Search Results (449)

Incremental sheet forming technology is finding increasing application in the production of components in many industries. This article presents the analysis of the formability of 0.68-mm-thick Zn-Cu-Ti alloy sheets during the single-point incremental forming (SPIF) of pyramid-shaped drawpieces. Basic mechanical properties of sheets were determined in a uniaxial tensile test. Formability tests were carried out using the Erichsen and Fukui methods. SPIF tests were carried out under the conditions of variable process parameters: tool diameter (12 and 20 mm), feed rate (500–3000 mm/min), tool rotational speed (250–3000 rpm), and step size (0.1–1.2 mm). The effect of SPIF process parameters on the value of basic mechanical parameters, maximum deviation of the measured wall profile from the ideal profile, limit-forming angle, and surface roughness of pyramid-shaped drawpieces was determined. It was found that increasing the step size resulted in a decrease in the value of the limit-forming angle. Both the step size and the tool rotational speed contribute to the increase of the maximum wall deviation. However, the use of higher feed rates and a larger tool diameter caused its reduction. Higher values of arithmetic mean surface roughness Ra were found for the outer surface of drawpieces. The use of a smaller step size with a larger tool diameter caused a reduction in the Ra value of the drawpiece wall. Based on the obtained results, it can be concluded that the Zn-Cu-Ti alloy demonstrates good suitability for SPIF when proper process parameters and sheet orientation are selected. An appropriate combination of tool diameter, feed rate, step size, and sample orientation can ensure the desired balance between dimensional accuracy, mechanical strength, and surface quality of the formed components. Full article

A hot compression simulation was conducted on the Al-7.62Zn-2.22Mg-0.90Cu-0.30Mn-0.09Er-0.13Zr alloy (7E97) within the temperature range of 300~460 °C and strain rate range of 0.001~10 s⁻¹ using a Gleeble-3500 hot simulator. A flow-stress constitutive equation and hot processing maps were established for the alloy, and the microstructural evolution of the alloy after hot deformation was investigated. It was found that the dominant dynamic softening mechanism of the alloy was dynamic recovery, accompanied by minor dynamic recrystallization. The optimal hot processing window for the alloy was determined to be in the ranges of 0.001~0.05 s⁻¹ and 350~410 °C. Full article

This study introduces a novel in situ pulsed current-assisted resistance spot welding method, which differs fundamentally from conventional post-weld heat treatments and is designed to enhance the mechanical performance of 7075-T651 aluminum alloy joints. Immediately after welding, a short-duration pulsed current is applied while the weld remains in a high excess-vacancy state, effectively accelerating precipitation reactions within the weld region. Transmission electron microscopy (TEM) observations reveal that pulsed current treatment promotes the formation of band-like solute clusters, indicating a significant acceleration of the early-stage precipitation process. Interestingly, the formation of quasicrystalline phases—rare in Al-Zn-Mg-Cu alloy systems—is incidentally observed at grain boundaries, exhibiting characteristic fivefold symmetry. Selected area electron diffraction (SAED) patterns further show that these quasicrystals undergo partial dissolution under the influence of the pulsed current, transforming into short-range ordered cluster-like structures. Lap shear tests demonstrate that joints treated with pulsed current exhibit significantly higher peak load and energy absorption compared to untreated specimens. Statistical analysis of weld size confirms that both groups possess comparable weld diameters under identical welding currents, suggesting that the observed mechanical improvements are primarily attributed to microstructural evolution rather than geometric factors. Full article

