Search Results (1,350)

To ensure the sustainability of alloy-based strategies, both compositional design and processing routes must be simplified. Metal additive manufacturing (AM), with its exceptionally rapid, non-equilibrium solidification, offers a unique platform to produce tailored microstructures in simple alloys that deliver superior mechanical properties. In this study, we employ laser powder bed fusion (LPBF) to fabricate 1080 plain carbon steel, a binary alloy comprising only iron and carbon. Deviating from conventional process optimization focusing primarily on density, we optimize LPBF parameters for mechanical performance. We systematically varied key parameters (laser power and scan speed) to produce batches of tensile specimens, which were then evaluated on a high-throughput mechanical testing platform (HTP). Using response surface methodology (RSM), we developed predictive models correlating these parameters with yield strength (YS) and elongation. The RSM models identified optimal and suboptimal parameter sets. Specimens printed under the predicted optimal conditions achieved YS of 1543.5 MPa and elongation of 7.58%, closely matching RSM predictions (1595.3 MPa and 8.32%) with deviations of −3.25% and −8.89% for YS and elongation, respectively, thus validating model accuracy. Comprehensive microstructural characterization, including metallographic analysis and fracture surface examination, revealed the microstructural origins of performance differences and the underlying strengthening mechanisms. This methodology enables rapid evaluation and optimization of LPBF parameters for 1080 carbon steel and can be generalized as an efficient framework for robust LPBF process development. Full article

Although cemented carbides have been manufactured by the powder metallurgy (P/M) technology for over a century now, systematic developmental efforts are still underway. In the present study, tool life improvements in metal grooving applications are the key objective. Four PVD-coated cemented carbides compositions, dedicated to groove steel, stainless steel, cast iron, and aluminium alloys, have been newly designed, along with their manufacturing conditions. Physical, mechanical and chemical characteristics—such as sintered density, modulus of elasticity, hardness, fracture toughness, WC grain size, and the chemical composition of the substrate material, as well as the chemical composition, microhardness, structure, and thickness of the coatings—have been studied. A series of grooving tests have also been conducted to assess whether modifications to the thus far marketed tool materials, tool geometries, and coatings can improve cutting performance. In order to compare the laboratory and application properties of the investigated materials with currently produced by reputable companies, commercial inserts have also been tested. The experimental results obtained indicate that the newly developed grooving inserts exhibit excellent microstructural characteristics, high hardness, fracture toughness, and wear resistance and that they show slightly longer tool life compared to the commercial ones. Full article

Accurate melt pool geometry prediction is essential for ensuring quality and reliability in Laser Powder Bed Fusion (L-PBF). However, small experimental datasets and limited physical interpretability often restrict the effectiveness of traditional machine learning (ML) models. This study proposes a hybrid framework that integrates an explicit thermal model with ML algorithms to improve prediction under sparse data conditions. The explicit model—calibrated for variable penetration depth and absorptivity—generates synthetic melt pool data, augmenting 36 experimental samples across conduction, transition, and keyhole regimes for 316 L stainless steel. Three ML methods—Multilayer Perceptron (MLP), Random Forest, and XGBoost—are trained using fivefold cross-validation. The hybrid approach significantly improves prediction accuracy, especially in unstable transition regions (D/W ≈ 0.5–1.2), where morphological fluctuations hinder experimental sampling. The best-performing model (MLP) achieves R² > 0.98, with notable reductions in MAE and RMSE. The results highlight the benefit of incorporating physically consistent, nonlinearly distributed synthetic data to enhance generalization and robustness. This physics-augmented learning strategy not only demonstrates scientific novelty by integrating mechanistic modeling into data-driven learning, but also provides a scalable solution for intelligent process optimization, in situ monitoring, and digital twin development in metal additive manufacturing. Full article

Magnetic gears (MGs) are attracting increasing attention in power transmission systems due to their contactless operation principles, low frictional losses, and high efficiency. However, the broad application potential of these technologies requires a comprehensive evaluation of engineering parameters, such as material selection, energy efficiency, and structural design. This review focuses solely on solid-core magnetic gear systems designed using laminated electrical steels, soft magnetic composites (SMCs), and high-saturation alloys. This review systematically examines the topological diversity, torque transmission principles, and the impact of various core materials, such as electrical steels, soft magnetic composites (SMCs), and cobalt-based alloys, on the performance of magnetic gear systems. Literature-based comparative analyses are structured around topological classifications, evaluation of material properties, and performance analyses based on losses. Additionally, the study highlights that aligning material properties with appropriate manufacturing methods, such as powder metallurgy, wire electrical discharge machining (EDM), and precision casting, is essential for the practical scalability of magnetic gear systems. The findings reveal that coaxial magnetic gears (CMGs) offer a favorable balance between high torque density and compactness, while soft magnetic composites provide significant advantages in loss reduction, particularly at high frequencies. Additionally, application trends in fields such as renewable energy, electric vehicles (EVs), aerospace, and robotics are highlighted. Full article

