Perovskite oxides with flexible compositions and electronic structures have great potential for application in electrocatalytic water oxidation reactions. However, few studies have focused on the application of perovskite oxides in electrocatalytic oxidation reactions of organic molecules, probably due to the absence of active species because of the poor conductivity and high energy barrier of the surface reconstruction. Herein, we report Cu 3 N nanosheets with a typical antiperovskite structure as electrocatalysts for selectively converting methanol to formate. The as-prepared antiperovskite nitride Cu 3 N samples exhibit a Faradic efficiency exceeding 90% for methanol to formate over a wide potential range, which was further confirmed by online electrochemical mass spectrometry and in situ infrared reflectance absorption spectroscopy. Moreover, the high-resolution transmission electron microscopy, X-ray absorption spectroscopy, and in situ Raman spectroscopy results indicate that the core-shell structure formed by generating surface Cu(II) species triggers the electrocatalytic methanol oxidation reaction activity, whereas the pristine Cu 3 N core facilitates the electron transport inside the catalyst during the electrocatalytic process.This study provides a modelable scheme for the highly selective conversion of methanol and introduces a novel nonoxide perovskite material for the electrochemical conversion of small-organic molecules.

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Pneumatic probes can be used to obtain the flow field parameters such as pressure, temperature and air flow angle, and has been widely used to measure the flow field in compressors. When probes are inserted into the compressor to measure the flow field, the probe stems will cause blockage in the flow field and interfere with it, reducing the pressure ratio and efficiency of the compressor. This paper proposes a method to reduce the interference of the stems by their surface suction. Three-dimensional models of a compressor with different types of probe stems were established. Computational Fluid Dynamics (CFD) simulations of the flow within a low-speed compressor without/with the probe stems and the stems having surface suction holes were conducted. The involved numerical methods were validated by the experimental data. The effects of the surface suction holes on the performance of this compressor were compared and analyzed in terms of blockage coefficient in the passage by the vortex identification method. The results show that probe stem surface suction can reduce the blockage of the stems on the downstream flow field. Compared with the situation of no suction, there is an optimal suction mass flow rate that can minimize the adverse effect of probe stems on the compressor aerodynamic performance. For the same type of the probe stems, the compressor performances, i.e., pressure ratio, efficiency and stability margin, are recovered with the increase of the number of suction holes along the span-wise direction.

Depression, especially moderate depression and MDD, brings huge pressure and loss to patients and society through a series of symptoms. However, the current diagnosis of depression is short of objective, quantifiable, and absolute detection techniques. If we can find specific depression molecular biomarkers and high-sensitivity and high-accuracy molecular biomarker detection technology, it can help patients with depression to diagnose and predict earlier. In this paper, the heterogeneous biomolecules of depression are classified into intracranial markers and blood markers, and the biomolecules with representative value are listed. Meanwhile, it analyzes and compares the current popular biological detection technologies, IHC and RNAscope. If the heterogeneous depression biomarkers can be detected by the combination of IHC and RNAscope technology, the accuracy and timeliness of depression diagnosis will be greatly improved, and lay the groundwork for better depression treatments in the future.