Currently, all‐inorganic CsPbX3 (X = Br, I, and Cl) perovskites (IPs) are emerging as excellent candidate materials for exploring optoelectronic devices, due to their superior optical/electronic performances. However, their intrinsic poor stability greatly limits their practical applications. Here, a general strategy is reported for in situ growth of all‐inorganic perovskite nanocrystals (IPNCs) in polymer fibers with highly uniform size and spatial distribution, which is based on one‐step electrospinning of solutions containing IPs precursors and polymers. It is verified that the IPNCs of CsPbX3 can be uniformly encapsulated within the polymer fibers with finely tuned compositions, by rationally adjusting the ratios of PbX2 and CsX salts in the raw solutions. Consequently, the photoluminescence (PL) emissions of CsPbX3@polymer fibers can be readily tuned to cover the whole visible range. The obtained CsPbBr3@polymer fibers exhibit fundamentally improved water/thermal stabilities with a PL quantum yield (QY) of 48%. Their PL QY retains beyond 70% of its original value after being immersed in water for 192 h and maintains over 50% after being heated at 80 °C for 120 min. Furthermore, the light emitting diodes with high brightness based on CsPbBr3@polymer fibers are constructed, suggesting their promising applications.

This paper investigates the transportation and vehicular modes classification by using big data from smartphone sensors. The three types of sensors used in this paper include the accelerometer, magnetometer, and gyroscope. This study proposes improved features and uses three machine learning algorithms including decision trees, K-nearest neighbor, and support vector machine to classify the user’s transportation and vehicular modes. In the experiments, we discussed and compared the performance from different perspectives including the accuracy for both modes, the executive time, and the model size. Results show that the proposed features enhance the accuracy, in which the support vector machine provides the best performance in classification accuracy whereas it consumes the largest prediction time. This paper also investigates the vehicle classification mode and compares the results with that of the transportation modes.

Copyright by the AIP Publishing. Shukla, Nitin C.; Liao, Hao-Hsiang; Abiade, Jeremiah T.; et al., "Thermal conductivity and interface thermal conductance of amorphous and crystalline Zr47Cu31Al13Ni9 alloys with a Y2O3 coating," Appl. Phys. Lett. 94, 081912 (2009); http://dx

Inorganic perovskites (IP) CsPbX3 (X = Cl, Br, I) have rapidly emerged as excellent candidate materials for optoelectronic devices, due to their superior optical/electronic performances. However, poor stability related to...

The fatigue behavior of magnesium-alloy, AZ31B, prestrained by equal-channel-angular pressing (ECAP) was studied as a function of the accumulated plastic-strain level and the orientation of the samples (along and perpendicular to the ECAP pressing direction). The material was processed via route B C , at 200°C, for 1, 2, and 8 passes, with and without a back pressure (BP) applied on the billet during ECAP. The low-cycle fatigue behavior of the AZ31B alloy is shown to be anisotropic and texture dependent. Due to the initial texture orientation, the specimens loaded parallel to the ECAP pressing direction have a longer fatigue life than the samples loaded perpendicular to it. The low-cycle fatigue life of the AZ31B alloy is enhanced by ECAP. The fatigue-property improvement is discussed in light of the grain-size refinement, enhanced ductility, and texture evolution.

Using an infrared (IR) camera, we observed in situ the dynamical shear-banding processes of the geometrically constrained specimens of a Zr-based bulk metallic glass in a quasi-static compression at various strain rates, measured the temperature evolutions within the specimens, and calculated the temperature increases in shear bands. Strain-rate-dependent serrated plastic flow is a result of shear-banding operations. The average temperature increases in the specimens are observed during the plastic deformation and their magnitudes are strain rate dependent. The temperature increases in shear bands are related to strain rates. The higher the strain rates, the larger the temperature increases in a shear band. The shear strain in a shear band may be responsible for the strain-rate-dependent temperature increase in a shear band.

We investigate the effect of nickel nanoparticle size on thermal transport in multilayer nanocomposites consisting of alternating layers of nickel nanoparticles and yttria stabilized zirconia (YSZ) spacer layers that are grown with pulsed laser deposition. Using time-domain thermoreflectance, we measure thermal conductivities of k=1.8, 2.4, 2.3, and 3.0 W m−1 K−1 for nanocomposites with nickel nanoparticle diameters of 7, 21, 24, and 38 nm, respectively, and k=2.5 W m−1 K−1 for a single 80 nm thick layer of YSZ. We use an effective medium theory to estimate the lower limits for interface thermal conductance G between the nickel nanoparticles and the YSZ matrix (G>170 MW m−2 K−1), and nickel nanoparticle thermal conductivity.

We describe the design, assembly, and operation of a novel instrument for measuring Seebeck coefficient and electrical resistivity of bulk thermoelectric materials of various shapes and sizes in the temperature range from 300 K to 600 K. The ability of the system to measure samples with a variety of shapes and sizes provides great flexibility in sample fabrication and preparation. The system is verified with Seebeck coefficient measurements on a standard material (SRM 3451) from NIST as well as a separate ZnO sample, a promising high temperature thermoelectric material, and the electrical resistivity is measured using the van der Pauw method. A variety of nickel-based samples with varying thickness are examined to validate the system and to demonstrate instrument precision and accuracy. The results indicate that this instrument is capable of rapid evaluation of the power factor for bulk thermoelectric materials without being limited to samples with specific shapes or dimensions.