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Lithium-sulfur batteries (LSBs) are regarded as promising candidates for next-generation electrochemical energy storage systems due to their low cost and high energy density. However, the insulative sulfur, the volume expansion and high soluble polysulfides are three roots impeding their practical applications, and consequently bring challenges of low sulfur utilization, poor cyclic stability and sluggish redox kinetics. Herein, a special core-shell ZnS-CNTs/S@Ni(OH)2 (labeled as ZnS-CNTs/S@NH) cathode has been designed to overcome above obstacles and elevate the electrochemical performance. The ZnS-CNTs/S@NH cathode is synthesized via a facile step-by-step strategy, in which ZnS-decorated CNTs was used as a framework to load sulfur and followed with a ultrathin Ni(OH)2 (NH) layer encapsulation. The ZnS-CNT core combines merits of CNT network and polar ZnS quantum dots (QDs), accommodating the volume change, offering efficient pathways for fast electron/ion transport, and anchoring polysulfides through polar interactions. The outer Ni(OH)2 shell physically confines the active material and meanwhile provides plenty of catalytic sites for effective polysulfide chemisorption. Benefiting from these merits, the ZnS-CNTs/S@NH cathode exhibits excellent cell performances in comparison with ZnS-CNTs/S and CNTs/S. Its discharge capacity at different C-rates is optimal in the three cathodes, which decreases from 1037.0 mAh g-1 at 0.1 C to 646.1 mAh g-1 at 2.0 C. Its cyclic capacity also manifests the slowest reduction from 861.1 to 760.1 mAh g-1 after 150 cycles at 0.5 C, showing a high retention (88.3%) and a tiny average fading rate (0.078%). The strategy in this work provides a feasible approach to design and construct core-shell cathode materials for realizing practically usable Li-S batteries.

The United States, Russia and China are militarily and economically among the most powerful countries in the post-Cold War period, and the interactions between the three powers heavily influence the international system. However, different conclusions about this question are generally made by researchers through qualitative analysis, and it is necessary to objectively and quantitatively investigate their interactions. Monthly-aggregated event data from the Global Data on Events, Location and Tone (GDELT) to measure cooperative and conflictual interactions between the three powers, and the complementary cumulative distribution function (CCDF) and the vector autoregression (VAR) method are utilized to investigate their interactions in two periods: January, 1991 to September, 2001, and October, 2001 to December, 2016. The results of frequencies and strengths analysis showed that: the frequencies and strengths of USA-China interactions slightly exceeded those of USA-Russia interactions and became the dominant interactions in the second period. Although that cooperation prevailed in the three dyads in two periods, the conflictual interactions between the USA and Russia tended to be more intense in the second period, mainly related to the strategic contradiction between the USA and Russia, especially in Georgia, Ukraine and Syria. The results of CCDF indicated that similar probabilities in the cooperative behaviors between the three dyads, but the differences in the probabilities of conflictual behaviors in the USA-Russia dyad showed complicated characteristic, and those between Russia and China indicated that Russia had been consistently giving China a hard time in both periods when dealing with conflict. The USA was always an essential factor in affecting the interactions between Russia and China in both periods, but China’s behavior only played a limited role in influencing the interactions between the USA-Russia dyad. Our study provides quantitative insight into the direct cooperative and conflictual interactions between the three dyads since the end of the Cold War and helps to understand their interactions better.

The UC emission spectra, UCL intensity dependence on the pump power density and decay curves of UC emissions of the CaF2 UCNCs under multi-wavelength excitation.

Constructing sulfur hosts with high electronic conductivity, large void space, strong chemisorption, and rapid redox kinetics is critically important for their practical applications in lithium–sulfur batteries (LSBs). Herein, by coupling ZnS quantum dots (QDs) with carbon nanotubes (CNTs), one multifunctional sulfur host CNT/ZnS-QDs is designed via a facile one-step hydrothermal method. SEM and TEM analyses reveal that small ZnS-QDs (−1 at 0.2 C to 544 mAh g−1 at 2.0 C, showing rate capability much higher than CNT/S and other CNT/ZnS-QDs/S samples. After 150 cycles, the cyclic capacity at 0.5 C exhibits a slow reduction from 1051 mAh g−1 to 771 mAh g−1, showing a high retention of 73.4% with a coulombic efficiency of over 99%. The electrochemical impedance spectroscopy analyses demonstrate that this special architecture juggles high conductivity and excellent confinement of polysulfides, which can significantly suppress the notorious shuttle effect and accelerate the redox kinetics. The strategy in this study provides a feasible approach to design efficient sulfur hosts for realizing practically usable LSBs.

