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Perovskite materials have a variety of crystal structures, and the properties of crystalline materials are greatly influenced by geometric information such as the space group, crystal system, and lattice constant. It used to be mostly obtained using calculations based on density functional theory (DFT) and experimental data from X-ray diffraction (XRD) curve fitting. These two techniques cannot be utilized to identify materials on a wide scale in businesses since they require expensive equipment and take a lot of time. Machine learning (ML), which is based on big data statistics and nonlinear modeling, has advanced significantly in recent years and is now capable of swiftly and reliably predicting the structures of materials with known chemical ratios based on a few key material-specific factors. A dataset encompassing 1647 perovskite compounds in seven crystal systems was obtained from the Materials Project database for this study, which used the ABX3 perovskite system as its research object. A descriptor called the bond-valence vector sum (BVVS) is presented to describe the intricate geometry of perovskites in addition to information on the usual chemical composition of the elements. Additionally, a model for the automatic identification of perovskite structures was built through a comparison of various ML techniques. It is possible to identify the space group and crystal system using just a small dataset of 10 feature descriptors. The highest accuracy is 0.955 and 0.974, and the highest correlation coefficient (R2) value of the lattice constant can reach 0.887, making this a quick and efficient method for determining the crystal structure.
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In this study, oxide dispersion-strengthened Cu alloy with a Y2O3 content of 1 wt.% was fabricated through citric acid sol-gel synthesis and spark plasma sintering (SPS). The citric acid sol-gel method provides molecular mixing for the preparation of precursor powders, which produces nanoscale and uniformly distributed Y2O3 particles in an ultrafine-grained Cu matrix. The effects of nanoscale Y2O3 particles on the microstructure, mechanical properties and thermal conductivity of the Cu-1wt.%Y2O3 alloy were investigated. The average grain size of the Cu-1wt.%Y2O3 alloy is 0.42 µm, while the average particle size of Y2O3 is 16.4 nm. The unique microstructure provides excellent mechanical properties with a tensile strength of 572 MPa and a total elongation of 6.4%. After annealing at 800 °C for 1 h, the strength of the alloy does not decrease obviously, showing excellent thermal stability. The thermal conductivity of Cu-1wt.%Y2O3 alloy is about 308 Wm-1K-1 at room temperature and it decreases with increasing temperature. The refined grain size, high strength and excellent thermal stability of Cu-1wt.%Y2O3 alloys can be ascribed to the pinning effects of nanoscale Y2O3 particles dispersed in the Cu matrix. The Cu-Y2O3 alloys with high strength and high thermal conductivity have potential applications in high thermal load components of fusion reactors.
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Tensile properties and microstructure changes under different stress states of tempered 9Cr-F/M steel were characterized using a transmission electron microscope (TEM), electron backscatter diffraction (EBSD), scanning electron microscopy (SEM), Vickers hardness tester, and tensile tester. This tempered steel has a typical lath martensite structure with only a few polygonal ferrites embedded, and M23C6 and MX phases nucleated on the lath boundaries or within the sub-grains. At elevated temperatures, the strength of the steel decreases. However, the elongation at 400 °C is lower than that at room temperature. For the necking zone, tensile deformation made the grain elongated to the direction of applied stress and thus the grain's cross-section becomes smaller. For samples with rectangular working area cross-section, the deformation in the TD direction was more severe than that in the ND direction, which made the grain elongated in the TD direction. These results can provide some guidance for composition optimization of the 9Cr-F/M steel and facilitate a better understanding of the fracture mechanism under different stress states.
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Li2ZrO3-coated and Al-doped micro-sized monocrystalline LiMn2O4 powder is synthesized through solid-state reaction, and the electrochemical performance is investigated as cathode materials for lithium-ion batteries. It is found that Li2ZrO3-coated LiAl0.06Mn1.94O4 delivers a discharge capacity of 110.90 mAhg-1 with 94% capacity retention after 200 cycles at room temperature and a discharge capacity of 104.4 mAhg-1 with a capacity retention of 87.8% after 100 cycles at 55 °C. Moreover, Li2ZrO3-coated LiAl0.06Mn1.94O4 could retain 87.5% of its initial capacity at 5C rate. This superior cycling and rate performance can be greatly contributed to the synergistic effect of Al-doping and Li2ZrO3-coating.
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The biggest obstacle for the application of tungsten as the target materials in the spallation neutron source is its serious corrosion in the coolant of flowing water. For this reason, W-Cr-C clad tungsten was developed by tungsten carburizing in a spark plasma sintering device, with superior corrosion resistance in the static immersion and electrochemical corrosion test. This work focused on its erosion and corrosion performance in a flowing water system, based upon test parameters simulated under the service conditions. W-Cr-C clad tungsten showed superior corrosion resistance to that of bare tungsten due to the corrosion form changing from the intergranular corrosion of bare tungsten to pitting corrosion of W-Cr-C coating. The corrosion rate of tungsten was as high as tenfold that of the coated sample at 20 °C, and at most fourfold at 60 °C after testing for 360 h. Effects of water velocity and temperature on pitting and intergranular corrosion were investigated in detail and their corresponding corrosion mechanisms were analyzed and discussed.
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Li7La3Zr2O12 (LLZO)-based ceramics are well-known as the most promising solid electrolytes for all-solid-state lithium metal batteries. However, its practical application has been significantly hindered by high Li/LLZO interfacial impedance as a result of poor interfacial contact. To solve these issues, in this work, the ZnO layer was magnetron sputter-deposited on Li6.55La2.95Ca0.05Zr1.5Ta0.5O12 (LLCZTO) pellets. It was found that by introducing a 200 nm thick ZnO layer, the interfacial area specific resistance was sharply reduced to as low as 1% that of pristine LLCZTO; meanwhile, Li plating/stripping performance was improved significantly with a long life span of 320 h and a low polarization potential of 0.1 V, whereas a thicker ZnO layer of 600 nm can only improve the interface contact to a very limited extent because of the accumulated volume expansion induced by the in situ transformation of ZnO to the Li-Zn alloy, demonstrating the thickness-dependent beneficial effect of the ZnO layer on improving the Li/LLCZTO interfacial contact and therefore reducing the interfacial resistance. Accordingly, the evolution of the interfacial contact mode and the Li+ migration mechanism during the Li plating/stripping process without or with ZnO layers of different thicknesses were discussed in detail.
RESUMEN
In this work, to improve the cyclability and high-temperature performance of cubic spinel LiMn2O4 (LMO) as cathode materials, Nb5+-doped LiMn2O4 powders coated and uncoated with Al2O3 and/or B2O3 were synthesized via the modified solid-state reaction method. It was found that Nb5+-doped and B2O3 + Al2O3-coated LMO powders comprising 5 µm granular agglomerated fine primary particles smaller than 350 nm in diameter exhibited superior electrochemical properties with initial discharge capacity of 101.68 mA h g-1; we also observed capacity retention of 96.31% after 300 cycles at room temperature (RT) and that of 98% after 50 cycles at 55 °C and 1C rate.