Metals

14 pages, 6858 KB

Open AccessArticle

Path Optimization of Laser Welding for Large-Scale Tube-to-Tubesheet

by Xuqiang Kang, Chuchuan Cao, Bingqi Wang and Anguo Huang

Metals 2026, 16(2), 147; https://doi.org/10.3390/met16020147 (registering DOI) - 25 Jan 2026

To address issues of residual stress concentration and deformation in large-scale multi-seam laser welding of tube-to-tubesheet, we established a 12 mm thick Q235 steel simulation model. The model considers the material’s high-temperature performance and mechanical properties. We designed three welding paths: sequential welding, [...] Read more.

To address issues of residual stress concentration and deformation in large-scale multi-seam laser welding of tube-to-tubesheet, we established a 12 mm thick Q235 steel simulation model. The model considers the material’s high-temperature performance and mechanical properties. We designed three welding paths: sequential welding, block-by-block symmetrical welding, and inward–outward symmetrical radial welding. The welding simulation software InteWeld 4.0 was used to study the effects of these paths on deformation. Results showed that the inside-out symmetric radiation welding path disperses heat input effectively. It prevents stiffness reduction from local heat accumulation. By using symmetrically distributed shrinkage forces that offset each other, this path greatly inhibits deformation accumulation. The maximum deformation was only 1.6 mm—5.9% and 33% lower than with block-by-block symmetric welding (1.7 mm) and sequential welding (2.4 mm). This path also resulted in a uniform residual stress distribution, with a maximum stress of only 250 MPa, making it the best option for suppressing deformation. Full article

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30 pages, 4895 KB

Open AccessArticle

Technological and Chemical Drivers of Zinc Coating Degradation in DX51d+Z140 Cold-Formed Steel Sections

by Volodymyr Kukhar, Andrii Kostryzhev, Oleksandr Dykha, Oleg Makovkin, Ihor Kuziev, Roman Vakulenko, Viktoriia Kulynych, Khrystyna Malii, Eleonora Butenko, Natalia Hrudkina, Oleksandr Shapoval, Sergiu Mazuru and Oleksandr Hrushko

Metals 2026, 16(2), 146; https://doi.org/10.3390/met16020146 (registering DOI) - 25 Jan 2026

Abstract

This study investigates the technological and chemical causes of early zinc-coating degradation on cold-formed steel sections produced from DX51D+Z140 galvanized coils. Commercially manufactured products exhibiting early corrosion symptoms were used in this study. The entire processing route, which included strip preparation, cold rolling, [...] Read more.

This study investigates the technological and chemical causes of early zinc-coating degradation on cold-formed steel sections produced from DX51D+Z140 galvanized coils. Commercially manufactured products exhibiting early corrosion symptoms were used in this study. The entire processing route, which included strip preparation, cold rolling, hot-dip galvanizing, passivation, multi-roll forming, storage, and transportation to customers, was analyzed with respect to the residual surface chemistry and process-related deviations that affect the coating integrity. Thirty-three specimens were examined using electromagnetic measurements of coating thickness. Statistical analysis based on the Cochran’s and Fisher’s criteria confirmed that the increased variability in zinc coating thickness is associated with a higher susceptibility to localized corrosion. Surface and chemical analysis revealed chloride contamination on the outer surface, absence of detectable Cr(VI) residues indicative of insufficient passivation, iron oxide inclusions beneath the zinc coating originating from the strip preparation, traces of organic emulsion residues impairing wetting and adhesion, and micro-defects related to deformation during roll forming. Early zinc coating degradation was shown to result from the cumulative action of multiple technological (surface damage during rolling, variation in the coating thickness) and environmental (moisture during storage and transportation) parameters. On the basis of the obtained results, a methodology was proposed to prevent steel product corrosion in industrial conditions. Full article

(This article belongs to the Special Issue Corrosion Behavior and Surface Engineering of Metallic Materials)

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14 pages, 15800 KB

Open AccessArticle

Effect of Heat Treatment Process on Microstructure and Mechanical Properties of As-Cast Mg-8Gd-1Y-2Sm-1.2Zn-0.5Mn Alloy

by Zirui Qiao, Feng Wang, Chun Xue, Chaojie Che and Zhibing Chu

Metals 2026, 16(2), 145; https://doi.org/10.3390/met16020145 (registering DOI) - 25 Jan 2026

Abstract

This study investigates the as-cast Mg-8Gd-1Y-2Sm-1.2Zn-0.5Mn (wt.%) alloy with high rare-earth content. Solution treatments were conducted at 480 °C, 520 °C, and 560 °C for 6–10 h. Microstructure and mechanical properties were characterized using OM, XRD, SEM-EDS, and compression testing. The as-cast alloy [...] Read more.

