Search Results (733)

Weathering steel (WS) is widely used in bridge construction due to its high corrosion resistance, durability, and low maintenance requirements. This paper reviews the performance of WS bridges in Canadian climates, focusing on the formation of protective patina, influencing factors, and long-term maintenance strategies. The protective patina, composed of stable iron oxyhydroxides, develops over time under favorable wet–dry cycles but can be disrupted by environmental aggressors such as chlorides, sulfur dioxide, and prolonged moisture exposure. Key alloying elements like Cu, Cr, Ni, and Nb enhance corrosion resistance, while design considerations—such as drainage optimization and avoidance of crevices—are critical for performance. The study highlights the vulnerability of WS bridges to microenvironments, including de-icing salt exposure, coastal humidity, and debris accumulation. Regular inspections and maintenance, such as debris removal, drainage system upkeep, and targeted cleaning, are essential to mitigate corrosion risks. Climate change exacerbates challenges, with rising temperatures, altered precipitation patterns, and ocean acidification accelerating corrosion in coastal regions. Future research directions include optimizing WS compositions with advanced alloys (e.g., rare earth elements) and integrating climate-resilient design practices. This review highlights the need for a holistic approach combining material science, proactive maintenance, and adaptive design to ensure the longevity of WS bridges in evolving environmental conditions. Full article

Tribological processes in extreme environments pose serious material challenges, requiring coatings that resist both wear and corrosion. This review summarizes recent advances in protective coatings engineered for extreme environments such as high temperatures, chemically aggressive media, and high-pressure and abrasive domains, as well as cryogenic and space applications. A comprehensive overview of promising coating materials is provided, including ceramic-based coatings, metallic and alloy coatings, and polymer and composite systems, as well as nanostructured and multilayered architectures. These materials are deployed using advanced coating technologies such as thermal spraying (plasma spray, high-velocity oxygen fuel (HVOF), and cold spray), chemical and physical vapor deposition (CVD and PVD), electrochemical methods (electrodeposition), additive manufacturing, and in situ coating approaches. Key degradation mechanisms such as adhesive and abrasive wear, oxidation, hot corrosion, stress corrosion cracking, and tribocorrosion are examined with coating performance. The review also explores application-specific needs in aerospace, marine, energy, biomedical, and mining sectors operating in aggressive physiological environments. Emerging trends in the field are highlighted, including self-healing and smart coatings, environmentally friendly coating technologies, functionally graded and nanostructured coatings, and the integration of machine learning in coating design and optimization. Finally, the review addresses broader considerations such as scalability, cost-effectiveness, long-term durability, maintenance requirements, and environmental regulations. This comprehensive analysis aims to synthesize current knowledge while identifying future directions for innovation in protective coatings for extreme environments. Full article

Nowadays, a single detection method is insufficient for comprehensively and clearly identifying both surface defects and inner defects in titanium alloys. To address this limitation, this paper proposes a titanium alloy defect detection method based on optical–acoustic image fusion. A detection system was developed to achieve comprehensive and precise inspection of titanium alloys by integrating advanced deep learning-based optical testing technology, reliable C-scan ultrasonic detection technology, and information fusion techniques. Furthermore, the PC software can output interactive fusion results and generate decision-level detection reports. The experimental results demonstrate that the surface defect detection algorithm achieves an accuracy of 99.0%, with a surface defect size measurement resolution of 0.01 mm, an internal defect size measurement resolution of 1 mm, and a positional error within 2 mm. It was found that the proposed method provides a potential solution for the practical application of inspecting surface defects and inner defects in the materials. Full article

Considering the importance of the automotive industry, reducing the environmental impact of automotive component manufacturing is crucial. Additionally, lightening of the latter promotes a reduction in fuel consumption throughout the vehicle’s life cycle, limiting emissions. This study presents a comprehensive approach to optimizing and manufacturing a MacPherson steering knuckle using topology optimization (TO), additive manufacturing, and rapid investment casting (RIC). Static structural simulations confirmed the mechanical integrity of the optimized design, with stress and strain values remaining within the elastic limits of the SG A536 iron alloy. The TO process achieved a 30% reduction in mass, resulting in lower material use and production costs. Additive manufacturing of optimized geometry reduced resin consumption by 27% and printing time by 9%. RIC simulations validated efficient mold filling and solidification, with porosity confined to removable riser regions. Life cycle assessment (LCA) demonstrated a 27% reduction in manufacturing environmental impact and a 31% decrease throughout the component life cycle, largely due to vehicle lightweighting. The findings highlight the potential of integrated TO and advanced manufacturing techniques to produce structurally efficient and environmentally sustainable automotive components. This workflow offers promising implications for broader industrial applications that aim to balance mechanical performance with ecological responsibility. Full article