The low sulfur utilization, cycling instability, and sluggish kinetics are the critical obstructions to practical applications of lithium-sulfur batteries (LSBs). Constructing sulfur hosts with high conductivity, suppressed shuttle effect, and rapid kinetics is essential for their practical application in LSBs. Here, we synthetically utilized the merits of ZnSe quantum dots (QDs) and layered Ni(OH)2to boost the performance of LSBs. A novel core-shell ZnSe-CNTs/S@Ni(OH)2was constructed using the ZnSe-CNTs network as framework to load sulfur and following with Ni(OH)2encapsulation. The CNT network decorated with ZnSe QDs not only serves as a conductive framework providing fast electron/ion transfer channels, but also limits polysulfide diffusion physically and chemically. Layered Ni(OH)2, the wrinkled encapsulation, not only permits fast electron/ion transfer, but also buffers the expansion, confines active materials, and limits the polysulfide dissolution chemically. When used as a cathode, ZnSe-CNTs/S@Ni(OH)2presents enhanced electrochemistry performance compared with ZnSe-CNTs/S and CNTs/S. The average specific capacity decreases from 1021.9 mAh g-1at 0.2 C to 665.0 mAh g-1at 2 C, showing rate capacity much higher than ZnSe-CNTs/S and CNTs/S. After 150 cycles, the capacity at 0.5 C slowly reduces from 926.7 to 789.0 mAh g-1, showing high retention of 85.1%. Therefore, our investigation provides a new strategy to construct a promising sulfur cathode for LSBs.

VO2(B), VO2(M), and V2O5 are the most famous compounds in the vanadium oxide family. Here, their gas-sensing properties were investigated and compared. VO2(B) nanoflakes were first self-assembled via a hydrothermal method, and then VO2(M) and V2O5 nanoflakes were obtained after a heat-phase transformation in nitrogen and air, respectively. Their microstructures were evaluated using X-ray diffraction and scanning and transmission electron microscopies, respectively. Gas sensing measurements indicated that VO2(M) nanoflakes were gas-insensitive, while both VO2(B) and V2O5 nanoflakes were highly selective to ammonia at room temperature. As ammonia sensors, both VO2(B) and V2O5 nanoflakes showed abnormal p-type sensing characteristics, although vanadium oxides are generally considered as n-type semiconductors. Moreover, V2O5 nanoflakes exhibited superior ammonia sensing performance compared to VO2(B) nanoflakes, with one order of magnitude higher sensitivity, a shorter response time of 14&ndash, 22 s, and a shorter recovery time of 14&ndash, 20 s. These characteristics showed the excellent potential of V2O5 nanostructures as ammonia sensors.

Silicon nanowires (SiNWs) with a length of about 8 μm and zinc oxide nanorods (ZnONRs) with a length of about 200 nm were prepared by wet chemical etching and chemical bath deposition, respectively. Capacitive humidity sensors based on ZnONRs/SiNWs were fabricated and their humidity sensing properties were examined at room temperature (∼25 °C). The largest response range of the sensors is 2.40–64.40 nF when the relative humidity (RH) changes from 11.30 to 97.69%. The sensitivity is 0.69 nF/% RH. The longest response and recovery time is ∼26 and 7 s, respectively, which corresponding to 97.69% RH. The sensors are proven to have long-term stability, with a maximum relative standard deviation (RSD) of 2.93% corresponding to 11.30% RH during about one month at room temperature in air. ZnONRs/SiNWs are a better ideal capacitive humidity sensing material compared to those we previously reported. It might be easy to miniaturize and compatible with traditional integrated circuit (IC) process.

Proceedings 18th International Symposium on Flow Visualization

There are a large number of paramagnetic defects on the surface of as-grown silicon nanowires (SiNWs) in contrast to H-terminated silicon (Si). Herein, SiNWs arrays were fabricated by chemical etching, Nickel nanoparticles (Ni NPs) were deposited on the surface of SiNWs arrays by the electroless plating. The influence of paramagnetic defects on the magnetic property of Ni/SiNWs was investigated and compared to Ni/Si. The paramagnetic defects of as-grown SiNWs and H-terminated Si were studied by ESR and FTIR spectra. The diameter distribution of Ni NPs on the surface of SiNWs arrays and Si was probed by SEM and fitted by the lognormal probability density function. The results reveal that the diameters of Ni NPs are 35.09 ± 0.53 and 34.92 ± 0.72 nm respectively. The magnetic properties of M–H hysteresis loops for Ni/SiNWs and Ni/Si were measured from 5 to 400 K. With the temperature increasing, the saturation magnetization of Ni/SiNWs and Ni/Si decreases gradually due to the thermal activation effect. Overall temperature range (5–400 K), the saturation magnetization of Ni/Si follows the modified Bloch's law. However, the data of Ni/SiNWs are only valid for high temperature range (50–400 K). At low temperature (5 K), there is an abrupt increase and the experimental data deviated from the modified Bloch model. This deviation at low temperature is associated with surface paramagnetic defects of SiNWs.

