Platinum-based alloy nanoparticles are the most attractive catalysts for the oxygen reduction reaction at present,but an in-depth understanding of the relationship between their short-range structural information and ...Platinum-based alloy nanoparticles are the most attractive catalysts for the oxygen reduction reaction at present,but an in-depth understanding of the relationship between their short-range structural information and catalytic performance is still lacking.Herein,we present a synthetic strategy that uses transition-metal oxide-assisted thermal diffusion.PtCo/C catalysts with localized tetragonal distortion were obtained by controlling the thermal diffusion process of transition-metal elements.This localized structural distortion induced a significant strain effect on the nanoparticle surface,which further shortened the length of the Pt-Pt bond,improved the electronic state of the Pt surface,and enhanced the performance of the catalyst.PtCo/C catalysts with special short-range structures achieved excellent mass activity(2.27 Amg_(Pt)^(-1))and specific activity(3.34 A cm^(-2)).In addition,the localized tetragonal distortion-induced surface compression of the Pt skin improved the stability of the catalyst.The mass activity decreased by only 13% after 30,000 cycles.Enhanced catalyst activity and excellent durability have also been demonstrated in the proton exchange membrane fuel cell configuration.This study provides valuable insights into the development of advanced Pt-based nanocatalysts and paves the way for reducing noble-metal loading and increasing the catalytic activity and catalyst stability.展开更多
Image quality assessment has become increasingly important in image quality monitoring and reliability assuring of image processing systems.Most of the existing no-reference image quality assessment methods mainly exp...Image quality assessment has become increasingly important in image quality monitoring and reliability assuring of image processing systems.Most of the existing no-reference image quality assessment methods mainly exploit the global information of image while ignoring vital local information.Actually,the introduced distortion depends on a slight difference in details between the distorted image and the non-distorted reference image.In light of this,we propose a no-reference image quality assessment method based on a multi-scale convolutional neural network,which integrates both global information and local information of an image.We first adopt the image pyramid method to generate four scale images required for network input and then provide two network models by respectively using two fusion strategies to evaluate image quality.In order to better adapt to the quality assessment of the entire image,we use two different loss functions in the training and validation phases.The superiority of the proposed method is verified by several different experiments on the LIVE datasets and TID2008 datasets.展开更多
Five generalized physical models of different distortion ratios were built according to DOU Guo-ren's similarity theory of total sediment transport modeling for estuarine and coastal regions. Experiments on local ...Five generalized physical models of different distortion ratios were built according to DOU Guo-ren's similarity theory of total sediment transport modeling for estuarine and coastal regions. Experiments on local scour in front of groins were made under the actions of tidal currents and waves with clear and sediment entraining water. The scour depths under different dynamic actions are compared. The effect of the distortion ratio on the depth of scour hole is discussed. A relationship between scour depths for distorted and undistorted models is given.展开更多
基金supported by the National Natural Science Foundation of China (Grant No.22278123).
文摘Platinum-based alloy nanoparticles are the most attractive catalysts for the oxygen reduction reaction at present,but an in-depth understanding of the relationship between their short-range structural information and catalytic performance is still lacking.Herein,we present a synthetic strategy that uses transition-metal oxide-assisted thermal diffusion.PtCo/C catalysts with localized tetragonal distortion were obtained by controlling the thermal diffusion process of transition-metal elements.This localized structural distortion induced a significant strain effect on the nanoparticle surface,which further shortened the length of the Pt-Pt bond,improved the electronic state of the Pt surface,and enhanced the performance of the catalyst.PtCo/C catalysts with special short-range structures achieved excellent mass activity(2.27 Amg_(Pt)^(-1))and specific activity(3.34 A cm^(-2)).In addition,the localized tetragonal distortion-induced surface compression of the Pt skin improved the stability of the catalyst.The mass activity decreased by only 13% after 30,000 cycles.Enhanced catalyst activity and excellent durability have also been demonstrated in the proton exchange membrane fuel cell configuration.This study provides valuable insights into the development of advanced Pt-based nanocatalysts and paves the way for reducing noble-metal loading and increasing the catalytic activity and catalyst stability.
基金supported by the National Natural Science Foundation of China(Grant No.61772171)the Major Science and Technology Platform Project of the Normal Universities in Liaoning(Grant No.JP2017005).
文摘Image quality assessment has become increasingly important in image quality monitoring and reliability assuring of image processing systems.Most of the existing no-reference image quality assessment methods mainly exploit the global information of image while ignoring vital local information.Actually,the introduced distortion depends on a slight difference in details between the distorted image and the non-distorted reference image.In light of this,we propose a no-reference image quality assessment method based on a multi-scale convolutional neural network,which integrates both global information and local information of an image.We first adopt the image pyramid method to generate four scale images required for network input and then provide two network models by respectively using two fusion strategies to evaluate image quality.In order to better adapt to the quality assessment of the entire image,we use two different loss functions in the training and validation phases.The superiority of the proposed method is verified by several different experiments on the LIVE datasets and TID2008 datasets.
文摘Five generalized physical models of different distortion ratios were built according to DOU Guo-ren's similarity theory of total sediment transport modeling for estuarine and coastal regions. Experiments on local scour in front of groins were made under the actions of tidal currents and waves with clear and sediment entraining water. The scour depths under different dynamic actions are compared. The effect of the distortion ratio on the depth of scour hole is discussed. A relationship between scour depths for distorted and undistorted models is given.
