Alloys, Volume 5, Issue 1 (March 2026) – 8 articles

Cr-based composite coatings with superior wear resistance are in growing demand for high-performance applications in the automotive, aerospace, and general manufacturing sectors. In this study, an Al10Cu alloy produced via powder metallurgy was coated with a chromium/nanodiamond (Cr/ND) composite layer using an electrodeposition process to enhance its tribological performance. The coatings were characterized using scanning electron microscopy, energy-dispersive X-ray spectroscopy, and X-ray diffraction. The resulting Cr/ND layer exhibited a uniform thickness of 73.5–76.2 μm and markedly improved surface hardness (809.4 HV), representing a 15-fold increase over the uncoated alloy (53.6 HV). Pin-on-disk tribological testing under dry sliding conditions showed complete elimination of detectable mass loss (0.00 mg vs. 0.55 mg for uncoated) within the measurement system resolution, indicating excellent resistance to both abrasive and adhesive wear. XRD analysis revealed the formation of a hexagonal close-packed Cr₂H phase with incorporated nanodiamond particles. To capture and predict the temporal evolution of the friction coefficient, a customized dual-layer long short-term memory neural network—optimized with a look-back window of 3 timesteps and ReLU-activated dense layers—was implemented. The model achieved superior predictive performance on the coated system, with validation and test R² values of 0.9973 and 0.9965, respectively, demonstrating enhanced modeling accuracy for surface-engineered materials. These findings demonstrate a significant advancement in wear protection for aluminum alloys and introduce a robust data-driven approach for real-time friction prediction in engineered surfaces. Full article

Machine learning (ML) is becoming an established part of alloy research, offering new ways to link composition, processing routes, and microstructure with measured properties. In this work, recent studies using ML for predicting or optimizing alloy behavior are reviewed, covering mechanical, corrosion, phase-related, and physical properties. Unlike previous reviews organized by alloy system or modeling approach, this review is structured by target property (mechanical, corrosion, phase/structure, and physical), which helps identify the input features commonly used to model each property and highlights existing gaps in data and validation. For each study, the main property of interest, dataset features, model type, algorithm choice, use of hyperparameter tuning, and validation strategy were examined. Comparing these reports shows that ensemble models such as random forest and XGBoost, together with deep neural networks, usually perform better than linear approaches. At the same time, issues related to small datasets and inconsistent reporting remain major challenges. Attention is also drawn to new directions, particularly physics-based learning and multi-objective optimization, that are changing how ML is applied in materials design. Overall, this review summarizes current practices and outlines areas where closer integration of data-driven and experimental methods could accelerate the development of next-generation alloys. Full article

Damage is a phenomenon experienced when a material is subjected to external factors such as load and temperature. Damage is quantified through the damage value of a material, and its value typically ranges from 0 to 1, with 1 indicating complete damage. The damage value in this context primarily refers to the crack initiation condition, indicating failure. The damage value corresponding to this condition is referred to as critical damage. However, most materials tend to fail at a critical damage value of less than one. Researchers have developed different models to evaluate damage, and some of the prominent models are Lemaitre, Rice & Tracy, Gurson, and Bhattacharya & Ellingwood. This study uses the Bhattacharya & Ellingwood model to evaluate the damage value of 113 selected steel materials that play crucial roles in aerospace, automobile, and other industrial applications. This model uses monotonic properties of the material as the input and estimates the critical damage value (D_c). The study revealed that, for steel materials, the D_c value generally ranges from 0.1 to 0.7. This study highlights the variation in damage with plastic strain under monotonic loading, and this helps to quickly select a specific material when the damage criterion is crack initiation. Full article

In metal additive manufacturing, the molten pool directly influences the performance of the fabricated components. Therefore, a comprehensive understanding of the molten pool behavior is essential for improving the quality of the parts and mitigating the formation of defects. Selective arc melting (SAM) is a promising additive manufacturing method for fabricating metal matrix composites. However, the melting and solidification process of the powder layer under the arc heat source remains unrevealed. This study aims to elucidate the formation mechanisms of surface morphology during SAM processing and the influence of carbide addition on the melting and solidification behavior of Inconel 718 powder. In this study, thin-walled parts of Inconel 718 and TiC/Inconel 718 composite were fabricated and their microstructures were studied. The melting and solidification behavior of Inconel 718 and TiC/Inconel 718 composite during single-track single-layer deposition was investigated using high-speed photography. Focusing on the differences in the sidewall surface morphology of the Inconel 718 and TiC/Inconel 718 composite parts, the edge feature formation of the deposition track of both materials was studied. Furthermore, the formation mechanism of the differences in forming height at different positions of the deposition track was explored. The results indicate that the melted material in the molten pool of Inconel 718 mainly comes from the mass transport of the beads generated around the molten pool, while the liquid material in the molten pool of TiC/Inconel 718 composite mainly comes from the in situ powder melted under the arc center. During the melting process of Inconel 718 powder, beads at the edge of the heating area come into contact with the boundary of the molten pool and solidify in situ, forming protrusion features. The randomness in the bead size leads to different volumes of molten material at different positions within the same time, thereby causing variations in building height. Full article