The corrosion behaviors of newly developed solder alloys with excellent mechanical properties, Sn-2.5 Ag-1.0 Bi-0.8 Cu-0.05 Ni (SABC25108N) and Sn-1.5 Bi-0.75 Cu-0.065 Ni (SBC15075N), are analyzed to supplement the corrosion behavior of the limited corrosion data in Pb- and Zn-free solder compositions. A potentiodynamic polarization test is conducted on these compositions in a NaCl electrolyte solution, the results of which are compared with those of conventional Sn-3.0 (wt%) Ag-0.5Cu and Sn-1.2Ag-0.5Cu-0.05Ni alloys. The results indicate that SBC15075N exhibits the lowest corrosion potential and highest corrosion current density, thus signifying the lowest corrosion resistance. By contrast, SABC25108N exhibits the lowest corrosion current density and highest corrosion resistance. Notably, SABC25108N shows a slower corrosion progression in the active state and exhibits the longest passive state. The difference in corrosion resistance is affected more significantly by the formation and distribution of the Ag₃Sn intermetallic compound phase owing to the high Ag content instead of by the presence of Bi or Ni. This uniform dispersion of Ag₃Sn IMC phases in the SABC25108N alloy effectively suppressed corrosion propagation along the grain boundaries and reduced the formation of corrosion products, such as Sn₃O(OH)₂Cl₂, thereby enhancing the overall corrosion resistance. These findings provide valuable insights into the optimal design of solder alloys and highlight the importance of incorporating sufficient Ag content into multicomponent compositions to improve corrosion resistance. Full article

Photothermal catalytic CO₂ conversion into chemicals that provide added value represents a promising strategy for sustainable energy utilization, yet the development of highly efficient, stable, and selective catalysts remains a significant challenge. Herein, we report a rationally designed p-n junction heterostructure, T-CZ-PBA (SC), synthesized via controlled pyrolysis of high crystalline Prussian blue analogues (PBA) precursor, which integrates CuCo alloy, ZnO, N-doped carbon (NC), and Zn^II-Co^IIIPBA into a synergistic architecture. This unique configuration offers dual functional advantages: (1) the abundant heterointerfaces provide highly active sites for enhanced CO₂ and H₂ adsorption/activation, and (2) the engineered energy band structure optimizes charge separation and transport efficiency. The optimized T-C₃Z₁-PBA (SC) achieves exceptional photothermal catalytic performance, demonstrating a CO₂ conversion rate of 126.0 mmol gcat⁻¹ h⁻¹ with 98.8% CO selectivity under 350 °C light irradiation, while maintaining robust stability over 50 h of continuous operation. In situ diffuse reflectance infrared Fourier transform spectroscopy (in situ DRIFTS) investigations have identified COOH* as a critical reaction intermediate and elucidated that photoexcitation accelerates charge carrier dynamics, thereby substantially promoting the conversion of key intermediates (CO₂* and CO*) and overall reaction kinetics. This research provides insights for engineering high-performance heterostructured catalysts by controlling interfacial and electronic structures. Full article

Experimental and theoretical design on thermal and structural properties of Cu-Zn-Al alloys are established. As such, from an experimental point of view, differential thermal analysis has been performed with the help of a DSC Netzsch STA 449 F1 Jupiter calorimeter with high levels of sensitivity, and the structural analysis has been accomplished through X-ray diffraction and SEM analysis. An unusual specific property for a metallic material has been discovered, which is known as “rubber-type behavior”, a characteristic determined by micro-structural changes. From the theoretical point of view, the thermal transfer in Cu-Zn-Al is presented by assimilating this alloy, both structurally and functionally, with a multifractal, situation in which the order–disorder transitions assimilated with thermal “dynamics” of Cu-Zn-Al, are mimed through transitions from non-multifractal to multifractal curves. In such a context, the thermal expansion velocity contains both the propagation speed of the phase transformation (be it a direct one: austenitic–martensitic transformation, or an indirect one: martensitic–austenitic transformation) and the thermal diffusion speed. Then, through self-modulations of the thermal field, the Cu-Zn-Al alloy will self-structure in channel-type or cellular-type thermal patterns, which can be linked to obtained experimental data. Consequently, since the thermal conductivity becomes a function of the observation scale, and heat transfer is modified to reflect the multifractal, non-differentiable paths in the material, it leads to anomalous diffusion and complex thermal behaviors. Full article

