In this work,Au loading and micro-morphology regulation were used to synergistically enhance the gas sensing properties of LaFeO_(3)-based materials.2 wt%Au:LaFeO_(3)prepared by electrostatic spinning method has a res...In this work,Au loading and micro-morphology regulation were used to synergistically enhance the gas sensing properties of LaFeO_(3)-based materials.2 wt%Au:LaFeO_(3)prepared by electrostatic spinning method has a response of 38.26 for 1 ppm H_(2)S and 5.32 for 1 ppm HCHO at 120℃.Over a one-month period,the response of 2 wt%Au:LaFeO_(3)decreases by just 0.52%for H_(2)S and 2.07%for HCHO,demonstrating excellent long-term stability.Additionally,for H_(2)S and HCHO at concentrations ranging from 0.1to 1 ppm,all the response-recovery time is within 40 s.2 wt%Au:LaFeO_(3)also shows excellent gas selectivity and humidity resistance.This outstanding gas sensing performance might be attributed to the catalytic sensitization effect of Au NPs,as well as the largest specific surface area,porosity,and the smallest grain size of 2 wt%Au:LaFeO_(3)hollow nanotube.To further enhance gas selectivity and recognition capability of 2 wt%Au:LaFeO_(3)for H_(2)S and HCHO,a machine learning model combining a backpropagation(BP)neural network with response-recovery feature data extracted through principal component analysis(PCA)was trained.This model accurately identified and detected individual gases in a mixture of H_(2)S and HCHO,with an error rate of less than 10%.This work demonstrates the synergistic enhancement of gas sensing properties through Au loading and micro-morphology regulation,offering a novel approach for detecting and identifying gases with cross-responsiveness using non-sensor arrays.展开更多
We report the controlled fabrication of nitrogen doped graphene(NG)nanoplates,which are uniformly decorated with iron nitride(Fe_(3)N)nanoparticles,via ball milling of mixtures of graphite and iron nitrates and the fo...We report the controlled fabrication of nitrogen doped graphene(NG)nanoplates,which are uniformly decorated with iron nitride(Fe_(3)N)nanoparticles,via ball milling of mixtures of graphite and iron nitrates and the following ammonia annealing.The obtained Fe_(3)N@NG composites demonstrate excellent electrocatalytic activity and durability for oxygen evolution reaction,both of which outperform those of the state-of-the-art iridium oxide catalysts.This may be attributed to nitrogen doping as well as the synergistic effect between Fe3N and graphene nanoplates.展开更多
基金Project supported by National Natural Science Foundation of China(22306070,62374112)Shandong Provincial Natural Science Foundation(ZR2021QE265,ZR2023QB002)+3 种基金Shandong Top Talent Special Foundation(0031504)the National Key Research and Development Program of China(2022YFE0105800)Zhejiang Provincial Huzhou Science and Technology Project(2023GZ60)Open Research Fund Program of State Environmental Protection Key Laboratory of Food Chain Pollution Control(FC2022YB05,FC2022YB03)。
文摘In this work,Au loading and micro-morphology regulation were used to synergistically enhance the gas sensing properties of LaFeO_(3)-based materials.2 wt%Au:LaFeO_(3)prepared by electrostatic spinning method has a response of 38.26 for 1 ppm H_(2)S and 5.32 for 1 ppm HCHO at 120℃.Over a one-month period,the response of 2 wt%Au:LaFeO_(3)decreases by just 0.52%for H_(2)S and 2.07%for HCHO,demonstrating excellent long-term stability.Additionally,for H_(2)S and HCHO at concentrations ranging from 0.1to 1 ppm,all the response-recovery time is within 40 s.2 wt%Au:LaFeO_(3)also shows excellent gas selectivity and humidity resistance.This outstanding gas sensing performance might be attributed to the catalytic sensitization effect of Au NPs,as well as the largest specific surface area,porosity,and the smallest grain size of 2 wt%Au:LaFeO_(3)hollow nanotube.To further enhance gas selectivity and recognition capability of 2 wt%Au:LaFeO_(3)for H_(2)S and HCHO,a machine learning model combining a backpropagation(BP)neural network with response-recovery feature data extracted through principal component analysis(PCA)was trained.This model accurately identified and detected individual gases in a mixture of H_(2)S and HCHO,with an error rate of less than 10%.This work demonstrates the synergistic enhancement of gas sensing properties through Au loading and micro-morphology regulation,offering a novel approach for detecting and identifying gases with cross-responsiveness using non-sensor arrays.
基金supported by the Open Research Fund Program of State Environmental Protection Key Laboratory of Food Chain Pollution Control(FC2022YB05,FC2022YB03)National Key Research and Development Program of China(2022YFE0105800)+2 种基金Shandong Top Talent Special Foundation(0031504),Natural Science Foundation of Beijing Municipality(8222042)Huzhou Science and Technology Project(2023GZ60)Special Research Funds of Shandong Jianzhu University(X20077Z0101 and X20087Z0101).
文摘We report the controlled fabrication of nitrogen doped graphene(NG)nanoplates,which are uniformly decorated with iron nitride(Fe_(3)N)nanoparticles,via ball milling of mixtures of graphite and iron nitrates and the following ammonia annealing.The obtained Fe_(3)N@NG composites demonstrate excellent electrocatalytic activity and durability for oxygen evolution reaction,both of which outperform those of the state-of-the-art iridium oxide catalysts.This may be attributed to nitrogen doping as well as the synergistic effect between Fe3N and graphene nanoplates.
