We report localised-surface-plasmon (LSP) enhanced deep-ultraviolet light-emitting diodes (deep-UV LEDs) using Al nanoparticles for LSP coupling. Polygonal Al nanoparticles were fabricated on the top surfaces of the deep-UV LEDs using the oblique-angle deposition method. Both the top- and bottom-emission electroluminescence of deep-UV LEDs with 279 nm multiple-quantum-well emissions can be effectively enhanced by the coupling with the LSP generated in the Al nanoparticles. The primary bottom-emission wavelength is longer than the primary top-emission wavelength. This difference in wavelength can be attributed to the substrate-induced Fano resonance effect. For resonance modes with shorter wavelengths, the radiation fraction directed back into the LEDs is largest in the direction that is nearly parallel to the surface of the device and results in total reflection and re-absorption in the LEDs.
The quantitative PCR (qPCR) method was firstly used to measure moss abundance with moss chloroplast gene rps4 as compared to that with cyanobacterial 16S rRNA gene and fungal 25-28S rRNA gene in the early succession stage of biological soil crusts (BSCs). Four sites with three BSC types collected from Hobq Desert of China, representing cyanobacterial-, lichen-, and moss-dominated BSCs were investigated. The copies of the moss rps4 gene, cyanobacterial 16S rRNA gene, and fungal 25-28S rRNA gene, chlorophyll a content, and the community composition variated significantly. The moss rps4 gene copies attained a significant positive correlation with chlorophyll a content and showed a crossvalidation with relative moss biomass.
Based on Johansen Cointegration Test, this paper sheds light on the long-run equilibrium relationship between natural gas consumption, gas production, and GDP in China. Three different natural gas demand scenarios of low, medium and high rates in the next ten years are considered, and a Neural Network Autoregression Model is used to predict the future carbon dioxide emission. We conclude: (1) In all three scenarios, the growth rates of natural gas consumption are all higher than those of natural gas production, while the gap between demand and domestic supply will gradually turn broader and China will largely rely on imports ; (2) In the scenario of low-rate economic growth, natural gas consumption will grow slowly, and it will be difficult to realize the carbon emission reduction targets by 2030 due to low-rate substitution of natural gas for coal; (3) If medium-rate to high-rate economic growth sustains, coupled with rapid increase in natural gas consumption and production, China’s Carbon Emission Reduction Targets for 2030 can be achieved with high-rate substitution of natural gas for coal.
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