Metal?nitrogen doped carbon is an emerging class of non?precious metal electrocatalysts used in carbon dioxide reduction reactions(CO₂RR).Metal?nitrogen doped carbon is an emerging class of non?precious metal electrocatalysts in carbon dioxide reduction reactions(CO₂RR).Current preparation methods mainly use impregnation?based post?processing,which often involves multiple preparation steps and limited types of metals.In this work,an iron?copper(FeCu) and nitrogen doped carbon catalyst was prepared through a coordination competition strategy.In the preparation,4,4?bipyridine served as ligand and iron nitrate and copper chloride as metal sites to form FeCu coordination polymers,which was directly transformed into FeCu?nitrogen doped porous carbon catalysts.The physicochemical properties such as morphological structure,metal species state and pore structure were characterized by SEM,TEM,XRD and N₂ adsorption?desorption,respectively.The performance of different FeCu?nitrogen doped carbon catalysts in electrocatalytic CO₂RR to syngas was examined in a three?electrode system.The regulation of n(CO)/n(H₂) in syngas was studied by adjusting the metal composition,metal combination and pyrolysis temperature,etc.The n(CO)/n(H₂) generated in the wide potential range of -0.7 V to -1.3 V can be regulated in the range of 0.15~3.33,which can meet the supply gas ratios for important reactions such as methanol synthesis,Fischer?Tropsch reaction and syngas fermentation.

The characteristics of acoustic signal for pipe leakage and general wavelet primary function were analyzed. It concludes that the suitable primary functions for acoustic signal of pipe leakage are Daubechies wavelet and Symlet wavelet. The experiments of the acoustic inspection were conducted in water leakage of the carbon steel pipe and the wavelet transform of the leakage signal was done by db5 and sym5 wavelet. It shows that the most energy is a6 level signal energy and the peak frequency of the signal focus on 2.90~3.81 kHz. The maximum relative error of two different wavelet transforms is 0.77% in the energy analysis and 5.17% in frequency analysis.