Copper-Based Electrocatalysts for Nitrate Reduction to Ammonia.

Ammonia (NH3) is a highly important industrial chemical used as fuel and fertilizer. The industrial synthesis of NH3 relies heavily on the Haber-Bosch route, which accounts for roughly 1.2% of global annual CO2 emissions. As an alternative route, the electrosynthesis of NH3 from nitrate anion (NO3-) reduction (NO3-RR) has drawn increasing attention, since NO3-RR from wastewater to produce NH3 can not only recycle waste into treasure but also alleviate the adverse effects of excessive NO3- contamination in the environment. This review presents contemporary views on the state of the art in electrocatalytic NO3- reduction over Cu-based nanostructured materials, discusses the merits of electrocatalytic performance, and summarizes current advances in the exploration of this technology using different strategies for nanostructured-material modification. The electrocatalytic mechanism of nitrate reduction is also reviewed here, especially with regard to copper-based catalysts.

[Retrieval of leaf water content of winter wheat from canopy hyperspectral data using partial least square regression].

Accurate estimation of leaf water content (LWC) from remote sensing can assist in determining vegetation physiological status, and further has important implications for drought monitoring and fire risk evaluation. This paper focuses on retrieving LWC from canopy spectra of winter wheat measured with ASD FieldSpec Pro. The experimental plots were treated with five levels of irrigation (0, 200, 300, 400 and 500 mm) in growing season, and each treatment had three replications. Canopy spectra and LWC were collected at three wheat growth stages (booting, flowering, and milking). The temporal variations of LWC, spectral reflectance, and their correlations were analyzed in detail. Partial least square regression embedded iterative feature-eliminating was designed and employed to obtain diagnostic bands and build prediction models for each stage. The results indicate that LWC decreases quickly along with the winter wheat growth. The mean values of LWC for the three stages are respectively 338.49%, 269.65%, and 230.90%. The spectral regions correlated strongly with LWC are 1 587-1 662 and 1 692-1 732 nm (booting), 617-687 and 1 447-1 467 nm (flowering), and 1 457-1 557 nm (milking). As far as the LWC prediction models are concerned, the optimum modes of spectral data are respectively logarithmic, 1st order derivative and plain reflectance. The diagnostic bands detected by PLS are from SWIR, NIR, and SWIR. Retrieval accuracy at the flowering stage is the highest (R2(cv) = 0.889) due to the enhancement of leaf water information at canopy scale via multiple scattering. At the booting and milking stage, accuracies are relatively lower (R2(cv) = 0.750, 0.696), because the retrieval of LWC is negatively affected by soil background and dry matter absorption respectively. This research demonstrated clearly that the spectral response and retrieval of LWC has distinct temporal characteristics, which should not be neglected when developing remote sensing product of crop water content in the future.

[A study of aggregate behavior of green-sensitive dyes containing fluorine].

Five different-structure carboncyanine dyes containing fluorine in methanol solution and the aggregate behavior on the surface of AgIBr tabulate grains were investigated, the photographic capability determined and the sensitive multiple calculated. From the monomolecular absorption curves of dye1, dye2 and dye3 in methanol solution, it can be seen that when the substitute changed from C2H5 to CH3 to no substitute, the maximal absorption peak shifted to a shorter wavelength. Sensitive dye with ethylene (dyel) adsorbed on the AgBrI surface formed a higher peak of J-aggregate with a higher sensitive multiple. Sensitive dye with no substitute (dye3) did not form J-aggregate, which had a low sensitive multiple and reduced the sensitivity. Compared with dye5, dye4 had a sharper and narrower reflective spectrum and a higher sensitive multiple. The results showed that a different-structure dye adsorbed on silver halide grains formed a different J-aggregate. The sensitive dye of J-aggregate with a sharper absorption spectrum had a higher sensitive multiple.