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Lithium-sulfur batteries hold promise for next generation batteries due to their high theoretical energy density and low cost. However, the rapid capacity fading caused by the shuttle of polysulfide between two electrodes severely hinders the practical application of Li–S batteries. To address the issue, we reported a three-dimensional heterostructured TiO 2 nanosheets/N-doped carbon (TO/NC), which is coated on a commercial polypropylene (PP) separator, as an efficient barrier for Li–S batteries. The TO/NC coating layer provides a bipolar chemical adsorption of lithium polysulfides (LiPSs) via TiO 2 nanosheets with exposed (001) facets and N-doped carbon, showing high trapping capacity and remarkable electrocatalytic activity for LiPSs. The slurry-bladed carbon black/sulfur cathode with 64 wt% sulfur offers outstanding performance with an initial capacity of 1314 mA h g−1 at 0.2 C. Over 900 cycles, the cell still maintains the capacity of 448 mA h g−1 at a 1 C rate with a degradation rate of only 0.055% per cycle. The separator reported in this work holds great promise for the development of high-energy Li–S batteries. [ABSTRACT FROM AUTHOR]

Low-cycle fatigue behaviors of Ni-base single crystal superalloys containing different Re contents have been investigated at 760 °C. During heat treatment, Re retards γ′ phases coarsening and equalizes the distribution of γ′ phases. As Re content increases, fatigue life increases and slip bands distribute more inhomogeneously. Moreover, adding Re not only reduces stacking fault energy of the matrix, but also promotes the element segregation to increase the lattice misfit. However, the larger lattice misfit does not lead to the formation of dislocation networks, but which activates dislocation movement and promotes dislocations cross-slip and climbing movement under high temperature and applied stress. On the other hand, with the addition of Re, cyclic deformation behaviors change from cyclic hardening to cyclic stability, mainly depending on a transformation of deformation mechanisms from slip bands cutting through γ and γ′ phases to stacking faults shearing. [ABSTRACT FROM AUTHOR]

Brazing of a Ni-based single crystal superalloy has been investigated with the additive Ni-based superalloy and filler Ni–Cr–W–B alloy at 1260 °C, and attentions were paid to the microstructure evolution during brazing and the stress-rupture behavior at 980 °C of such brazed joints after homogenization. Microstructure in the brazed joint generally includes brazing alloy zone (BAZ), isothermally solidified zone (ISZ) and diffusion affected zone (DAZ). Microstructure evolution during this brazing process is discussed at the heating stage, the holding stage and the cooling stage respectively, according to the diffusion path of B atoms. Initially well-distributed γ/γ′ microstructure in the homogenized bonded zone after heat treatment and substantial γ′ rafts enhance the post-brazed joint to obtain a stress-rupture lifetime of more than 120 h at 980 °C/250 MPa. On the other hand, the decreased stress-rupture behavior of post-brazed joint, compared with parenting material, is ascribed to the presence of inside brazing porosity and stray grain boundary, which not only reduces the effective loading-carrying area but also offers preferential sites for creep vacancy aggregation to further soften stray grain boundary. And finally an early fracture of these post-brazed joints through the intergranular microholes aggregation and growth mode under this testing condition was observed. [ABSTRACT FROM AUTHOR]

High temperature stress rupture anisotropies of a second generation Ni-base single crystal (SC) superalloy specimens with [001], [011] and [111] orientations under 900 °C/445 MPa and 1100 °C/100 MPa have been investigated in the present study, with attentions to the evolution of γ/γ′ microstructure observed by scanning electron microscopy and the dislocation configuration characterized by transmission electron microscopy in each oriented specimen. At 1100 °C/100 MPa as well as 900 °C/445 MPa, the single crystal superalloy exhibits obvious stress rupture anisotropic behavior. The [001] oriented specimen has the longest rupture lifetime at 900 °C/445 MPa, and the [111] oriented sample shows the best rupture strength at 1100 °C/100 MPa. While the [011] oriented specimen presents the worst rupture lifetime at each testing condition, its stress rupture property at 1100 °C/100 MPa is clearly improved, compared with 900 °C/445 MPa. The evident stress rupture anisotropy at 900 °C/445 MPa is mainly attributed to the distinctive movement way of dislocations in each oriented sample. Whereas, at 1100 °C/100 MPa, together with the individual dislocation configuration, the evolution of γ/γ′ microstructure in each orientation also plays a key role in the apparent stress rupture anisotropy. [ABSTRACT FROM AUTHOR]

In this study, a NiCrAlY + AlNiY composite coating was prepared by arc ion plating technique and subsequent annealing treatment. Cyclic hot corrosion tests of the composite coating and a reference NiCrAlY coating coated with mixed salts of Na 2 SO 4  + K 2 SO 4 and Na 2 SO 4  + NaCl were carried out at 700 °C. The results indicated that the composite coating performed better against the corrosion due to the gradient element distribution in Al-enriched outer layer and Cr-enriched inner layer. The corrosion mechanisms for the two coatings were also discussed. [ABSTRACT FROM AUTHOR]

Feature selection is one of the most fundamental problems in machine learning and has drawn increasing attention due to high-dimensional data sets emerging from different fields like bioinformatics. For feature selection, filter methods play an important role, since they can be combined with any machine learning model and can heavily reduce run time of machine learning algorithms. The aim of the analyses is to review how different filter methods work, to compare their performance with respect to both run time and predictive accuracy, and to provide guidance for applications. Based on 16 high-dimensional classification data sets, 22 filter methods are analyzed with respect to run time and accuracy when combined with a classification method. It is concluded that there is no group of filter methods that always outperforms all other methods, but recommendations on filter methods that perform well on many of the data sets are made. Also, groups of filters that are similar with respect to the order in which they rank the features are found. For the analyses, the R machine learning package mlr is used. It provides a uniform programming API and therefore is a convenient tool to conduct feature selection using filter methods. [ABSTRACT FROM AUTHOR]