Periglacial phenomena and palaeobotany evidence of environmental changes are present in the Daqingshan area, northern China. This arid-semiarid area is sensitive to climatic change. There were four climatic periods during the Holocene. During the Hypsithermal, the annual mean temperature was 1–2 °C higher than today. On the other hand, the annual mean temperature was 2.0–2.5 °C lower during recent glaciation and about 7 °C lower at the end of the Late Pleistocene. The fluctuation of vertical vegetation belts was about 200–600 m during the Holocene. Des phenomenes periglaciaires et des observations paleobotaniques demontrent l'existence de changements de l'environnement dans la region de Daqingshan, au nord de la Chine. Cette region aride ou semi-aride est tres sensible aux changements climatiques. Quatre periodes climatiques ont ete reconnues pendant l'Holocene. Pendant l'Hypsithermal, la temperature moyenne annuelle etait 1 a 2 °C plus elevee qu'aujourd'hui. D'autre part, la temperature moyenne annuelle etait 2,0 a 2,5 °C plus basse pendant la glaciation recente et environ 7 °C plus elevee a la fin du Pleistocene. Les modifications des limites verticales de la vegetation pendant l'Holocene ont ete comprises approximativement entre 200 et 600 m.

Correctly and efficiently estimating hydrological responses corresponding to a specific storm event at the streams in a watershed is the main goal of any sound water resource management strategy. Methods for calculating a stream flow hydrograph at the selected streams typically require a great deal of spatial and temporal watershed data such as geomorphological data, soil survey, landcover, precipitation data, and stream network information to name a few. However, extracting and preprocessing such data for estimation and analysis is a hugely time-consuming task, especially for a watershed with hundreds of streams and lakes and complicated landcover and soil characteristics. To deal with the complexity, traditional models have to simplify the watershed and the streams network, use average values for each subcatchment, and then indirectly validate the model by adjusting the parameters through calibration and verification. To obviate such difficulties, and to better utilize the new, high precision spatial/temporal data, a new massive spatiotemporal watershed hydrological storm event response model (MHSERM) was developed and implemented on ESRI ArcMap platform. Different from other hydrological modeling systems, the MHSERM calculated the rainfall run off at a resolution of finer grids that reflects high precision spatial/temporal data characteristics of the watershed, not at conventional catchment or subcatchment scales, and that can simulate the variations of terrain, vegetation and soil far more accurately. The MHSERM provides a framework to utilize the USGS DEM and Landcover data, NRCS SSURGO and STATSGO soil data and National Hydrology Dataset (NHD) by handling millions of elements (grids) and thousands of streams in a real watershed and utilizing the Spatiotemporal NEXRAD precipitation data for each grid in pseudo real-time. Specifically, the MHSERM model has the following new functionalities: (1) Grid the watershed on the basis of high precision data like USGS DEM and Landcover data, NRCS SSURGO and STATSGO soil data, e.g., at a 30 meter by 30 meter resolution; (2) Delineate catchments based on the USGS National Digital Elevation Model (DEM) and the stream network data of the National Hydrography Dataset (NHD); (3) Establish the stream network and routing sequence for a watershed with hundreds of streams and lakes extracted from the National Hydrography Dataset (NHD) either in a supervised or unsupervised manner; (4) Utilize the NCDC NEXRAD precipitation data as spatial and temporal input, and extract the precipitation data for each grid; (5) Calculate the overland runoff volume, flow path and slope to the stream for each grid; (6) Dynamically estimates time of concentration to the stream for each interval, and only for the grids with rainfall excess, not for the whole catchment; (7) Deal with different hydrologic conditions (Good, Fair, Poor) for landcover data and different Antecedent Moisture Condition (AMC); (8) Process single or a series of storm events automatically; thus, the MHSERM model is capable of simulating both discrete and continuous storm events; (9) Calculate the temporal flow rate (i.e., hydrograph) for all the streams in the stream network within the watershed, save them to a database for further analysis and evaluation of various what-if scenarios and BMP designs. In MHSERM model, the SCS Curve number method is used for calculating overland flow runoff volume, and the Muskingum-Cunge method is used for flow routing of the stream network.