JOM最新文献

The phase equilibria and division of the Ag₂S–GaS–Ga₂S₃–FeS₂–FeS–Ag₂S region (A) of the Ag–Fe–Ga–S system below 600 K were established by the modified EMF method. The electrochemical cells (ECs) of the following structure were assembled: (−)C||Ag||SE||R(Ag⁺)||PE||C(+), where C is the graphite; Ag is the left electrode; SE is the solid-state electrolyte; PE is the right electrode; R(Ag⁺) is the region of Ag⁺ diffusion in the PE. Initially assembled PEs are a nonequilibrium phase mixture of binary sulfides with the ratios of simple substances covering all composition space of (A). The catalyst for the reactions in R(Ag⁺) were Ag⁺ ions acting as small nucleation centers of equilibrium mixtures of compounds. The division of (A) was realized with the participation of the binary as well as more complex compounds AgGaS₂, Ag₉GaS₆, AgFeS₂, Ag₂FeS₂, Ag₂FeGa₂₀S₃₂, Ag₂FeGa₂S₅, and Ag₁₈Fe₉Ga₂S₂₁. The spatial position of the three- and four-phase regions relative to the Ag point was employed to establish the overall potential-forming reactions for synthesizing quaternary phases in the PEs of ECs. The temperature dependencies of the electromotive force of ECs were used to calculate the values of the standard thermodynamic functions of the quaternary compounds.

A dense bulk zirconia-toughened alumina (ZTA)-reinforced copper matrix composite with high particle content was fabricated by using a non-pressure infiltration method. The impact of different CuO content on the properties of ZTA/Cu matrix composites was investigated, and materials’ microstructure was analyzed. The results indicate that with a CuO content of 35 wt.%, the relative density, hardness, and electrical conductivity reached optimal values of 89.7%, 145.7 HV, and 16.2%IACS, respectively. Meanwhile, the friction coefficient and wear loss were 0.35 mm³ and 0.059 mm³, reducing it by 57.4% and 20.4% compared with pure Cu. Additionally, variations in composite morphology were observed based on CuO content, as the incorporation of CuO led to the segregation of oxygen at the interface, which plays a critical role in reducing interfacial energy between the particles and the matrix, thereby improved wettability. These findings provide valuable insight into the potential use of non-pressure infiltration methods in producing high-density ZTA-reinforced copper matrix composites, offering a pathway toward enhanced mechanical and tribological performance.

This paper studies fatigue application scenarios for high-performance gears and other mechanical components. It addresses the limitations of internal encapsulation detection and challenges of long-cycle tests. The paper proposes an intelligent prediction method for fatigue features, utilizing visual detection and accelerated degradation life. It integrates conventional test benches and environmental reliability accelerated test conditions, conducts in-depth research on fatigue life estimation algorithms, and explores the feasibility of employing deep learning algorithms and failure prediction models for fatigue life prediction. The paper also establishes an algorithmic system architecture that integrates and processes information from multiple systems and sensors, including gear fatigue performance driving and fatigue monitoring. This approach enables the rapid identification of early micro-motion fatigue characteristics, online autonomous detection, and intelligent failure estimation by integrating information from various systems and sensors. It can accurately predict fatigue degradation and provide a basis for adopting a rational anti-fatigue optimization design.

The properties of cutting fluids play a critical role in lubricating and cooling in machining operations. This study describes the optimization of the cutting parameters (depth of cut, feed, and cutting speed) in a conventional lathe machine to reduce surface roughness of aluminum alloy 6061 by using a novel biodegradable oil as cutting fluid. The optimal cutting parameters for surface roughness in turning are determined by applying the Taguchi technique L-27 orthogonal array, and corresponding surface roughness is measured. Analysis of variance (ANOVA) results explained that feed is the most influential factor on surface roughness with a contribution of 29.67%, followed by speed, 24.82%, and coolant ratio, 22.86%, while the depth of cut makes the lowest contribution of 16.83%. The surface roughness is found at its lower level at a blend ratio of MO/CO 80/20%, then linearly increases at MO/CO of 90/10%, and the highest surface roughness is obtained when 100/00% mineral-based cutting oil is used as a coolant. The decrease in surface roughness is ascribed to the superior lubricating and cooling capabilities of castor oil. The confirmatory experimental value of surface roughness at the optimal setting is 0.202 µm, confirming the parameters’ optimization at this configuration.