This study investigates the as-cast Mg-8Gd-1Y-2Sm-1.2Zn-0.5Mn (wt.%) alloy with high rare-earth content. Solution treatments were conducted at 480 °C, 520 °C, and 560 °C for 6–10 h. Microstructure and mechanical properties were characterized using OM, XRD, SEM-EDS, and compression testing. The as-cast alloy shows a dendritic structure with continuous grain-boundary phases (Mg₅RE, W, and LPSO), exhibiting a compressive yield strength of 145 MPa, ultimate strength of 238 MPa, and fracture strain of 12.66%. Solution temperature has a critical influence on phase dissolution and grain refinement. Notably, the overall plasticity of the material did not show a significant dependence on the specific solution temperature or holding time within the studied range. Treatment at 520 °C produces the most balanced microstructure: clear grain boundaries, extensive phase dissolution, refined grains, and enhanced solid-solution strengthening. Specifically, 520 °C for 10 h results in the finest and most uniformly distributed residual phases, a homogeneous matrix, the highest compressive strength, and suitable conditions for subsequent aging, thus being identified as optimal. Fractography reveals a transition from quasi-cleavage in the as-cast state toward enhanced ductility after solution treatment. However, small cleavage facets after 10 h are attributed to stress concentrations from rare-earth-rich regions and reduced deformation compatibility due to retained LPSO phases. Full article

(This article belongs to the Special Issue Heat Treatment, Microstructures, and Mechanical Properties of Metallic Materials)

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27 pages, 4994 KB

Open AccessReview

Slip Irreversibility, Microplasticity, and Fatigue Cracking Mechanism in Near-α and α + β Titanium Alloys

by Adam Ismaeel, Xuexiong Li, Xirui Jia, Ali Jamea, Zongxu Chen, Xuanming Feng, Dongsheng Xu, Xiaohu Chen and Weining Lei

Metals 2026, 16(2), 144; https://doi.org/10.3390/met16020144 (registering DOI) - 25 Jan 2026

Abstract

The micromechanisms “slip transfer, slip irreversibility, microplasticity, and fatigue cracking” in titanium alloys are reviewed, with a special emphasis on near-α and α + β alloys. As the interplay between slip activity, microplasticity, and fatigue cracking governs both the microscale and macroscale [...] Read more.

The micromechanisms “slip transfer, slip irreversibility, microplasticity, and fatigue cracking” in titanium alloys are reviewed, with a special emphasis on near-α and α + β alloys. As the interplay between slip activity, microplasticity, and fatigue cracking governs both the microscale and macroscale mechanical response, we reveal how the slip irreversibility and localized dislocation activity at the grain boundaries (GBs) and α/β interfaces generate dislocation pile-ups and strain localization, subsequently driving fatigue crack initiation and propagation. The review highlights the favorable crack initiation along basal planes and the roles of α grain orientations, slip transfer barriers, and the β phase in governing fatigue cracking, while addressing unresolved questions about localized interactions and texture effects. It also explores the complex interactions that govern the effects of microstructures, textures, and defects on fatigue cracking. Ultimately, the review provides a unified framework for linking slip events to microplasticity and to fatigue failure, offering actionable insights for alloy design and fatigue prediction. Full article

(This article belongs to the Special Issue Failure Analysis and Failure Mechanism of Metallic Materials—State of the Art)

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16 pages, 3143 KB

Open AccessArticle

Effects of Combined Cr, Mn, and Zr Additions on the Microstructure and Mechanical Properties of Al–6Cu Alloys Under Various Heat Treatment Conditions

by Hyuncheul Lee, Jaehui Bang, Pilhwan Yoon and Eunkyung Lee

Metals 2026, 16(2), 143; https://doi.org/10.3390/met16020143 (registering DOI) - 25 Jan 2026

Abstract

This study investigates the synergistic effects of Cr–Zr and Mn–Zr additions on the microstructural evolution and mechanical properties of Al–6 wt.%Cu alloys. Alloys were designed with solute concentrations positioned below, near, and above their maximum solubility limits, and were evaluated under as-cast, T4, [...] Read more.