This study aimed to evaluate the impact of contact surface roughness on the performance characteristics of M12-type electrical contacts, with particular emphasis on current and thermal derating parameters. Three samples were prepared, all made from the same conductive material CuZn42, in accordance with identical geometric and technological specifications, differing in the surface roughness value: R_z = 2 μm, representing high surface finish quality, and R_z = 10 μm, representing lower quality. The results showed that the surface roughness of the contact significantly affects the thermal and electrical properties of the tested contacts. Surfaces with lower roughness (R_z = 2 μm) exhibited better electrical conductivity, lower contact resistance, and slower temperature rise as the current load increased. In contrast, contacts with higher roughness (R_z = 10 μm) showed a faster temperature rise and a reduction in the maximum allowable current at higher ambient temperatures. These results could be useful in the design of systems requiring reliability, particularly in high-power devices. Full article

Investment casting is a precision casting technology that can produce complex shapes from various materials, particularly difficult-to-cast and difficult-to-machine metallic alloys. Meanwhile, electrical discharge machining (EDM) is a well-known technique for producing ultra-precise mechanical parts, and electrode quality is crucial. Few studies have explored how rapid prototyping (RP) pattern generation and investment casting influence the final product’s shape, dimensions, and surface roughness. This study investigates EDM electrode fabrication using investment casting and RP-generated epoxy resin patterns. We examine the effects of electrode materials (CuZn5, CuZn30, and FeCr24) on surface roughness, alongside the impact of ceramic shell thickness and RP pattern shrinkage on electrode quality. The EDM electrodes have a shrinkage of 0.8–1.9% and a surface roughness of 3.20–6.35 μm, depending on the material selections. Additionally, the probability of shell cracking decreases with increasing shell thickness, achieving stability at 16.00 mm. This research also applies investment casting electrodes to process DC53 steel. The results indicate that the surface roughness of the workpiece after EDM machining with different electrode materials is in the range of 4.71 µm to 9.88 µm. The result expands the use of investment casting in electrode fabrication, enabling the production of high-precision electrodes with complex profiles and challenging materials, potentially reducing both time and cost. Full article

Cu–Zn alloys are widely used engineering materials with well-known industrial applications. However, studies on their electrical and thermal conductivities have primarily relied on experimental measurements, while theoretical investigations remain limited. In this work, eight crystal structure models were constructed to represent three phase configurations (α single phase, α + β′ dual phase, and β′ single phase) of Cu–Zn alloys with Zn concentrations ranging from 0 to 50 at.%. Based on the first-principles calculations combined with the Boltzmann transport equation, the electrical and thermal conductivities of these models were computed, and the electronic structure of the α-phase configurations was further analyzed. The results show that both electrical and thermal conductivities exhibit a non-monotonic trend with increasing Zn content, initially decreasing and then increasing. This trend is in strong agreement with available experimental data. Further analysis of the electronic structure reveals that, in the α-phase region, the density of states near the Fermi level is mainly contributed by Cu d-orbitals. As Zn content increases, the effective DOS near the Fermi level decreases, leading to reduced electron transport capability. For thermal conductivity, both the Wiedemann–Franz law and the first-principles calculations were employed, yielding results consistent with experimental trends. In summary, this study systematically investigates the variation of electrical and thermal conductivities of Cu–Zn binary alloys with Zn content and explores the underlying physical mechanisms from the perspective of electronic structure. The findings provide valuable theoretical support for understanding and optimizing the transport properties of complex alloy systems. Full article

The increasing restriction of lead in industrial alloys, particularly in copper–zinc-based materials such as CuZn40Pb2, necessitates the development of environmentally safer alternatives. ZnAl15Cu1Mg (ZEP1510), a zinc-based wrought alloy composed of 15% aluminum, 1% copper, 0.03% magnesium, with the remainder being zinc, has emerged as a promising candidate for lead-free applications due to its favorable forming characteristics and corrosion resistance. This study investigates the performance of ZEP1510 compared to conventional leaded copper alloys and galvanized steel. Corrosion behavior was evaluated using neutral salt spray testing, cyclic climate chamber exposure, and electrochemical potential analysis in chloride- and sulfate-containing environments. ZEP1510 exhibited corrosion resistance comparable to brass and significantly better performance than galvanized steel in neutral and humid atmospheres. Combined with its low processing temperature and high recyclability, ZEP1510 presents itself as a viable and sustainable alternative to brass with lead for applications in sanitary, automotive, and electrical engineering industries. Full article