Laser powder bed fusion (LPBF) is an advanced additive manufacturing technology that is gaining increasing interest for biomedical implants because it can produce dense, patient-specific metallic components with controlled microstructures. This study investigated the LPBF fabrication of 316L stainless steel, which is widely used in orthopedic and dental implants, and examined the effects of laser power and scanning speed on the microstructure and mechanical properties relevant to biomedical applications. The study achieved 99.97% density and refined columnar and cellular austenitic grains, with optimized molten pool morphology. The optimal LPBF parameters, 190 W laser power and 700 mm/s, produced a tensile strength of 762.83 MPa and hardness of 253.07 HV_0.2, which exceeded the values of conventional cast 316L stainless steel. These results demonstrated the potential of optimized LPBF 316L stainless steel for functional biomedical applications that require high mechanical integrity and biocompatibility. Full article

To reduce the carbon footprint of the concrete industry and promote a circular economy, this study explores the reuse of waste materials such as glass powder (GP) and nitrile rubber (NR) fibres in concrete. However, the inclusion of these waste materials results in lower compressive strength compared to conventional concrete, limiting their application to non-structural elements. To overcome this limitation, this study adopts the concept of confined concrete by developing concrete-filled steel tube (CFST) stub columns. In total, twelve concrete mix variations were developed, with and without steel tube confinement. GP was utilised at replacement levels of 10–30% by weight of cement, while NR fibres were introduced at 0.5% and 1% by volume of concrete. The findings demonstrate that the incorporation of GP and NR fibres leads to a reduction in compressive strength, with a compounded effect observed when both materials are combined. Steel confinement within CFST columns effectively mitigated the strength reductions, restoring up to 17% of the lost capacity and significantly improving ductility and energy absorption capacity. All CFST columns exhibited consistent local outward buckling failure mode, irrespective of the concrete mix variations. A comparison with predictions from existing design codes and empirical models revealed discrepancies, underscoring the need for refined design approaches for CFST columns incorporating sustainable concrete infill. This study contributes valuable insights into the development of eco-friendly, high-performance structural systems, highlighting the potential of CFST technology in facilitating the adoption of waste materials in the construction sector. Full article

Due to the high potential of shot peening to improve the surface quality of additively manufactured components, in this work, the influence on surface morphology and, thus, the surface topography and selected properties of the surface and subsurface regions of additively manufactured parts is analysed. For this, cubic specimens made of stainless steel 316L and AlSi10Mg were manufactured via powder bed fusion laser beam metal (PBF-LB/M), and subsequently, their “as-built” surfaces were shot peened. Shot peening was conducted with stainless steel or ceramic beads using pressures of 3 and 5 bar. The resulting morphologies were analysed regarding topography, microstructure and mechanical properties (hardness and cyclic deformation behaviour) in the subsurface region and the residual stresses. The results demonstrate a strong plastic deformation due to shot peening, resulting in a decreased surface roughness as well as an increased hardness and compressive residual stresses near the surface. These effects were generally more pronounced after using higher peening pressure and/or ceramic beads. Note that two sets of PBF-LB/M parameters were used to produce the AlSi10Mg specimens. The investigation of these specimens reveals an interrelation between the parameters used in shot peening and PBF-LB/M on the resulting surface morphology. Full article

Laser beam powder bed fusion of metals (PBF-LB/M, or simply L-PBF) has emerged as one of the most competitive additive manufacturing technologies for producing complex metallic components with high precision, design freedom, and minimal material waste. Among the various categories of additive manufacturing processes, L-PBF stands out, paving the way for the execution of part designs with geometries previously considered unfeasible. Despite offering several advantages, parts with overhang features require the use of support structures to provide dimensional stability of the part. Support structures achieve this by resisting residual stresses generated during processing and assisting heat dissipation. Although the scientific community acknowledges the role of support structures in the success of L-PBF manufacturing, they have remained relatively underexplored in the literature. In this context, the present work investigated the impact of laser power and scanning speed on the dimensioning, integrity and tensile strength of single-walled block type support structures manufactured in AISI 316L stainless steel. The method proposed in this work is divided in two stages: processing parameter exploration, and mechanical characterization. The results indicated that support structures become more robust and resistant as laser power increases, and the opposite effect is observed with an increment in scanning speed. In addition, defects were detected at the interfaces between the bulk and support regions, which were crucial for the failure of the tensile test specimens. For a layer thickness corresponding to 0.060 mm, it was verified that the combination of laser power and scanning speed of 150 W and 500 mm/s resulted in the highest tensile resistance while respecting the dimensional deviation requirement. Full article

