A novel concept and approach to engineering carbon nanodots(CNDs)were explored to overcome the limited light absorption of CNDs in low-energy spectral regions.In this work,we constructed a novel type of supra-CND by t...A novel concept and approach to engineering carbon nanodots(CNDs)were explored to overcome the limited light absorption of CNDs in low-energy spectral regions.In this work,we constructed a novel type of supra-CND by the assembly of surface charge-confined CNDs through possible electrostatic interactions and hydrogen bonding.The resulting supra-CNDs are the first to feature a strong,well-defined absorption band in the visible to near-infrared(NIR)range and to exhibit effective NIR photothermal conversion performance with high photothermal conversion efficiency in excess of 50%.展开更多
The accurate acquisition of the grain crop planting area is a necessary condition for realizing precision agriculture.UAV remote sensing has the advantages of low cost use,simple operation,real-time acquisition of rem...The accurate acquisition of the grain crop planting area is a necessary condition for realizing precision agriculture.UAV remote sensing has the advantages of low cost use,simple operation,real-time acquisition of remote sensor images and high ground resolution.It is difficult to separate cultivated land from other terrain by using only a single feature,making it necessary to extract cultivated land by combining various features and hierarchical classification.In this study,the UAV platform was used to collect visible light remote sensing images of farmland to monitor and extract the area information,shape information and position information of farmland.Based on the vegetation index,texture information and shape information in the visible light band,the object-oriented method was used to study the best scheme for extracting cultivated land area.After repeated experiments,it has been determined that the segmentation scale 50 and the consolidation scale 90 are the most suitable segmentation parameters.Uncultivated crops and other features are separated by using the band information and texture information.The overall accuracy of this method is 86.40%and the Kappa coefficient is 0.80.The experimental results show that the UAV visible light remote sensing data can be used to classify and extract cultivated land with high precision.However,there are some cases where the finely divided plots are misleading,so further optimization and improvement are needed.展开更多
In order to obtain a metasurface structure capable of filtering light of a specific wavelength range in the visible band,the traditional methods usually traverse the space consisting of possible designs,searching for ...In order to obtain a metasurface structure capable of filtering light of a specific wavelength range in the visible band,the traditional methods usually traverse the space consisting of possible designs,searching for a potenti ally satisfactory structure by performing iterative calculations to solve Maxwell's equations.In this article,we propose a systematic method based on neural networks that can complete an inverse design process to solve the problem.Compared with the traditional methods,our method is much faster while competent to encom-pass a high degree of freedom to generate device structures,which can ensure that the spectra of generated structures resemble the desired ones.展开更多
基金supported by the National Science Foundation of China(No.11204298,61205025,61274126 and 61306081)the Jilin Province Science and Technology Research Project(No.20140101060JC,20150519003JH and 20130522142JH)the Outstanding Young Scientist Program of CAS.
文摘A novel concept and approach to engineering carbon nanodots(CNDs)were explored to overcome the limited light absorption of CNDs in low-energy spectral regions.In this work,we constructed a novel type of supra-CND by the assembly of surface charge-confined CNDs through possible electrostatic interactions and hydrogen bonding.The resulting supra-CNDs are the first to feature a strong,well-defined absorption band in the visible to near-infrared(NIR)range and to exhibit effective NIR photothermal conversion performance with high photothermal conversion efficiency in excess of 50%.
基金We acknowledge that this research work was financially supported by the Leading Talents of Guangdong Province Program(Project No.2016LJ06G689)Educational Commission of Guangdong Province of China for Platform(Project No.2015KGJHZ007)+1 种基金Science and Technology Planning Project of Guangdong Province(Project No.2017B010117010)China Agriculture Research System(Project No.CARS-15-22)。
文摘The accurate acquisition of the grain crop planting area is a necessary condition for realizing precision agriculture.UAV remote sensing has the advantages of low cost use,simple operation,real-time acquisition of remote sensor images and high ground resolution.It is difficult to separate cultivated land from other terrain by using only a single feature,making it necessary to extract cultivated land by combining various features and hierarchical classification.In this study,the UAV platform was used to collect visible light remote sensing images of farmland to monitor and extract the area information,shape information and position information of farmland.Based on the vegetation index,texture information and shape information in the visible light band,the object-oriented method was used to study the best scheme for extracting cultivated land area.After repeated experiments,it has been determined that the segmentation scale 50 and the consolidation scale 90 are the most suitable segmentation parameters.Uncultivated crops and other features are separated by using the band information and texture information.The overall accuracy of this method is 86.40%and the Kappa coefficient is 0.80.The experimental results show that the UAV visible light remote sensing data can be used to classify and extract cultivated land with high precision.However,there are some cases where the finely divided plots are misleading,so further optimization and improvement are needed.
文摘In order to obtain a metasurface structure capable of filtering light of a specific wavelength range in the visible band,the traditional methods usually traverse the space consisting of possible designs,searching for a potenti ally satisfactory structure by performing iterative calculations to solve Maxwell's equations.In this article,we propose a systematic method based on neural networks that can complete an inverse design process to solve the problem.Compared with the traditional methods,our method is much faster while competent to encom-pass a high degree of freedom to generate device structures,which can ensure that the spectra of generated structures resemble the desired ones.