Climate concerns are driving the automotive industry to adopt advanced manufacturing technologies that aim to improve energy efficiency and reduce vehicle weight. In this context, lightweight structural materials such as aluminium alloys have gained significant attention due to their favorable strength-to-weight ratio. Laser welding plays a crucial role in assembling such materials, offering high flexibility and fast joining capabilities for thin aluminium sheets. However, welding these materials presents specific challenges, particularly in controlling heat input to minimize distortions and ensure consistent weld quality. As a result, numerical simulations based on the Finite Element Method (FEM) are essential for predicting weld-induced phenomena and optimizing process performance. This study investigates welding-induced distortions in laser butt welding of 1.5 mm-thick Al 6061 samples through FEM simulations performed in the SYSWELD 2024.0 environment. The methodology provided by the software is based on the Moving Heat Source (MHS) model, which simulates the physical movement of the heat source and typically requires extensive calibration through destructive metallographic testing. This transient approach enables the detailed prediction of thermal, metallurgical, and mechanical behavior, but it is computationally demanding. To improve efficiency, the Imposed Thermal Cycle (ITC) model is often used. In this technique, a thermal cycle, extracted from an MHS simulation or experimental data, is imposed on predefined subregions of the model, allowing only mechanical behavior to be simulated while reducing computation time. To avoid MHS-based calibration, this work proposes using thermal cycles acquired in-line during welding via infrared thermography as direct input for the ITC model. The method was validated experimentally and numerically, showing good agreement in the prediction of distortions and a significant reduction in workflow time. The distortion values from simulations differ from the real experiment by less than 0.3%. Our method exhibits a slight decrease in performance, resulting in an increase in estimation error of 0.03% compared to classic approaches, but more than 85% saving in computation time. The integration of real process data into the simulation enables a virtual representation of the process, supporting future developments toward Digital Twin applications. Full article

The field of metal additive manufacturing has witnessed significant growth in recent years, with technology offering the ability to produce complex geometries that are challenging to manufacture using the traditional methods. In situ monitoring and control of the manufacturing process are crucial for increasing the production capacity and improving the quality of manufactured parts. This article provides a comparative analysis of computational, indirect, and direct methods for in situ temperature monitoring during additive manufacturing of metal alloy components. Furthermore, it discusses the current status, recent improvements, and perspectives for in situ temperature measurements. The basic principles of thermal imaging, two-color pyrometry, and millimeter-wave radiometry are explored, highlighting their limitations for addressing challenges related to material emissivity and rapid changes in building material composition. Overcoming the challenges related to the inaccessibility of the chamber where the parts are formed, direct temperature measurements would allow for the integration of collected information into big data systems. Within the framework of Industry 4.0, this approach offers a viable alternative to the conventional metal shaping processes, improving the production capacity and part quality. This research aims to contribute to ongoing advancements in metal additive manufacturing and its potential to completely replace traditional metal casting practices in the Industry 4.0 era. Full article

The surface quality of biomedical implants, such as shoulder joint caps, plays a critical role in their performance, longevity, and biocompatibility. Most biomedical shoulder joints fail to reach their optimal functionality when finished through conventional techniques like grinding and lapping due to their inability to achieve nanometer-grade smoothness, which results in greater wear and friction along with potential failure. The advanced magnetorheological finishing (MRF) approach provides enhanced surface quality through specific dimensional control material removal. This research evaluates how MRF treatment affects the surface roughness performance and microhardness properties and wear resistance behavior of cobalt–chromium alloy shoulder joint caps which have biocompatible qualities. The study implements a magnetorheological finishing system built with an electromagnetic tool to achieve the surface roughness improvements from 0.35 µm to 0.03 µm. The microhardness measurements show that MRF applications lead to a rise from HV 510 to HV 560 which boosts the wear protection of samples. After MRF finishing, the coefficient of friction demonstrates a decrease from 0.12 to 0.06 which proves improved tribological properties of these implants. The results show that MRF technology delivers superior benefits for biomedical use as it extends implant life span and decreases medical complications leading to better patient health outcomes. The purposeful evaluation of finishing techniques and their effects on implant functionality demonstrates MRF is an advanced technology for upcoming orthopedic implants while yielding high precision and enhanced durability and functional output. Full article