In the framework of hydrogen production and storage for clean energy generation, the resistance to hydrogen embrittlement of a newly developed austenitic stainless steel is presented. Gas-atomized metal powders prepared from secondary-sourced metals were employed to manufacture test specimens with Laser Powder Bed Fusion (LPBF) technology. After machining and exposure to a controlled, pressurized hydrogen atmosphere at high temperature, the effect of hydrogen charging on the mechanical performance under static and dynamic conditions was investigated. The stabilizing effect of the optimized chemical composition is reflected in the absence of degradation effects on Yield Stress (YS), Ultimate Tensile Stress (UTS), and fatigue life observed for specimens exposed to hydrogen. Moreover, despite a moderate reduction in the elongation at fracture observed by increasing the hydrogen charging time, ductility loss calculated as Relative Reduction of Area (RRA) remains substantially unaffected by the duration of exposure to hydrogen and demonstrates that the austenitic steel is capable of resisting hydrogen embrittlement (HE). Full article

This study explored the potential of reusing eggshell powders as a renewable activating agent for producing porous carbon materials from coffee husk. Carbonization and activation experiments were conducted by heating the samples at a rate of 10 °C/min up to 850 °C under a nitrogen atmosphere. A custom-designed double steel-mesh sample holder was used to hold approximately 2.0 g coffee husk on the top, with varying masses of eggshell at the bottom to achieve eggshells to coffee husk mass ratios of 2:1, 4:1, 6:1 and 8:1. The results demonstrated that CO₂ released from the thermal decomposition of the eggshell powder significantly enhanced pore development at 850 °C. Compared to the pore properties of carbon material produced without eggshell (e.g., BET surface area of 321 m²/g), the activated carbon samples exhibited substantially improved pore properties (e.g., BET surface area in the range of 592 to 715 m²/g). Furthermore, the pore characteristics improved consistently with increasing eggshell content. Observations by scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS) and Fourier-transform infrared spectroscopy (FTIR) confirmed the structural and chemical transformations of the resulting carbon materials. Under optimal carbonization-activation conditions, the resulting carbon materials derived from coffee husk exhibited microporous structures and slit-shaped pores, as indicated by the Type I isotherms and H4 hysteresis loops. Full article

Additive manufacturing (AM), particularly laser powder bed fusion (L-PBF), provides unmatched design flexibility for creating intricate steel structures with minimal post-processing. However, adopting L-PBF for high-performance applications is difficult due to the challenge of predicting microstructure evolution. This is because the process is sensitive to many parameters and has a complex thermal history. Thin-walled geometries present an added challenge because their dimensions often approach the scale of individual grains. Thus, microstructure becomes a critical factor in the overall integrity of the component. This study focuses on applying cellular automata (CA) modeling to establish robust and efficient process–structure relationships in L-PBF of 316L stainless steel. The CA framework simulates solidification-driven grain evolution and texture development across various processing conditions. Model predictions are evaluated against experimental electron backscatter diffraction (EBSD) data, with additional quantitative comparisons based on texture and morphology metrics. The results demonstrate that CA simulations calibrated with relevant process parameters can effectively reproduce key microstructural features, including grain size distributions, aspect ratios, and texture components, observed in thin-walled L-PBF structures. This work highlights the strengths and limitations of CA-based modeling and supports its role in reliably designing and optimizing complex L-PBF components. Full article

The Scalable and Expeditious Additive Manufacturing (SEAM) process is an advanced additive manufacturing (AM) technique that relies on the optimization of metal powder suspensions to achieve high-quality 3D-printed components. This study explores the critical role of dispersants in enhancing the performance of stainless steel (SS) 420 metal powder suspensions for the SEAM process by improving powder loading, recyclability, flowability, and consequent final part density. The addition of dispersant allows for increased powder contents while preserving stable rheological properties, thereby enabling higher powder loading without compromising the rheological characteristics required in the SEAM process. Previously, our team implemented a two-step printing strategy to address the segregation issues during printing. Nonetheless, the semi-cured layer was not recyclable after printing, resulting in a significant amount of waste in the SEAM process. This, in turn, leads to a considerable increase in material costs. On the other hand, the addition of a dispersant has been shown to enhance suspension stability, enabling multiple cycles of reuse. This novel approach has been demonstrated to reduce material waste and lower production costs. The enhanced flowability guarantees uniform suspension spreading, resulting in defect-free layer deposition and superior process control. Moreover, the dispersant’s ability to impede particle agglomeration and promote powder loading contributes to the attainment of a 99.33% relative density in the final sintered SS420 parts, thereby markedly enhancing their mechanical integrity. These findings demonstrate the pivotal role of dispersants in refining the SEAM process, enabling the production of high-density, cost-effective metal components with superior material utilization and process efficiency. Full article