This study investigates the synergistic effects of Cr–Zr and Mn–Zr additions on the microstructural evolution and mechanical properties of Al–6 wt.%Cu alloys. Alloys were designed with solute concentrations positioned below, near, and above their maximum solubility limits, and were evaluated under as-cast, T4, and T6 heat treatment conditions. Mechanical testing revealed distinct behavioral trends depending on the heat treatment: the T4 heat treatment condition generally exhibited superior hardness and yield strength, whereas the T6 heat treatment condition resulted in a slight reduction in hardness but facilitated a significant recovery in tensile strength and structural stability, particularly in alloys designed near the solubility limit. To elucidate the crystallographic origins of these mechanical variations, X-ray diffraction analysis was conducted to monitor changes in lattice parameters, dislocation density, and micro-strain. The results showed that T4 heat treatment induced lattice contraction and a decrease in dislocation density, suggesting that the high strength under T4 heat treatment conditions arises from lattice distortion caused by supersaturated solute atoms. Conversely, T6 aging led to lattice relaxation approaching that of pure aluminum, yet simultaneously triggered a re-accumulation of dislocation density and micro-strain due to the coherency strain fields surrounding precipitates, which effectively impede dislocation motion. Therefore, rather than proposing a single, definitive optimization condition, this study aims to secure foundational data regarding the correlation between these microstructural descriptors and mechanical behavior, providing a guideline for balancing the strengthening contributions in transition metal-modified Al–Cu alloys. Full article

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16 pages, 2907 KB

Open AccessArticle

Parallel Hybrid Modeling of Al–Mg–Si Tensile Properties Using Density-Based Weighting

by Christian Dalheim Øien, Ole Runar Myhr and Geir Ringen

Metals 2026, 16(2), 142; https://doi.org/10.3390/met16020142 (registering DOI) - 25 Jan 2026

Abstract

A hybrid modeling framework for predicting the mechanical properties of Al-Mg-Si alloys, that blends physics-based and machine-learning models, is developed and tested. Motivated by a demand for post-consumer material (PCM) content in wrought aluminium applications, this work proposes, analyses, and discusses a parallel [...] Read more.

A hybrid modeling framework for predicting the mechanical properties of Al-Mg-Si alloys, that blends physics-based and machine-learning models, is developed and tested. Motivated by a demand for post-consumer material (PCM) content in wrought aluminium applications, this work proposes, analyses, and discusses a parallel framework that applies an adaptive weighting coefficient derived from local observation density. Based on existing datasets from a range of Al-Mg-Si alloys, such a model is trained and tested in an iterative manner to study its robustness, by emulating a shift in observed alloy composition. The results indicate that the hybrid model is able to combine the interpolative strength of machine learning for cases similar to previous observations with the explorative strength of physics-based (Kampmann–Wagner Numerical) modeling for previously unobserved parameter combinations, as the hybrid model shows higher or similar accuracy than the best of its constituents across the majority of the sequence. The observed model characteristics are promising for predicting the effect of increased compositional variation inherent in PCM. Finally, possible future research is discussed. Full article

(This article belongs to the Special Issue Application of Machine Learning in Metallic Materials)

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14 pages, 11061 KB

Open AccessArticle

On Microstructure Evolution and Magnetic Properties of Annealed FeNiCrMn Alloy

by Yu Zhang, Caili Ma, Jingwen Gao, Wenjie Chen, Song Zhang and Xia Huang

Metals 2026, 16(2), 141; https://doi.org/10.3390/met16020141 (registering DOI) - 24 Jan 2026

Abstract

Fe-Ni-based alloys have attracted attention due to their potential for applications such as transmission line de-icing, where the core requirements include a Curie temperature near the freezing point and sufficient saturation magnetization. Accordingly, this study designed an Fe-29Ni-2Cr-1.5Mn (at.%) alloy with a Curie [...] Read more.

Fe-Ni-based alloys have attracted attention due to their potential for applications such as transmission line de-icing, where the core requirements include a Curie temperature near the freezing point and sufficient saturation magnetization. Accordingly, this study designed an Fe-29Ni-2Cr-1.5Mn (at.%) alloy with a Curie temperature around the freezing point, aiming to investigate the correlation between microstructural evolution and magnetic properties after cold rolling and annealing. The alloy was cold-rolled by 65% and subsequently annealed at 873 K for 0 to 60 min. The study reveals systematic evolutions in the alloy’s microstructure and magnetic properties. During the initial annealing stage, recovery substructures predominantly formed within the deformed grains, accompanied by a reduction in dislocation density and lattice constant. In the later annealing stage, the recrystallized fraction increased, although complete recrystallization was not achieved. Texture analysis indicates that the intensity of the Cube texture strengthened from 0.48 to 1.13. Correspondingly, the saturation magnetization and Curie temperature increased by approximately 9.76% and 10.25%, respectively, in the early annealing period, and then stabilized thereafter. The early-stage improvement in properties is likely related to stress relief and lattice distortion relaxation during the recovery stage. The calculated magnetocrystalline anisotropy constant of this alloy at 273 K is K₁ = 126 ± 18 J/m³, indicating that the <100> direction is its easy magnetization axis. This study provides insights into optimizing the magnetic properties of this alloy through controlled annealing. Full article