High-entropy alloys (HEAs) represent a breakthrough class of materials characterized by a unique combination of properties derived from their multielement compositions. This review explores the current advancements in both electrochemical and electroless deposition techniques for synthesizing HEA thin films. This paper discusses the crucial plating conditions using aqueous or organic electrolytes and various current/potential modes that influence the formation, quality, and properties of these complex alloy coatings. Particular attention is given to their emerging applications in areas such as catalysis, protective coatings, microelectronics, and liquids’ separation. A comparison of electrochemical versus electroless methods reveals insights into the advantages and limitations of each technique for research and industrial use. This comprehensive review aims to guide further innovation in the development and application of HEA coatings. Full article

Background/Objectives: The increasing demand for aesthetics in dentistry has driven significant advancements in both materials and techniques. The primary cause of ceramic detachment in dental restorations is extensive mechanical stress, which often results in detachment and clinical complications. This study aims to improve the bond strength between NiCr-based metal frameworks and ceramic coatings by introducing biocompatible inorganic MeSiON thin films (Me = Cr or Zr) as interlayers. Methods: MeSiON coatings with a thickness of ~2 μm were deposited on NiCr alloy using cathodic arc evaporation. To tailor the stoichiometry, morphology, and mechanical properties of the coatings, the substrate bias voltage was varied: −50 V, −100 V, −150 V, −200 V. Structural and surface characterization was performed using SEM/EDS, XRD, profilometry, and contact angle analysis. The coating adhesion was evaluated by using standardized scratch testing, while the bond strength was evaluated using a three-point bending test. Results: The NiCr alloy exhibited a dendritic microstructure, and the ceramic layer consisted mainly of quartz, feldspar, kaolin, and ZrO₂. ZrSiON coatings showed superior roughness, elemental incorporation, and adhesion compared to Cr-based coatings, these properties being further improved by increasing the substrate bias. The highest bond strength was achieved with a ZrSiON coating deposited at −200 V, a result we attributed to increased surface roughness and mechanical interlocking at the ceramic-metal interface. Conclusions: CrSiON and ZrSiON interlayers enhanced ceramic-to-metal adhesion in NiCr-based dental restorations. The enhancement in bond strength is primarily ascribed to substrate bias-induced modifications in the coating’s stoichiometry, roughness, and adhesion. Full article

Grain boundary weakening in high-temperature environments significantly influences the fatigue crack growth mechanisms of nickel-based superalloys, introducing challenges in accurately predicting fatigue life. In this study, a dislocation-density-based crystal plasticity phase-field (CP–PF) model is developed to simulate the fatigue crack growth behavior of the GH4169 alloy under both room and elevated temperatures. Grain boundaries are explicitly modeled, enabling the competition between transgranular and intergranular cracking to be accurately captured. The grain boundary separation energy and surface energy, calculated via molecular dynamics simulations, are employed as failure criteria for grain boundary and intragranular material points, respectively. The simulation results reveal that under oxygen-free conditions, fatigue crack propagation at both room and high temperatures is governed by sustained shear slip, with crack advancement hindered by grains exhibiting low Schmid factors. When grain boundary oxidation is introduced, increasing oxidation levels progressively degrade grain boundary strength and reduce overall fatigue resistance. Specifically, at room temperature, oxidation shortens the duration of crack arrest near grain boundaries. At elevated service temperatures, intensified grain boundary degradation facilitates a transition in crack growth mode from transgranular to intergranular, thereby accelerating crack propagation and exacerbating fatigue damage. Full article

