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Characterization of Metallic Materials: Solidification, Deformation, Heat Treatment and Other Related Phenomena—Third Edition

A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Metals and Alloys".

Deadline for manuscript submissions: 20 September 2025 | Viewed by 1005

Special Issue Editors


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Guest Editor
Industrial Materials and Process R&D Department, Korea Institute of Industrial Technology (KITECH), Incheon 21999, Republic of Korea
Interests: metals and alloys; thermodynamic calculation; phase diagram; solidification; metal oxidation
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Materials Supply Chain R&D Department, Korea Institute of Industrial Technology, Incheon 21999, Republic of Korea
Interests: metals and alloys; metal forming
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue features research and review articles on the characterization of metallic materials under various material conditions such as solidification, formation, and heat treatment. This Special Issue focuses on all types of characterization methods, including all forms of microscopy (transmission electron microscopy, scanning electron microscopy, etc.) and analytical techniques related to microstructure, interface, surface, etc. Studies focusing on analysis using computational science are also welcome. Recent studies dealing with the behavior of materials under various phenomena (solidification, phase transformation, oxidation, diffusion, deformation, and so on) that can occur in processes such as casting, plastic working, and heat treatment are suitable for publication in this Special Issue. This Special Issue will provide materials scientists with up-to-date information explaining the behavior of many types of metallic materials using novel approaches. This Special Issue covers all kinds of metallic materials.

Dr. Seong-Ho Ha
Dr. Young-Ok Yoon
Guest Editors

Manuscript Submission Information

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Keywords

  • metals and alloys
  • microstructure characterization
  • microscopy
  • solidification
  • forming
  • heat treatment

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Published Papers (3 papers)

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Research

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11 pages, 3535 KiB  
Article
Effect of Fe Content on Phase Behavior of Sm–Co–Fe Alloys During Solidification and Aging
by Zhi Zhu, Yikun Fang, Wei Wu, Bo Zhao, Meng Zheng, Ming Lei and Jiashuo Zhang
Materials 2025, 18(8), 1854; https://doi.org/10.3390/ma18081854 - 17 Apr 2025
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Abstract
The effect of different Fe contents on the phases of Sm–Co–Fe ternary alloys during solidification is investigated herein by melting the alloys using a non-consumable vacuum arc furnace. In particular, the phases of the Sm25.5CobalFex (x = [...] Read more.
The effect of different Fe contents on the phases of Sm–Co–Fe ternary alloys during solidification is investigated herein by melting the alloys using a non-consumable vacuum arc furnace. In particular, the phases of the Sm25.5CobalFex (x = 19, 21, 23, and 25 wt.%) alloys are investigated after solidification and aging. The results obtained from Cai Li’s modified Miedema model show a strong interaction between the Sm–Co alloy atoms. Additionally, the results obtained from the Toop geometric model show a strong interaction between the Sm–Co–Fe ternary alloy atoms, enabling the formation of intermetallic compounds. The experimental results show that when the Sm content is 25.5 wt.%, the SmCo5 phase gradually decreases as the Fe content increases and disappears when the Fe content is 25 wt.%. Thermodynamic calculations show that when the Fe content is 19 wt.%, there is a region where the SmCo5 and Sm2Co17 phases co-exist. As the Fe content increases, this region gradually decreases. For a 25 wt.% Fe content, the Sm2Co17 and SmCo5 two-phase region does not appear when the Sm content varies. The samples are aged at 1143 °C for 12 h, then melted and cut. The phase results obtained by scanning are consistent with the calculated results. In this study, the effect of each constituent element of Sm–Co–Fe ternary alloys on their solidification phases is investigated, providing a strong foundation for studying the 2:17-type Sm–Co magnetic materials obtained after melting and aging a five-element Sm–Co alloy. Full article
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14 pages, 10319 KiB  
Article
Effect of Transition Layers on the Microstructure and Properties of CMT Additively Manufactured Steel/Copper Specimens
by Xuyang Guo, Yulang Xu, Jingyong Li and Cheng Zhang
Materials 2025, 18(8), 1734; https://doi.org/10.3390/ma18081734 - 10 Apr 2025
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Abstract
During the cold metal transfer (CMT) arc additive manufacturing process of steel/copper bimetallic materials, interfacial penetration cracks have been observed due to the significant differences in thermal and physical properties between steel and copper. To mitigate the occurrence of these penetration cracks and [...] Read more.
During the cold metal transfer (CMT) arc additive manufacturing process of steel/copper bimetallic materials, interfacial penetration cracks have been observed due to the significant differences in thermal and physical properties between steel and copper. To mitigate the occurrence of these penetration cracks and enhance the interfacial elemental diffusion at the steel/copper junction, this study aims to fabricate high-performance steel/copper bimetallic materials with a uniform microstructure using CMT arc additive manufacturing techniques. A reciprocating additive sequence was adopted, with steel deposited first, followed by copper. Four different interlayer compositions, Cu-Ni, Fe-Ni, Cu-Cr, and Ni-Cr, were applied to the steel surface before the deposition of aluminum bronze. These interlayers served as a transition between the steel and copper materials. The manufacturing process then continued with the deposition of aluminum bronze to achieve the desired bimetallic structure. After the addition of interlayers, all four sets of samples exhibited excellent macroscopic formability, with clear and smooth interlayer contours and no visible cracks or collapse defects at the junction interfaces. The mechanical properties of the composite walls were enhanced following the addition of the interlayers, with an increase in tensile strength observed across the samples. The sample with the Fe-Ni interlayer showed the most significant improvement, with a 52% increase in impact energy absorption. Furthermore, the sample with the Fe-Ni interlayer demonstrated a higher average hardness level than the other groups, which was associated with the distribution and content of the iron-rich phase and the β′ phase. Full article
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Review

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17 pages, 1688 KiB  
Review
Application of Machine Learning in Amorphous Alloys
by Like Zhang, Huangyou Zhang, Boyan Ji, Leqing Liu, Xianlan Liu and Ding Chen
Materials 2025, 18(8), 1771; https://doi.org/10.3390/ma18081771 - 13 Apr 2025
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Abstract
In the past few decades, traditional methods for developing amorphous alloys, such as empirical trial-and-error approaches and density functional theory (DFT)-based calculations, have enabled researchers to explore numerous amorphous alloy systems and investigate their properties. However, these methods are increasingly unable to meet [...] Read more.
In the past few decades, traditional methods for developing amorphous alloys, such as empirical trial-and-error approaches and density functional theory (DFT)-based calculations, have enabled researchers to explore numerous amorphous alloy systems and investigate their properties. However, these methods are increasingly unable to meet the demands of modern research due to their long development cycles and low efficiency. In contrast, machine learning (ML) has gained widespread adoption in the design, analysis, and property prediction of amorphous alloys due to its advantages of low experimental cost, powerful performance, and short development cycles. This review focuses on four key applications of ML in amorphous alloys: (1) prediction of amorphous alloy phases, (2) prediction of amorphous composite phases, (3) prediction of glass-forming ability (GFA), and (4) prediction of material properties. Finally, we outline future directions for ML in materials science, including the development of more sophisticated models, integration with high-throughput experimentation, and the creation of standardized data-sharing platforms. These insights provide potential research directions and frameworks for subsequent studies in this field. Full article
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