23 pages, 4690 KB

Open AccessArticle

Predicting the Ti-Al Binary Phase Diagram with an Artificial Neural Network Potential

by Micah Nichols, Mashroor S. Nitol, Saryu J. Fensin, Christopher D. Barrett and Doyl E. Dickel

Metals 2026, 16(2), 140; https://doi.org/10.3390/met16020140 (registering DOI) - 24 Jan 2026

Abstract

The microstructure of the Ti-Al binary system is an area of great interest, as it affects material properties and plasticity. Phase transformations induce microstructural changes; therefore, accurately modeling the phase transformations of the Ti-Al system is necessary to describe plasticity. Interatomic potentials can [...] Read more.

The microstructure of the Ti-Al binary system is an area of great interest, as it affects material properties and plasticity. Phase transformations induce microstructural changes; therefore, accurately modeling the phase transformations of the Ti-Al system is necessary to describe plasticity. Interatomic potentials can be a powerful tool to model how materials behave; however, existing potentials lack accuracy in certain aspects. While classical potentials like the Modified Embedded Atom Method (MEAM) perform adequately for modeling a dilute Al solute within Ti’s

α

phase, they struggle with accurately predicting plasticity. In particular, they struggle with stacking fault energies in intermetallics and to some extent elastic properties. This hinders their effectiveness in investigating the plastic behavior of formed intermetallics in Ti-Al alloys. Classical potentials also fail to predict the

α

-to-

β

phase boundary. Existing machine learning (ML) potentials reproduce the properties of formed intermetallics with density functional theory (DFT) but do not accurately capture the

α

-to-

β

or

α

-to-D0₁₉ phase boundaries. This work uses a rapid artificial neural network (RANN) framework to produce a neural network potential for the Ti-Al binary system. This potential is capable of reproducing the Ti-Al binary phase diagram up to 30% Al concentration. The present interatomic potential ensures stability and allows results near the accuracy of DFT. Using Monte Carlo simulations, the RANN potential accurately predicts the

α

-to-

β

and

α

-to-D0₁₉ phase transitions. The current potential also exhibits accurate elastic constants and stacking fault energies for the L1₀ and D0₁₉ phases. Full article

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20 pages, 1939 KB

Open AccessArticle

Fiber-Diode Hybrid Laser Welding of IGBT Copper Terminals

by Miaosen Yang, Qiqi Lv, Shengxiang Liu, Qian Fu, Xiangkuan Wu, Yue Kang, Xiaolan Xing, Zhihao Deng, Fuxin Yao and Simeng Chen

Metals 2026, 16(2), 139; https://doi.org/10.3390/met16020139 - 23 Jan 2026

Abstract

The traditional ultrasonic bonding technique for IGBT T2 copper terminals often causes physical damage to ceramic substrates, severely compromising the reliability of power modules. Meanwhile, T2 copper laser welding faces inherent challenges including low laser absorption efficiency and unstable molten pool dynamics. To [...] Read more.

The traditional ultrasonic bonding technique for IGBT T2 copper terminals often causes physical damage to ceramic substrates, severely compromising the reliability of power modules. Meanwhile, T2 copper laser welding faces inherent challenges including low laser absorption efficiency and unstable molten pool dynamics. To address these issues, this study targets the high-quality connection of IGBT T2 copper terminals and proposes a welding solution integrating a Fiber-Diode Hybrid Laser system with galvo-scanning technology. Comparative experiments between galvo-scanning and traditional oscillation methods CNC scanning were conducted under sinusoidal and circular trajectories to explore the regulation mechanism of welding quality. The results demonstrate that CNC scanning lacks precision in thermal input control, resulting in inconsistent welding quality. Galvo-scanning enables precise modulation of laser energy distribution and molten pool behavior, effectively reducing spatter and porosity defects. It also promotes the transition from columnar grains to equiaxed grains, significantly refining the weld microstructure. Under the sinusoidal trajectory with a welding speed of 20 mm/s, the Lap-shear strength of the galvo-scanned joint reaches 277 N/mm², outperforming all CNC-scanned joints. This research proposes a non-contact welding strategy targeted at eliminating the mechanical failure mechanism associated with conventional ultrasonic bonding of ceramic substrates. It establishes the superiority of galvo-scanning for precision welding of high-reflectivity materials and lays a foundation for its potential application in new energy vehicle power modules and microelectronic packaging. Full article