In this paper, we present the analysis of functional alloy samples containing metals aluminum (Al), copper (Cu), lead (Pb), silicon (Si), tin (Sn), and zinc (Zn) using a Q-switched Nd laser operating at a wavelength of 532 nm with a pulse duration of 5 ns. Nine pelletized alloy samples were prepared, each containing varying chemical concentrations (wt.%) of Al, Cu, Pb, Si, Sn, and Zn—elements commonly used in electrotechnical and thermal functional materials. The laser beam is focused on the target surface, and the resulting emission spectrum is captured within the temperature interval of $9.0\times {10}^3$ to $1.1\times {10}^4$ K using a set of compact Avantes spectrometers. Each spectrometer is equipped with a linear charged-coupled device (CCD) array set at a 2 μs gate delay for spectrum recording. The quantitative analysis was performed using calibration-free laser-induced breakdown spectroscopy (CF-LIBS) under the assumptions of optically thin plasma and self-absorption-free conditions, as well as local thermodynamic equilibrium (LTE). The net normalized integrated intensities of the selected emission lines were utilized for the analysis. The intensities were normalized by dividing the net integrated intensity of each line by that of the aluminum emission line (Al II) at 281.62 nm. The results obtained using CF-LIBS were compared with those from the laser ablation time-of-flight mass spectrometer (LA-TOF-MS), showing good agreement between the two techniques. Furthermore, a random forest technique (RFT) was employed using LIBS spectral data for sample classification. The RFT technique achieves the highest accuracy of ~98.89% using out-of-bag (OOB) estimation for grouping, while a 10-fold cross-validation technique, implemented for comparison, yields a mean accuracy of ~99.12%. The integrated use of LIBS, LA-TOF-MS, and machine learning (e.g., RFT) enables fast, preparation-free analysis and classification of functional metallic materials, highlighting the synergy between quantitative techniques and data-driven methods. Full article

The metal-based/ceramic interface structure is a key research focus in science, and addressing the stability of the interface has significant scientific importance as well as economic value. In this project, the work of adhesion, heat of segregation, electronic structure, charge density, and density of states for doped-M (M = Ti, Mg, Cu, Zn, Si, Mn, or Al) Ni (111)/Al₂O₃ (0001) interface structures are studied using first-principle calculation methods. The calculation results demonstrate that doping Ti and Mg can increase the bonding strength of the Ni–Al₂O₃ interface by factors of 3.4 and 1.5, respectively. However, other dopants, such as Si, Mn, and Al, have a negative effect on the bonding of the Ni–Al₂O₃ interface. As a result, the alloying elements may be beneficial to the bonding of the Ni–Al₂O₃ interface, but they may also play an opposite role. Moreover, the Ti and Mg dopants segregate from the matrix and move to the middle position of the Ni–Al₂O₃ interface during relaxation, while other dopants exhibit a slight segregation and solid solution in the matrix. Most remarkably, the segregation behavior of Ti and Mg induced electron transfer to the middle of the interface, thereby increasing the charge density of the Ni–Al₂O₃ interface. For the optimal doped-Ti Ni–Al₂O₃ interface, bonds of Ti–O and Ti–Ni are found, which indicates that the dopant Ti generates stable compounds in the interface region, acting as a stabilizer for the interface. Consequently, selecting Ti as an additive in the fabrication of metal-based ceramic Ni–Al₂O₃ composites will contribute to prolonging the service lifetime of the composite. Full article