Plow loosening machines are essential agricultural machinery in the agricultural production process. Improving the surface strengthening process and extending the working life of the plow teeth of the plow loosening machine are of great significance. In this paper, the preparation of Stellite6/Cu composite coating on the surface of 316L steel substrate intended for strengthening the plow teeth of a plow loosening machine using laser cladding technology was studied. The influence of different laser process parameters on the microstructure and properties of Stellite6/Cu composite coating was investigated. The composite coating powder was composed of Stellite6 powder with a different weight percent of copper. Microstructural analysis, phase composition, elemental distribution, microhardness, wear resistance, and corrosion resistance of the composite coatings on the plow teeth were analyzed using scanning electron microscopy (SEM), X-ray diffraction (XRD), microhardness testing, energy dispersive spectroscopy (EDS), friction and wear testing, and electrochemical workstation measurements. The results showed that (1) When the laser power was 1000 W, the average hardness of the prepared Stellite6/Cu composite layer achieved the highest hardness, approximately 1.36 times higher than the average hardness of the substrate, and the composite coating prepared exhibited the best wear resistance; (2) When the scanning speed was 800 mm/min, the composite coating exhibited the lowest average friction coefficient and the optimal corrosion resistance in a 3.5% wt.% NaCl solution with a self-corrosion current density of −7.55 µA/cm²; (3) When the copper content was 1 wt.%, the composite coating achieved the highest average hardness with 515.2 HV, the lowest average friction coefficient with 0.424, and the best corrosion resistance with a current density of −8.878 µA/cm². Full article

In railways, problems in braking and traction can be caused by so-called low-adhesion conditions. Adhesion is increased by sanding, where sand grains are blasted towards the wheel–rail contact. Despite the successful use of sanding in practice and extensive experimental studies, the physical mechanisms of adhesion increase are poorly understood. This study combines experimental work with a DEM model to aim at a deeper understanding of adhesion increase during sanding. The experimentally observed processes during sanding involve repeated grain breakage, varying sand fragment spread, formation of clusters of crushed sand powders, plastic deformation of the steel surfaces due to the high load applied and shearing of the compressed sand fragments. The developed DEM model includes all these processes. Two types of rail sand are analysed, which differ in adhesion increase in High-Pressure Torsion tests under wet contact conditions. This study shows that higher adhesion is achieved when a larger proportion of the normal load is transferred through sand–steel contacts. This is strongly influenced by the coefficient of friction between sand and steel. Adhesion is higher for larger sand grains, higher sand fragment spread, and higher steel hardness, resulting in less indentation, all leading to larger areas covered by sand. Full article

This study investigated the effect of adding superhard ReB₂ to atmospheric plasma sprayed (APS) coatings based on 60 wt% Al₂O₃ and 40 wt% ZrO₂. The amorphous phases commonly present in such coatings are known to impair their performance. ReB₂ was introduced as a crystallization nucleus due to its high melting point. ReB₂ decomposes in the presence of moisture and oxygen into H₃BO₃, ReO₃, HBO₂, and HReO₄. ReB₂ was encapsulated with Al₂O₃ via metallothermic synthesis to improve moisture stability, yielding a powder with d₉₀ = 15.1 μm. After milling, it was added at 20 wt% to the Al₂O₃-ZrO₂ feedstock. Agglomeration parameters were optimized, and coatings were deposited under varying APS conditions onto 316L steel substrates with a NiAl bond coat. In the coating with the highest ReB₂ content, the identified phases included ReB₂ (2.6 wt%), Re (0.8 wt%), α-Al₂O₃ (30.9 wt%), η-Al₂O₃ (32.4 wt%), and monoclinic and tetragonal ZrO₂. The nanohardness of the coating, measured using a Vickers indenter at 96 mN and calculated via the Oliver–Pharr method, was 9.2 ± 1.0 GPa. High abrasion resistance was obtained for the coating with a higher content of η-Al₂O₃ (48.7 wt%). The coefficient of friction, determined using a ball-on-disc test with a corundum ball, was 0.798 ± 0.03. After 15 months, the formation of (H₃O)(ReO₄) was observed, suggesting initial moisture-induced changes. The results confirm that Al₂O₃-encapsulated ReB₂ can enhance phase stability and crystallinity in APS coatings. Full article