(This article belongs to the Special Issue Advanced Laser Welding and Joining of Metallic Materials)

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15 pages, 1196 KB

Open AccessArticle

Machine Learning-Assisted Fabrication for K417G Alloy Prepared by Wide-Gap Brazing: Process Parameters, Microstructure, and Properties

by Zhun Cheng, Min Wu, Bo Wei, Xinhua Wang, Xiaoqiang Li and Jiafeng Fan

Metals 2026, 16(2), 138; https://doi.org/10.3390/met16020138 - 23 Jan 2026

Abstract

This study employed data-driven machine learning models to analyze the effects of filler material composition and other process parameters on mechanical properties during the crack repair of nickel-based superalloys such as K417G using wide-gap brazing technology. First, a linear regression model was used [...] Read more.

This study employed data-driven machine learning models to analyze the effects of filler material composition and other process parameters on mechanical properties during the crack repair of nickel-based superalloys such as K417G using wide-gap brazing technology. First, a linear regression model was used to analyze the influence of independent variables (filler material composition and other process parameters) on the dependent variables (tensile strength and elongation). The regression results indicated that temperature and filler composition significantly affected tensile strength and elongation. Subsequently, a TabNet machine learning model was applied to simulate the relationship between parameters such as composition and mechanical properties. The experimental results showed that when four parameters, namely, the filler composition, temperature, holding time, and pressure, were used as input features, the deviation between the actual and predicted values of elongation was minimal, with a value of only 1.5650. Full article

(This article belongs to the Special Issue Advanced Metal Welding and Joining Technologies—3rd Edition)

21 pages, 6679 KB

Open AccessArticle

Influence of Lignosulfonate on the Hydrothermal Interaction Between Pyrite and Cu(II) Ions in Sulfuric Acid Media

by Kirill Karimov, Maksim Tretiak, Uliana Sharipova, Tatiana Lugovitskaya, Oleg Dizer and Denis Rogozhnikov

Metals 2026, 16(2), 137; https://doi.org/10.3390/met16020137 - 23 Jan 2026

Abstract

Hydrometallurgical pretreatment of pyrite-bearing concentrates and tailings by hydrothermal interaction with Cu(II) solutions is a promising route for chemical beneficiation and mitigation of acid mine drainage but is limited by passivation caused by elemental sulfur and secondary copper sulfides. Here, the effect of [...] Read more.

Hydrometallurgical pretreatment of pyrite-bearing concentrates and tailings by hydrothermal interaction with Cu(II) solutions is a promising route for chemical beneficiation and mitigation of acid mine drainage but is limited by passivation caused by elemental sulfur and secondary copper sulfides. Here, the effect of sodium lignosulfonate (SLS) on the hydrothermal reaction between natural pyrite and CuSO₄ in H₂SO₄ media at 180–220 °C was studied at [H₂SO₄]₀ = 10–30 g/dm³, [Cu]₀ = 6–24 g/dm³, and [SLS]₀ = 0–1.0 g/dm³. Process efficiency was evaluated by Fe extraction into solution and Cu precipitation on the solid phase, and products were characterized by XRD and SEM/EDS. SLS markedly intensified pyrite conversion: at 200 °C and 120 min, Fe extraction increased from 14 to 26% and Cu precipitation from 5 to 23%, while at 220 °C, Fe extraction reached 33.4% and Cu precipitation 26.8%. XRD confirmed the sequential transformation CuS → Cu_1.8S. SEM/EDS showed that SLS converts localized nucleation of Cu_xS on defect sites into the formation of a fine, loosely packed, and well-dispersed copper sulfide phase. The results demonstrate that lignosulfonate surfactants efficiently suppress passivation and enhance mass transfer, providing a basis for intensifying hydrothermal pretreatment of pyrite-bearing industrial materials. Full article

(This article belongs to the Special Issue Recent Progress in Metal Extraction and Recycling)

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22 pages, 63134 KB

Open AccessArticle

The Effects of Laser Shock Peening with and Without Protective Coating on the Corrosion Resistance of Sensitized 304L Stainless Steel

by Richard Chiang and Vijay K. Vasudevan

Metals 2026, 16(2), 136; https://doi.org/10.3390/met16020136 - 23 Jan 2026

Abstract

This study examined the effects of laser shock peening (LSP) and LSP without protective coating (LSPwC) on the microstructure and corrosion behavior of 304L stainless steel using cyclic polarization testing. LSP enhanced corrosion resistance under mild sensitization (650 °C; 5 h) by inducing [...] Read more.