Semi-solid processes of aluminium alloys, characterised by the coexistence of solid and liquid phases, offer advantages in terms of mechanical properties and fatigue resistance, thanks to the more globular microstructure. Thermodynamic models can be used to analyse the solidification behaviour and to predict the solidification window, ΔT. The CALPHAD method enables the calculation of the phases formed during solidification and the optimisation of alloy composition to meet specific industrial requirements. This study aims to assess how thermodynamic properties in both liquid and solid phases affect the ΔT. Initially, the influence of thermodynamic properties of pure components and interaction parameters was analysed in simplified regular binary systems. To compare these findings with real industrial systems, Al-based alloys were examined. Using available databases, the ΔT was estimated via the CALPHAD method adding alloying elements commonly found in secondary Al-alloys. Finally, the same minority alloying elements were added to Al-Si 8 and 11 wt.% alloys, and the corresponding ΔT were calculated. Cr, Fe, Mg, Mn, and Ti increase the ΔT, while Cu, Ni, and Zn decrease it. The obtained results may serve as a valuable tool for interpreting phenomenological observations and understanding the role of minority elements in the semi-solid processing of secondary Al-Si casting alloys. Full article

AZ31B magnesium alloy (wt.%: Al 2.94; Zn 0.87; Mn 0.57; Si 0.0112; Fe 0.0027; Cu 0.0008; Ni 0.0005; Mg remaining) has appropriate mechanical properties, good biodegradability and biocompatibility and can be used as a good orthopedic implant material. AZ31B magnesium alloy with a superhydrophobic surface exhibits excellent corrosion resistance and antibacterial adhesion performance, but superhydrophobic surfaces also hinder osteoblast adhesion and proliferation on the implants, resulting in unsatisfactory osteogenic properties. Therefore, it is necessary to achieve the wettability transition of the superhydrophobic surface at an early stage of implantation. In this work, superhydrophobic hydroxyapatite (HA)/calcium myristate (CaMS)/myristic acid (MA) composite coatings were prepared on AZ31B magnesium alloy using the hydrothermal and immersion methods. The composite coatings can spontaneously undergo the wettability transition from superhydrophobic to hydrophilic after complete exposure to simulated body fluid (SBF, a solution for modeling the composition and concentration of human plasma ions) for 9 h. The wettability transition mainly originated from the deposition and growth of the newly formed CaMS among the HA nanopillars during immersing, which deconstructed the micro-nano structure of the superhydrophobic coatings and directly exposed the HA to the water molecules, thereby significantly altering the wettability of the coatings. Benefiting from the superhydrophobic surface, the composite coating exhibited excellent antibacterial properties. After the wettability transition, the HA/CaMS/MA composite coating exhibited superior osteoblast adhesion performance. This work provides a strategy to enable a superhydrophobic coating to undergo spontaneous wettability transition in SBF, thereby endowing the coated magnesium alloy with a favorable osteogenic property. Full article

Stacking fault energy (SFE) is a critical property governing deformation mechanisms and influencing the mechanical behavior of materials. This work presents a unified framework for understanding and predicting SFE based solely on an electronic structure representation. By integrating density of states (DOS) spectral data, dimensionality reduction techniques, and machine learning models, it was found that the SFE behavior is indeed represented within the electronic structure and that this information can be used to accelerate the prediction of SFE. In the first part of this study, we established quantitative relationships between electronic structure and microstructural features, linking chemistry to mechanical properties. Using principal component analysis (PCA) and uniform manifold approximation and projection (UMAP), we identified key features from high-resolution vector representation of DOS data and explored their correlation with SFE. The second part of this work focuses on the predictive modeling of SFE, where a machine learning model trained on UMAP-reduced features achieved high accuracy (R² = 0.86, MAE = 15.46 mJ/m²). To bridge length scales, we extended this methodology to predict SFE in alloy systems, leveraging single-element data to inform multi-element alloy design. We illustrate this approach with Cu-Zn alloys, where the framework enabled rapid screening of compositional space while capturing complex electronic structure interactions. The proposed framework accelerates alloy design by reducing reliance on costly experiments and ab initio calculations. Full article