This study provides the first complete and experimentally validated Yoshida–Uemori (Y–U) parameter set for AA6005C aluminum alloy, enabling accurate constitutive modeling for stamping simulations. A comprehensive set of mechanical tests was conducted, comprising uniaxial tensile tests along 0°, 45°, and 90° to the rolling direction, hydraulic bulge tests, Nakajima tests for the forming limit curve (FLC), and cyclic tension-compression experiments. Results showed moderate planar anisotropy with R-values of 0.49–0.90, equi-biaxial yield stress around 105 MPa, and plane-strain FLC₀ ≈ 0.25, typical for 6xxx-series alloys. The cyclic tests highlighted a strong Bauschinger effect and transient softening, which allowed precise calibration of the Yoshida-Uemori (Y-U) model. The resulting material parameters were validated using a U-bending case study, in which the predicted springback angle differed by only 2°, confirming the transferability of the calibrated model to forming conditions not used during parameter identification. The dataset generated in this work provides a robust foundation for finite element simulations of the AA6005C stamping processes and constitutes a practical reference for industrial implementation. Full article

High-entropy alloys (HEAs) present a vast compositional design space, characterized by four core effects—high configurational entropy, sluggish diffusion, severe lattice distortion, and the cocktail effect—which collectively underpin their exceptional potential for both structural and hydrogen storage applications. This mini-review synthesizes recent advances in the compositional design of HEAs with emphasis on structural materials and hydrogen storage. Firstly, it provides an overview of the definition of HEAs and the roles of principal alloying elements, then synthesizes solid solution formation rules based on representative descriptors—atomic size mismatch, electronegativity difference, valence electron concentration, mixing enthalpy, and mixing entropy—together with their applicability limits and common failure scenarios. A brief introduction is provided to the preparation methods of arc melting and powder metallurgy, which have a strong interaction with the composition. The design–structure–property links are then consolidated for structural materials (mechanical properties) and for hydrogen storage materials (hydrogen storage performance). Furthermore, the rules for the combined design of control systems for HEAs and the associated challenges were further discussed, and the future development prospects of HEAs in structural materials and hydrogen storage were also envisioned. Full article

Friction extrusion technology was first developed and patented in 1991 at The Welding Institute, but it remained largely unexplored for many years. Over the past decade, this technology has gained popularity due to its ability to recycle chips and produce composite materials. Typically, in friction extrusion, the applied force and extrusion direction are opposite; this configuration is commonly referred to as reverse extrusion. Additionally, the tool feed rate is often used as a control parameter. However, this approach introduces technological challenges and results in a heterogeneous product structure. This paper proposes a novel friction extrusion method in which the applied force and extrusion direction are co-directional, and no tool is used. Moreover, a constant load is maintained throughout the extrusion process. Experimental results demonstrate that the proposed scheme is feasible and enables wire extrusion without macroscopic defects. Although the current efficiency is low and the maximum sample size achieved is 45 mm, the cross-sectional microhardness of the samples remains stable. The material strength reached approximately 90% of that of the initial 2024 aluminum alloy. Full article

Intermetallic alloys based on A15-type compounds, including cubic Ti₃Sb, attract increasing interest due to their tunable electronic properties and potential for surface-related functional applications. Here, the interaction of nitrogen with Ti₃Sb is systematically investigated using spin-polarized density functional theory within the GGA-PBE approximation. Nitrogen adsorption was analyzed on the Ti₃Sb (111), (100), and (110) surfaces by considering top, bridge, and hollow sites at different surface coverages. Low nitrogen coverage was found to minimize lateral adsorbate interactions, allowing reliable evaluation of single-atom adsorption energies. Among the studied configurations, nitrogen adsorption at the hollow site of the Ti₃Sb (111) surface is energetically most favorable. In addition, partial substitution of Ti or Sb atoms by nitrogen in Ti₃Sb supercells was examined to assess its effect on bulk electronic properties. Nitrogen incorporation leads to pronounced modifications of the electronic band structure, density of states, and local magnetic moments, with a strong dependence on crystallographic direction. The calculated results reveal distinct electronic anisotropies originating from direction-dependent band dispersion and associated effective carrier masses. These findings clarify the role of nitrogen in tailoring both surface and bulk electronic characteristics of Ti₃Sb and provide a theoretical basis for the targeted design of A15-type intermetallic materials for sensing, catalytic, and energy-related applications. Full article