This study examined the effects of laser shock peening (LSP) and LSP without protective coating (LSPwC) on the microstructure and corrosion behavior of 304L stainless steel using cyclic polarization testing. LSP enhanced corrosion resistance under mild sensitization (650 °C; 5 h) by inducing compressive stress and increasing dislocation density, stabilizing the passive film. Limited improvement was observed under severe sensitization (650 °C; 24 h). Deformation-induced martensite detected by XRD was attributed to mechanical polishing, not LSP. In contrast, LSPwC reduced corrosion resistance across all conditions due to Fe-rich surface oxides that impaired passivation. Full article

(This article belongs to the Special Issue Laser Shock Peening: From Fundamentals to Applications)

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15 pages, 3899 KB

Open AccessArticle

Thermodynamic and Experimental Investigation of Lead Removal from Pb-Sb Alloy Using an H₃PO₄-(NaPO₃)₆ Composite Agent

by Jiahui Tan, Xiangfeng Kong, Jia Yang, Dachun Liu and Hongwei Yang

Metals 2026, 16(2), 135; https://doi.org/10.3390/met16020135 - 23 Jan 2026

Abstract

This study presents a rapid and efficient laboratory-scale process for removing lead from Pb–Sb alloy melts using a composite H₃PO₄–(NaPO₃)₆ flux. Thermodynamic analysis was combined with experimental investigation to elucidate the influence of key parameters on [...] Read more.

This study presents a rapid and efficient laboratory-scale process for removing lead from Pb–Sb alloy melts using a composite H₃PO₄–(NaPO₃)₆ flux. Thermodynamic analysis was combined with experimental investigation to elucidate the influence of key parameters on lead removal behavior. The Wilson equation was employed to describe the non-ideal behavior of the Pb–Sb system, enabling estimation of equilibrium lead contents and providing theoretical support for interpreting experimental trends. Under the investigated conditions (1073 K, H₃PO₄/(NaPO₃)₆ mass ratio of 2:1, and a holding time of 10 min), the Pb mass fraction was reduced from 10.0 wt.% to 0.018 wt.%, corresponding to a lead removal efficiency of 99.86%. Compared with the traditional refining processes, this method shortens the processing time and avoids the use of volatile gas reagents, demonstrating its potential for lead–antimony separation. The results provide thermodynamic and experimental insight into phosphate-based refining of crude antimony. Full article

(This article belongs to the Section Extractive Metallurgy)

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16 pages, 24835 KB

Open AccessArticle

Linking Microstructural Evolution to Magnetic Response for Damage Assessment in In-Service 321 Stainless Steel

by Shengzhong Hu, Yunrong Lyu, Weiming Li and Fuping Guo

Metals 2026, 16(2), 134; https://doi.org/10.3390/met16020134 - 23 Jan 2026

Abstract

This study evaluated the damage behavior of 321 austenitic stainless steel under tensile loading by measuring its magnetic properties. The results indicate that, at room temperature, the magnetic properties of 321 stainless steel respond distinctly to mechanical loading. Changes under external stress are [...] Read more.

This study evaluated the damage behavior of 321 austenitic stainless steel under tensile loading by measuring its magnetic properties. The results indicate that, at room temperature, the magnetic properties of 321 stainless steel respond distinctly to mechanical loading. Changes under external stress are primarily attributed to the phase transformation from austenite to martensite. Both coercive force and magnetic Barkhausen noise effectively characterize this material’s deformation and phase transformation processes: the coercive force dynamics curve exhibits an initial rise, followed by a decline with a decrease during the specimen’s necking stage. Magnetic Barkhausen noise is highly sensitive to stress changes, especially during the elastic stage. In situ measurements show that, at a stress of 300 MPa, the magnetic Barkhausen noise peak voltage signal reaches 0.060 V, which is a 100.0% increase compared to the original specimen (0.030 V). Therefore, when assessing the stress state and damage of stainless steel using coercive force and magnetic Barkhausen noise techniques, attention should be paid to the inflection characteristics of the coercive force dynamic curve and the inflection points in the peak values of the magnetic Barkhausen noise voltage signal. These features can be used to effectively monitor crack initiation and propagation in austenitic stainless steel. Full article

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23 pages, 4591 KB

Open AccessArticle

From Mining Residues to Potential Resources: A Cross-Disciplinary Strategy for Raw Materials Recovery and Supply

by Stefano Ubaldini, Alena Luptakova, Matteo Paciucci, Daniela Caschera, Roberta Grazia Toro, Isabel Nogues, Victor Pinon, Magdalena Balintova, Adriana Estokova, Miloslav Luptak, Eva Macingova, Rosamaria Salvatori and Daniela Guglietta

Metals 2026, 16(2), 133; https://doi.org/10.3390/met16020133 - 23 Jan 2026

Abstract

Digital and green energy transitions are driving an unprecedented demand for Strategic and Critical Raw Materials (S-CRMs), necessitating the identification of alternative sources such as secondary raw materials from exploration and mining residues. This study investigates an integrated, multi-scale approach to map and [...] Read more.

