In Situ Adsorption-Reduction of Chromium(VI) with a Self-Regenerated Intelligent Urea-MOF(Fe): Preparation, DFT Simulation and Mechanism.

Environmental pollution caused by hexavalent chromium becomes worse and worse, so it is urgent to develop efficient and stable treatments. In this work, urea-doped iron-based metal-organic framework N/MOF(Fe) was prepared via the solvothermal method, and its microstructure was systematically analyzed using characterization techniques, such as SEM, TEM, BET, XRD, FTIR, XPS and so on. Comparison of FTIR spectra with different urea doping amounts revealed the regulation law of amino functional groups and their influence on the construction of Cr(VI) adsorption active sites.

In-Depth Excavation and Screening of Triterpene Saponins From the Rhizome of Panax japonicus Using High Performance Liquid Chromatography Coupled to Electrospray Ionization and Quadrupole Time-of-Flight Mass Spectrometry.

The rhizome of Panax japonicus (RPJ) has been used for thousands of years in west China. Triterpene saponins (TSs) were considered to be the main pharmacologically bioactive ingredients in RPJ. However, it is difficult and time-consuming to profile and identify them according to the traditional phytochemical methods.

Neural network-based prediction of the secret-key rate of quantum key distribution.

Numerical methods are widely used to calculate the secure key rate of many quantum key distribution protocols in practice, but they consume many computing resources and are too time-consuming. In this work, we take the homodyne detection discrete-modulated continuous-variable quantum key distribution (CV-QKD) as an example, and construct a neural network that can quickly predict the secure key rate based on the experimental parameters and experimental results. Compared to traditional numerical methods, the speed of the neural network is improved by several orders of magnitude.