Dynamic Molecular Interphases Regulated by Trace Dual Electrolyte Additives for Ultralong-Lifespan and Dendrite-Free Zinc Metal Anode.

Metallic zinc is a promising anode material for rechargeable aqueous multivalent metal-ion batteries due to its high capacity and low cost. However, the practical use is always beset by severe dendrite growth and parasitic side reactions occurring at anode/electrolyte interface. Here we demonstrate dynamic molecular interphases caused by trace dual electrolyte additives of D-mannose and sodium lignosulfonate for ultralong-lifespan and dendrite-free zinc anode. Triggered by plating and stripping electric fields, the D-mannose and lignosulfonate species are alternately and reversibly (de-)adsorbed on Zn metal, respectively, to accelerate Zn2+ transportation for uniform Zn nucleation and deposition and inhibit side reactions for high Coulombic efficiency. As a result, Zn anode in such dual-additive electrolyte exhibits highly reversible and dendrite-free Zn stripping/plating behaviors for >6400 hours at 1 mA cm-2, which enables long-term cycling stability of Zn||ZnxMnO2 full cell for more than 2000 cycles.

The therapeutic effect of Xuanbai Chengqi Decoction on chronic obstructive pulmonary disease with excessive heat in the lung and fu-organs based on gut and lung microbiota as well as metabolic profiles.

As a prescription for treating lung inflammation and intestinal diseases, Xuanbai Chengqi Decoction (XBCQD) in clinical practice can effectively treat COPD with excessive heat in the lung and fu-organs, which is characterized by phlegm-heat accumulation in the lung and constipation. This study aims to find the potential biomarkers of COPD with excessive heat in the lung and fu-organs from two aspects of lung and intestine based on metabolomics and microbiota analysis, and to evaluate the efficacy of XBCQD as well as to explore the mechanism of drug function according the regulating effect of drugs on these markers. The HPLC-Q-TOF-MS/MS, 16SrDNA technology and multiple statistical methods were used to trace the process of disease and curative effect with XBCQD. Results showed that the onset and development of disease was associated with the imbalance of 41 differential metabolites in plasma, bronchoalveolar lavage fluid and feces and 82 bacteria at the levels of phylum, class, order, family and genus from lung and intestine, including Escherichia-Shigella. However, after treatment with XBCQD, 30 differential metabolites mainly involving in the metabolism of linoleic acid, taurine and hypotaurine metabolism, arachidonic acid metabolism, biosynthesis of primary bile acids, tryptophan metabolism, arginine and proline metabolism and 65 pulmonary and intestinal bacteria at all levels were reversed in the drug group. In addition, the results of the correlation analysis showed that specific microbiota from lung and intestine and reversed differential metabolites had a significant correlation, and they could affect each other in the course of disease occurrence and treatment. This study preliminarily confirmed that XBCQD can be used to treat COPD with excessive heat in the lung and fu-organs through lung-intestine simultaneous treatment. It also provided new strategies for the treatment of lung diseases or intestinal diseases, and new research ideas for the evaluation of drug efficacy.

[Soil Salinity Estimation Based on Near-Ground Multispectral Imagery in Typical Area of the Yellow River Delta].

This study chooses the core demonstration area of 'Bohai Barn' project as the study area, which is located in Wudi, Shandong Province. We first collected near-ground and multispectral images and surface soil salinity data using ADC portable multispectral camera and EC110 portable salinometer. Then three vegetation indices, namely NDVI, SAVI and GNDVI, were used to build 18 models respectively with the actual measured soil salinity. These models include linear function, exponential function, logarithmic function, exponentiation function, quadratic function and cubic function, from which the best estimation model for soil salinity estimation was selected and used for inverting and analyzing soil salinity status of the study area. Results indicated that all models mentioned above could effectively estimate soil salinity and models using SAVI as the dependent variable were more effective than the others. Among SAVI models, the linear model (Y = -0.524x + 0.663, n = 70) is the best, under which the test value of F is the highest as 141.347 at significance test level, estimated R2 0.797 with a 93.36% accuracy. Soil salinity of the study area is mainly around 2.5 per thousand - 3.5 per thousand, which gradually increases from southwest to northeast. The study has probed into soil salinity estimation methods based on near-ground and multispectral data, and will provide a quick and effective technical soil salinity estimation approach for coastal saline soil of the study area and the whole Yellow River Delta.