Digital and green energy transitions are driving an unprecedented demand for Strategic and Critical Raw Materials (S-CRMs), necessitating the identification of alternative sources such as secondary raw materials from exploration and mining residues. This study investigates an integrated, multi-scale approach to map and recover S-CRMs from an abandoned exploration stockpile in Zlatá Baňa, Slovak Republic. A key aspect of the methodology is comprehensive chemical and mineralogical characterization (XRF, PXRD, FTIR, LIBS, and SEM-EDS), which provided scientific validation for the diagnostic absorption features observed in laboratory reflectance spectra. These laboratory-acquired signatures were then used as endmembers to classify Sentinel-2 imagery via the Spectral Angle Mapper (SAM) algorithm. This integration enabled the identification of three distinct residue classes, with classA (jarosite-rich residues) emerging as the most reactive facies. Subsequent bioleaching experiments using Acidithiobacillus ferrooxidans demonstrated that microbial activity more than doubled Zn mobilization compared to abiotic controls. This cross-disciplinary strategy confirms that the synergy between advanced analytical characterization and remote sensing provides a robust, cost-effective pathway for the sustainable recovery of S-CRMs in regions affected by historical and mining activities. Full article

(This article belongs to the Special Issue Efficient Utilization of Metal Mineral Resources and Low-Carbon Metallurgy)

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19 pages, 17087 KB

Open AccessArticle

Microstructural and Wear Characterisation of Aluminium 7075-Based Metal Matrix Composites Reinforced with High-Entropy Alloy Particles and Manufactured via Friction Stir Processing

by Leire Garcia-Sesma, Javier Vivas, Iban Quintana and Egoitz Aldanondo

Metals 2026, 16(2), 132; https://doi.org/10.3390/met16020132 - 23 Jan 2026

Abstract

This study investigates the microstructural evolution and wear behaviour of aluminium 7075-based metal matrix composites (MMCs) reinforced with high-entropy alloy (HEA) particles and fabricated via friction stir processing (FSP). A detailed characterisation of the grain refinement in the 7075 matrix was conducted, revealing [...] Read more.

This study investigates the microstructural evolution and wear behaviour of aluminium 7075-based metal matrix composites (MMCs) reinforced with high-entropy alloy (HEA) particles and fabricated via friction stir processing (FSP). A detailed characterisation of the grain refinement in the 7075 matrix was conducted, revealing significant dynamic recrystallization and grain size reduction induced by the severe plastic deformation inherent to FSP. The interaction between the matrix and HEA particles was analysed, showing strong interfacial bonding, which was further influenced by post-processing heat treatments. These microstructural modifications were correlated with the wear performance of the composites, demonstrating enhanced resistance due to the synergistic effect of precipitates and particle reinforcement. The findings highlight the potential of FSP as a viable route for tailoring surface properties in advanced MMCs for demanding tribological applications. Full article

(This article belongs to the Special Issue Surface Treatments and Coating of Metallic Materials (2nd Edition))

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18 pages, 3938 KB

Open AccessArticle

Integrated Modeling and Multi-Criteria Analysis of the Turning Process of 42CrMo4 Steel Using RSM, SVR with OFAT, and MCDM Techniques

by Dejan Marinkovic, Kenan Muhamedagic, Simon Klančnik, Aleksandar Zivkovic, Derzija Begic-Hajdarevic and Mirza Pasic

Metals 2026, 16(2), 131; https://doi.org/10.3390/met16020131 (registering DOI) - 23 Jan 2026

Abstract

This paper analyzes different approaches for the mathematical modeling and optimization of process parameters in the hard turning process of 42CrMo4 steel using a hybrid approach combining response surface methodology (RSM), multi-criteria decision making (MCDM), and machine learning through, support vector regression (SVR) [...] Read more.

