Friction and Wear of Hot-pressed Bearing Materials Containing Molybdenum Disulfide
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Abstract Layered MoO 3 represents a promising cathode for aqueous rechargeable Zn‐ion batteries, but the implementation of this material is limited due to the low conductivity and poor structural stability. A 30 m ZnCl 2 water‐in‐salt electrolyte (WISE) is introduced to a MoO 3 nanobelt cathode for the first time, significantly increasing the stability of MoO 3 cathodes compared to those in 3 m ZnSO 4 and 3 m ZnCl 2 . The Zn/MoO 3 cell in WISE unambiguously demonstrate significantly improved rate performance delivering 349, 253, and 222 mAh g −1 at 100, 500, and 1000 mA g −1 , denoting a 12× capacity increase of those achieved in 3 m electrolytes at 1000 mA g −1 . A capacity retention rate of 73% is achieved after (dis)charging at 100 mA g −1 for 100 cycles, and no obvious capacity fading is observed at higher current densities of 500 mA g −1 and 2 A g −1 . Specifically, the data suggest that the drastic fading in 3 m electrolytes can be attributed to the parasitic surface deposits on Zn originated from Mo dissolution and H 2 formation due to Zn corrosion and hydrogen evolution reaction, which are significantly suppressed in the WISE. The direct visualization of these side reactions is achieved for the first time in the Zn‐MoO 3 system, using an in situ optoelectrochemical measurement.
Light-emitting diode (LED) arrays fabricated on a polycrystalline metal substrate are demonstrated using a novel technique that enables the growth of epitaxial metal-organic chemical vapor deposition (MOCVD) GaN layers on non-single-crystal substrates. Epitaxial GaN is deposited directly on metal foil using an intermediate ion beam-assisted deposition (IBAD) aligned layer. For a single 170 μm-diameter LED on the metal foil, electroluminescence (EL) spectrum shows a peak wavelength of ≈452 nm and a full width at half maximum (FWHM) of ≈24 nm. The current–voltage (I –V ) characteristics show a turn-on voltage of 3.7 V, a series resistance of 10 Ω. LEDs on metal show a relative external quantum efficiency (EQE) that is roughly 3× lower than that of similar LEDs fabricated on a sapphire substrate. Finally, InGaN LEDs on large-area non-single-crystal substrates such as metal foils enable large-area manufacturing, reducing production cost, and opening the door for new applications in lighting and displays.
Due to the widespread use and familiarity of austenitic stainless steels in many industries these alloys are often the first materials used when adapting new processing techniques. The rapid cooling and solidification rates that occur during fusion based additive manufacturing processes like powder bed fusion cause a fundamental shift in the solidification behavior of the material. While the effects that Cr and Ni have on the microstructure have been fairly well documented across a range of solidification conditions, the impact of alloying elements like Mo are not as well understood at rapid solidification rates. For this study, four custom stainless steel alloy feedstocks were made with targeted modification of the Cr and Mo concentrations to maintain a constant Cr/Ni eq ratio of ~1.7. Two-piston splat quenching was used to produce rapidly solidified samples and the solidification mode, phase, and cell size were investigated. Solidification rates were estimated to be between 0.4 and 1.5m/s. A comparison of the microsegregation and partitioning behavior of Cr, Ni and Mo in ferrite solidified material was also performed for the different alloy compositions. Variations of the Mo concentration between each feedstock showed no measurable influence on the solidification/cooling rates, solidification morphology, or the partitioning of Mo. Furthermore, higher concentrations of Mo were found to significantly increase the amount of ferrite phase in the microstructure by suppressing the ferrite to austenite massive transformation.
Refractory metals are a class of high-melting-temperature materials suitable for use in extreme environment applications. Interestingly, during additive manufacturing many pure refractory metals exhibit a switch from (001) to (111) build direction fiber preference with increasing surface energy density. Here we exploit this solidification physics to fabricate material with “mesoscale composite” engineered structures consisting of features with contrasting (001) and (111) build direction microtextures. Separately, elevated temperature tensile testing of EBM fabricated material with a randomized distribution of mixed (001)/(111)-fiber grains is shown to exhibit excellent properties. These results are utilized to build a crystal plasticity model for evaluating the local inelastic response of the composite mesoscale structures. Analysis of printed microstructures and microstructure-scale simulations indicate that both macro-scale and localized material behavior may be tailored. This strategy can be potentially used to synthesize materials with optimized performance for high-temperature applications.
The interaction between solute atoms is critical to the thermodynamic behavior of Fe-Cr alloys, but the effects of non-dilute Al and Mo on the Fe-Cr phase stability and vacancy formation energy are not clearly understood. In this study, density functional theory, cluster expansion, and Monte Carlo simulation are used to predict the effects of ternary solute elements on the thermodynamic properties in multicomponent Fe-Cr alloys. The machine learning regression approach is applied to train and construct energy models that accurately describe the complex chemical interactions. The computational outcomes include the prediction of the partial ternary phase diagram, mixing enthalpy, and vacancy formation energy for different compositions. The phase boundary calculation predicts a pronounced change of Cr solubility in bcc Fe by the addition of Al and the rejection of Al atoms from a’ precipitates. The mixing enthalpy calculation shows that Mo may also reduce the Cr solubility in bcc Fe. Additionally, the simulations show that non-dilute Cr decreases the vacancy formation energy in bcc Fe, while adding Al results in a less significant effect. Finally, the results demonstrate important applications of using machine learning energy models to study model or commercial alloys with multicomponent solute species and point defects.
The high pressure and high strain rate dynamic strength of Mo is experimentally and computationally investigated in the 3–20 GPa stress, 50–600 C temperature, and 10 5 –10 6 /s strain rate regimes using a modified tamped Richtmyer-Meshkov instability (RMI) method. Modifications to the tamped RMI method include a method to determine loading states during strain, a new strength calibration function based on interface shape, and a robust uncertainty quantification method. These modifications improve fidelity of the tamped RMI method, allowing evaluation of the compensating effects of pressure hardening, strain rate hardening, strain hardening, and thermal softening. The new calibration function based on interface shape is not limited to sinusoidal corrugations and could be applied to additional interface shapes. Plate impact experiments are performed at Argonne National Laboratory’s Advanced Photon Source’s Dynamic Compression Sector operated by Washington State University (DCS), driving a planar shock front through a corrugated Mo-D 2 O or Mo-C 8 F 18 interface, forcing the corrugation to significantly deform. The extent of interfacial deformation, RMI growth, is experimentally observed using X-ray phase contrast imaging at the DCS. RMI jet lengths and jet shapes are extracted from the experimental radiographs, then used to calibrate numerical simulations performed with the Sandia National Laboratories (SNL) hydrocode CTH. Mo yield strength, Y, as a function of shock pressure, P, strain rate, $\dot{\varepsilon }$, accumulated strain, ϵ, relative volumetric compression, RD , and temperature, T , is determined for each impact experiment and presented. The calibrated Mo yield strength values range 1.2–1.8 GPa, with strength generally decreasing as the impact stress increases. This trend is likely caused by thermal softening or strain localization. The tabular yield strength versus loading condition data presented in this paper can be used to fit complex strength models.
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