17 research outputs found

    Relative increases in CH4 and CO2 emissions from wetlands under global warming dependent on soil carbon substrates

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    15 páginas.- 3 figuras.- 57 referencias.- Supplementary information The online version contains supplementary material available at https://doi.org/10.1038/s41561-023-01345-6Compelling evidence has shown that wetland methane emissions are more temperature dependent than carbon dioxide emissions across diverse hydrologic conditions. However, the availability of carbon substrates, which ultimately determines microbial carbon metabolism, has not been adequately accounted for. By combining a global database and a continental-scale experimental study, we showed that differences in the temperature dependence of global wetland methane and carbon dioxide emissions (EM/C) were dependent on soil carbon-to-nitrogen stoichiometry. This can be explained mainly by the positive relationship between soil organic matter decomposability and EM/C. Our study indicates that only 23% of global wetlands will decrease methane relative to carbon dioxide emissions under future warming scenarios when soil organic matter decomposability is considered. Our findings highlight the importance of incorporating soil organic matter biodegradability into model predictions of wetland carbon–climate feedback.The authors received funding from Strategic Priority Research Program of the Chinese Academy of Sciences (XDA28030102 to Y.L.), National Natural Scientific Foundation of China (92251305 to M.N., 41622104 to Y.L.), Innovation Program of the Institute of Soil Science (ISSASIP2201 to Y.L.) and Youth Innovation Promotion Association of the Chinese Academy of Sciences (2016284 to Y.L.).Peer reviewe

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    Charge Transfer Effect on Raman and Surface Enhanced Raman Spectroscopy of Furfural Molecules

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    The detection of furfural in transformer oil through surface enhanced Raman spectroscopy (SERS) is one of the most promising online monitoring techniques in the process of transformer aging. In this work, the Raman of individual furfural molecules and SERS of furfural-Mx (M = Ag, Au, Cu) complexes are investigated through density functional theory (DFT). In the Raman spectrum of individual furfural molecules, the vibration mode of each Raman peak is figured out, and the deviation from experimental data is analyzed by surface charge distribution. In the SERS of furfural-Mx complexes, the influence of atom number and species on SERS chemical enhancement factors (EFs) are studied, and are further analyzed by charge transfer effect. Our studies strengthen the understanding of charge transfer effect in the SERS of furfural molecules, which is important in the online monitoring of the transformer aging process through SERS

    Application of Self-Assembled Raman Spectrum-Enhanced Substrate in Detection of Dissolved Furfural in Insulating Oil

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    Accurate detection of dissolved aging features in transformer oil is the key to judging the aging degree of oil-paper insulation. In this work, in order to realize in situ detection of furfural dissolved in transformer oil, silver nanoparticles were self-assembled on the surface of gold film with P-aminophenylthiophenol (PATP) as a coupling agent. Rhodamine-6G (R6G) was used as the probe molecule to test the enhancement effect. By optimizing the molecular concentration, molecular deposition time, and silver sol deposition time of PATP, the nanoparticles were made more uniform and compact, and an enhanced substrate with rich hot spots was obtained. The optimum substrate was developed, and surface-enhanced Raman spectroscopy (SERS) detection of trace furfural dissolved in transformer oil was realized. The results showed that the substrate prepared under the conditions of 0.1 mol/L PATP, 5 hours deposition in PATP and 12 hours immersion in silver sol, had the best reinforcement effect (that is, uniform and compact particle arrangement and no particle clusters). By use of this substrate, the minimum detectable concentration of furfural in transformer oil was about 1.06 mg/L, which provides a new method for fast and nondestructive detection of transformer aging diagnosis

    Centrifugal Extraction-Assisted Fiber-Enhanced Raman Spectroscopy for Online Detection of Trace Furfural in Oil Power Equipment

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    Oil-paper insulated equipment is integral in power conversion and supports low-loss electricity transport. As a characteristic byproduct of the oil-paper insulation system, the realization of efficient detection of furfural in oil is crucial to the safe operation of the power grid. We proposed a novel approach using dual-enhanced Raman spectroscopy for sensing trace liquid components. This method employs a centrifugal extractor to separate and enrich the targeted components, achieving selective enhancement. The optimal phase ratio was determined to be 30:1. A liquid-core fiber was used to optimize the laser transmission efficiency and Raman signal collection efficiency, resulting in a nonselective signal enhancement of 44.86. It also investigated the impact of intermolecular interactions on the shift of Raman spectra, identifying the reasons for the differences in Raman signals between pure furfural, furfural in oil, and furfural in water. A batch of samples with furfural dissolved in insulation oil was measured using this system and achieved a limit of detection of 0.091 mg/L. The stability of the dual-enhanced Raman platform was experimentally verified with a spectral intensity fluctuation of 0.68%. This method is fast, stable, adaptable, and suitable for the detection of a wide range of liquid ingredients
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