This paper analyzes different approaches for the mathematical modeling and optimization of process parameters in the hard turning process of 42CrMo4 steel using a hybrid approach combining response surface methodology (RSM), multi-criteria decision making (MCDM), and machine learning through, support vector regression (SVR) with one-factor-at-a-time (OFAT) sensitivity analysis. Controlled process parameters such as cutting speed, depth of cut, feed, and insert radius are applied to conduct the experiments based on a full factorial experimental design. RSM was used to develop models that describe the effect of controlled parameters on surface roughness and cutting forces. Special emphasis was placed on the analysis of standardized residuals to evaluate the predictive capabilities of the RSM-developed model on an unseen data set. For all four outputs considered, analysis of the standardized residuals shows that over 97% of the points lie within ±3 standard deviations. A multi-criteria optimization technique was applied to establish an optimal combination of input parameters. The SVR model had high performance for all outputs, with coefficient of determination values between 89.91% and 99.39%, except for surface roughness on the test set, with a value of 9.92%. While the SVR model achieved high predictive accuracy for cutting forces, its limited generalization capability for surface roughness highlights the higher complexity and stochastic nature of surface formation mechanisms in the turning process. OFAT analysis showed that feed rate and depth of cut have been shown to be the most important input variables for all analyzed outputs. Full article

(This article belongs to the Special Issue Smart Sensing and Artificial Intelligence in Metal Processing and Machining)

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19 pages, 5147 KB

Open AccessArticle

The Influence of Applying PVD Coatings on Adhesion Wear Resistance of Quenching and Tempering Steels

by Ivica Kladarić, Stjepan Golubić, Danko Ćorić and Andrijana Milinović

Metals 2026, 16(2), 130; https://doi.org/10.3390/met16020130 - 23 Jan 2026

Abstract

The article examines the effect of different types of two-layer nanostructured coatings (cVIc and nACVIc) deposited on three types of steel substrates, 45S20, C45E, and 42CrMo4, to determine the resistance to adhesive wear of the substrate/coating system. The samples underwent different heat treatments, [...] Read more.

The article examines the effect of different types of two-layer nanostructured coatings (cVIc and nACVIc) deposited on three types of steel substrates, 45S20, C45E, and 42CrMo4, to determine the resistance to adhesive wear of the substrate/coating system. The samples underwent different heat treatments, including normalising, quenching, and quenching and tempering, followed by PVD (physical vapour deposition) treatment at temperatures of 450 °C (cVIc) and 460 °C (nACVIc). The thickness of the cVIc layers for all three steels ranged from 0.9 to 3.4 μm, while the thickness of the nACVIc layers on all steels was slightly greater, ranging from 1.9 to 3.1 μm. Tribological tests were conducted using the pin-on-disc method, and the results were statistically analysed. Results indicate that steel grade, heat treatment, and PVD coating significantly affect adhesive wear resistance, with the type of PVD coating showing the strongest influence. For all three steels, quenched and uncoated samples exhibited the lowest adhesion wear index values. Normalised and quenched with or without tempering steels coated with cVIc layer exhibit higher resistance to adhesive wear due to better adhesion of the layer compared to the nACVIc coating. Full article

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14 pages, 4680 KB

Open AccessArticle

Performance Evaluation of Five-Axis CNC Milling via Spindle Current and Vibration Monitoring

by Beatriz Cardoso, José Ferreira, Tiago E. F. Silva, Pedro Sá Couto, Ana Reis and Abílio M. P. de Jesus

Metals 2026, 16(1), 129; https://doi.org/10.3390/met16010129 - 22 Jan 2026

Abstract

The digitalization of machining processes is increasingly recognized as essential for achieving higher productivity, reliability, and traceability. However, access to reliable in-process sensor data remains limited, particularly in multi-axis CNC machining, where dimensional accuracy and surface integrity strongly depend on stable and optimized [...] Read more.

The digitalization of machining processes is increasingly recognized as essential for achieving higher productivity, reliability, and traceability. However, access to reliable in-process sensor data remains limited, particularly in multi-axis CNC machining, where dimensional accuracy and surface integrity strongly depend on stable and optimized process conditions. This study investigates sensor-based monitoring as a practical approach for evaluating process performance in five-axis CNC milling. Electric current and vibration signals were acquired during three machining operations, under distinct cutting parameters, using current clamps and a plug-and-play MEMS accelerometer. The signals were processed using the root mean square method to assess the correlation between sensor data and machining conditions. Dimensional inspection of each workpiece was carried out to verify geometric conformity. The results show that spindle current measurements exhibit a strong linear correlation with material removal rate and cutting power, supporting their use as indicators of cutting forces and energy consumption. Vibration signals revealed pronounced dynamic behaviour for specific tool orientations, particularly in transverse to tool axis direction. The proposed methodology provides a simple and low-cost framework for integrating sensor-based monitoring into five-axis CNC milling, particularly relevant for semi-roughing operations, and offers a basis for future studies on process optimization and real-time condition monitoring. Full article

(This article belongs to the Special Issue Numerical and Experimental Advances in Metal Processing, 2nd Edition)

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