University of Oulu
2Nano and Molecular Systems Research Unit, University of Oulu
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 2.4 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2020090367371
Language: English
Published: John Wiley & Sons, 2020
Publish Date: 2020-09-03
Description:

Abstract

In aluminum‐killed calcium‐treated steels, the characterization of multiphase oxides found in the CaO–MgO–Al2O3 system is essential for the study of inclusion formation, modification, and the control process. Herein, Raman spectroscopy is used as a characterization technique for the multiphase mixtures of MgO·Al₂O₃ spinel and calcium aluminate phases of C12A7, C3A, and CA. Multiphase samples of C12A7–CA–MA and C12A7–C3A–MA are synthesized from MgO·Al₂O₃ spinel and calcium aluminates with varying phase content. The relative intensity of the Raman peaks is qualitatively used for the most primary phases present in the sample. Regression models are also identified for predicting the phase composition. Prediction model identification is conducted using the successive projection algorithm (SPA) for feature selection and the partial least squares regression (PLS) model as a regressor. The identified prediction models show a reasonably good prediction performance. Herein, the time‐gated Raman spectroscopy technique to characterize the multiphase mixture of magnesium aluminate spinel and calcium aluminate phases of CA, C12A7, C3A is used, and the potential application for inclusion characterization is demonstrated.

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Series: Steel research international
ISSN: 1611-3683
ISSN-E: 1869-344X
ISSN-L: 1611-3683
Volume: 91
Issue: 8
Article number: 2000084
DOI: 10.1002/srin.202000084
OADOI: https://oadoi.org/10.1002/srin.202000084
Type of Publication: A1 Journal article – refereed
Field of Science: 216 Materials engineering
215 Chemical engineering
Subjects:
Funding: The authors acknowledge the support of I4Future doctoral programme funded by European Union's H2020 under the Marie Skłodowska‐Curie grant agreement no. 713606 and Academy of Finland Profilation project (Academy of Finland, no. 311934).
EU Grant Number: (713606) I4FUTURE - Novel Imaging and Characterisation Methods in Bio, Medical, and Environmental Research and Technology Innovations
Academy of Finland Grant Number: 311934
Detailed Information: 311934 (Academy of Finland Funding decision)
Copyright information: © 2020 The Authors. Published by WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
  https://creativecommons.org/licenses/by/4.0/