This study develops a comprehensive artificial neural network (ANN) model for predicting the mechanical properties of carbon–manganese cast steel, specifically, the yield strength (YS), tensile strength (TS), elongation (El), and reduction of area (RA), based on the chemical composition (16 alloying elements) and heat treatment parameters. The neural network model, employing a 20-44-44-4 architecture and trained on 400 samples from an industrial dataset of 500 samples, achieved 90% of test predictions within a 5% deviation from actual values, with mean prediction errors of 3.45% for YS and 4.9% for %EL. A user-friendly graphical interface was developed to make these predictive capabilities accessible, without requiring programming expertise. Sensitivity analyses revealed that increasing the copper content from 0.05% to 0.2% enhanced the yield strength from 320 to 360 MPa while reducing the ductility, whereas niobium functioned as an effective grain refiner, improving both the strength and ductility. The combined effects of carbon and manganese demonstrated complex synergistic behavior, with the yield strength varying between 280 and 460 MPa and the tensile strength ranging from 460 to 740 MPa across the composition space. Optimal strength–ductility balance was achieved at moderate compositions of 1.0–1.2 wt% Mn and 0.20–0.24 wt% C. The model provides an efficient alternative to costly experimental trials for optimizing C-Mn steels, with prediction errors consistently below 6% compared with 8–20% for traditional empirical methods. This approach establishes quantitative guidelines for designing complex multi-element alloys with targeted mechanical properties, representing a significant advancement in computational material engineering for industrial applications. Full article

In this paper, the impact of mechanical alloying (MA) and spark plasma sintering (SPS) on the phase evolution and mechanical properties development of CoCrFeNiTi high–entropy alloys (HEAs) was investigated. The microstructure and properties of the material were examined, using X-ray diffraction (XRD) for phase identification, scanning electron microscopy (SEM) for surface morphology observation, transmission electron microscopy (TEM) for microstructural analysis, and hardness testing to evaluate mechanical performance. The milled powder exhibited nanocrystalline solid solution microstructure with grain sizes below 48 nm, composed of 83% face–centered cubic (FCC) and 17% body–centered cubic (BCC) phases. Mechanically, the bulk CoCrFeNiTi alloy exhibited exceptional strength attributes, as evidenced by a Vickers hardness value reaching 675 Hv, along with a compressive strength of 1894 MPa and a yield stress of 1238 MPa. These findings suggested that the synergistic effects of mechanical alloying and SPS processing can precisely control the phase stability, microstructure refinement, and property optimization in CoCrFeNiTi HEA, with particular promise for advanced structural applications. Full article

Aluminum and its alloy magnetron sputtering targets, owing to their superior electrical/thermal conductivity and robust substrate adhesion, serve as critical materials in advanced electronics and information technologies. It is known that the microstructure of the target, including grain uniformity and crystallographic texture, directly affects the sputtering performance and the quality of the deposited thin film. Despite extensive research efforts, the review paper focused on the microstructure of aluminum target materials is still absent. In that context, the recent progress on the Al alloy target is reviewed, focusing on grain refinement and texture control strategies. The roles of alloying elements, such as Si, Cu, and rare-earth Sc and Nd, are described first. The two conventional manufacturing techniques of fabricating Al targets, including melting and powder metallurgy, are introduced. Then, studies on grain refinement by thermomechanical processing routes (hot/cold rolling, annealing and forging) are summarized. Lastly, texture engineering through deformation and heat treatment protocols (unidirectional/multidirectional rolling, deformation thickness, and composite deformation modes) is reviewed. By establishing the relationship between thermomechanical processing and microstructure, this review provides insights for designing high-performance aluminum targets tailored to next-generation advanced thin-film applications. Full article

The peening process plays a pivotal role in enhancing the properties of aluminium alloys across various industries, including aerospace, automotive, and construction. Among the critical factors influencing this process, the shot peening time is of paramount importance for studying material characteristics. In the present study, we undertook a comprehensive investigation into the mechanical properties, surface roughness, and damage evolution behaviour of 7075 aluminium alloy subjected to different shot peening durations. This investigation was conducted using a microhardness tester, laser confocal microscope, scanning electron microscope, and other advanced equipment, in conjunction with digital image correlation methods and temperature evolution analysis. Our findings demonstrate that the shot peening time has a profound impact on the mechanical properties of the 7075 alloy. Specifically, the microhardness, tensile strength, and surface roughness of the alloy increased with increasing shot peening time, whereas the elongation rate exhibited a non-monotonic trend, initially decreasing and then increasing. Utilising DIC and temperature evolution analysis, we analysed the influence of shot peening time on the damage evolution behaviour of the alloy and developed tensile damage evolution equations tailored to different shot peening durations. The damage evolution of the 7075 alloy under various shot peening times was observed to proceed through two distinct stages: smooth development and rapid damage. Notably, the damage evolution laws derived from both techniques exhibited good consistency and agreement. The present study serves as a theoretical foundation for exploring the surface peening and damage evolution of 7075 aluminium alloy, which holds significant implications for optimising peening parameters and predicting material life in engineering applications. Full article