Haze in China is primarily caused by high pollution of atmospheric fine particulates（PM2.5）.However, the detailed source structures of PM2.5 light extinction have not been well established, especially for the roles ...Haze in China is primarily caused by high pollution of atmospheric fine particulates（PM2.5）.However, the detailed source structures of PM2.5 light extinction have not been well established, especially for the roles of various organic aerosols, which makes haze management lack specified targets. This study obtained the mass concentrations of the chemical compositions and the light extinction coefficients of fine particles in the winter in Dongguan, Guangdong Province, using high time resolution aerosol observation instruments. We combined the positive matrix factor（PMF） analysis model of organic aerosols and the multiple linear regression method to establish a quantitative relationship model between the main chemical components, in particular the different sources of organic aerosols and the extinction coefficients of fine particles with a high goodness of fit（R^2= 0.953）. The results show that the contribution rates of ammonium sulphate,ammonium nitrate, biomass burning organic aerosol（BBOA）, secondary organic aerosol（SOA） and black carbon（BC） were 48.1%, 20.7%, 15.0%, 10.6%, and 5.6%, respectively. It can be seen that the contribution of the secondary aerosols is much higher than that of the primary aerosols（79.4% versus 20.6%） and are a major factor in the visibility decline. BBOA is found to have a high visibility destroying potential, with a high mass extinction coefficient, and was the largest contributor during some high pollution periods. A more detailed analysis indicates that the contribution of the enhanced absorption caused by BC mixing state was approximately 37.7% of the total particle absorption and should not be neglected.展开更多
In the present study, graphene photonic crystals are employed to enhance the light extraction efficiency（LEE） of two-color, red and blue, light-emitting diode（LED）. The transmission characteristics of one-dimensio...In the present study, graphene photonic crystals are employed to enhance the light extraction efficiency（LEE） of two-color, red and blue, light-emitting diode（LED）. The transmission characteristics of one-dimensional（1D） Fibonacci graphene photonic crystal LED（FGPC-LED） are investigated by using the transfer matrix method and the scaling study is presented. We analyzed the influence of period, thickness, and permittivity in the structure to enhance the LEE. The transmission spectrum of 1D FGPC has been optimized in detail. In addition, the effects of the angle of incidence and the state of polarization are investigated. As the main result, we found the optimum values of relevant parameters to enhance the extraction of red and blue light from an LED as well as provide perfect omnidirectional and high peak transmission filters for the TE and TM modes.展开更多
In this article, we calculate the contribution from the nonfactorizable soft hadronic matrix element to the decay B^0→Xc1π^0 with the light-cone quantum chromo-dynamic （QCD） sum rules. The numerical results show t...In this article, we calculate the contribution from the nonfactorizable soft hadronic matrix element to the decay B^0→Xc1π^0 with the light-cone quantum chromo-dynamic （QCD） sum rules. The numerical results show that its contribution is rather large and should not be neglected. The total amplitudes lead to a branching fraction which is in agreement with the experimental data marginally.展开更多
High-quality optical components have been widely used in various applications;thus,extremely high beam quality is required.Moreover,surface roughness is a key indicator of the surface quality.In this study,the angular...High-quality optical components have been widely used in various applications;thus,extremely high beam quality is required.Moreover,surface roughness is a key indicator of the surface quality.In this study,the angular distribution of light scattering field intensity was obtained for surfaces having different roughness profiles based on the finite difference time domain(FDTD)method,and the results were compared with those obtained using the generalized Harvey-Shack(GHS)theory.It was shown that the FDTD approach can be used for an accurate simulation of the scattered field of a rough surface,and the superposition of results obtained from many surfaces that have the same roughness level was in good agreement with the result given by the analytic GHS model.A light scattering matrix(LSM)method was proposed based on the FDTD simulation results that could obtain rich surface roughness information.The classification effect of LSM was compared with that of the single-incidence scattering distribution(SISD)based on a ResNet-50 deep learning network.The classification accuracy of the model trained with the LSM dataset was obtained as 95.74%,which was 23.40%higher than that trained using the SISD dataset.Moreover,the effects of different noise types and filtering methods on the classification performance were analyzed,and the LSM was also shown to improve the robustness and generalizability of the trained surface roughness classifier.Overall,the proposed LSM method has important implications for improving the data acquisition scheme of current light scattering measurement systems,and it also has the potential to be used for detection and characterization of surface defects of optical components.展开更多
基金supported by the National Natural Science Foundation of China(Nos.41622304,U1301234)the Ministry of Science and Technology of China(Nos.2014BAC21B03,2016YFC0203600)the Science and Technology Plan of Shenzhen Municipality
文摘Haze in China is primarily caused by high pollution of atmospheric fine particulates（PM2.5）.However, the detailed source structures of PM2.5 light extinction have not been well established, especially for the roles of various organic aerosols, which makes haze management lack specified targets. This study obtained the mass concentrations of the chemical compositions and the light extinction coefficients of fine particles in the winter in Dongguan, Guangdong Province, using high time resolution aerosol observation instruments. We combined the positive matrix factor（PMF） analysis model of organic aerosols and the multiple linear regression method to establish a quantitative relationship model between the main chemical components, in particular the different sources of organic aerosols and the extinction coefficients of fine particles with a high goodness of fit（R^2= 0.953）. The results show that the contribution rates of ammonium sulphate,ammonium nitrate, biomass burning organic aerosol（BBOA）, secondary organic aerosol（SOA） and black carbon（BC） were 48.1%, 20.7%, 15.0%, 10.6%, and 5.6%, respectively. It can be seen that the contribution of the secondary aerosols is much higher than that of the primary aerosols（79.4% versus 20.6%） and are a major factor in the visibility decline. BBOA is found to have a high visibility destroying potential, with a high mass extinction coefficient, and was the largest contributor during some high pollution periods. A more detailed analysis indicates that the contribution of the enhanced absorption caused by BC mixing state was approximately 37.7% of the total particle absorption and should not be neglected.
文摘In the present study, graphene photonic crystals are employed to enhance the light extraction efficiency（LEE） of two-color, red and blue, light-emitting diode（LED）. The transmission characteristics of one-dimensional（1D） Fibonacci graphene photonic crystal LED（FGPC-LED） are investigated by using the transfer matrix method and the scaling study is presented. We analyzed the influence of period, thickness, and permittivity in the structure to enhance the LEE. The transmission spectrum of 1D FGPC has been optimized in detail. In addition, the effects of the angle of incidence and the state of polarization are investigated. As the main result, we found the optimum values of relevant parameters to enhance the extraction of red and blue light from an LED as well as provide perfect omnidirectional and high peak transmission filters for the TE and TM modes.
基金supported by the National Natural Science Foundation of China (Grant No 10775051)the Program for New Century Excellent Talents in University of China (Grant No NCET-07-0282)
文摘In this article, we calculate the contribution from the nonfactorizable soft hadronic matrix element to the decay B^0→Xc1π^0 with the light-cone quantum chromo-dynamic （QCD） sum rules. The numerical results show that its contribution is rather large and should not be neglected. The total amplitudes lead to a branching fraction which is in agreement with the experimental data marginally.
基金supported by the National Key R&D Program of China(Grant No.2020YFB1710400)the Key R&D Project of Hubei Province(Grant No.2023BAB067)。
文摘High-quality optical components have been widely used in various applications;thus,extremely high beam quality is required.Moreover,surface roughness is a key indicator of the surface quality.In this study,the angular distribution of light scattering field intensity was obtained for surfaces having different roughness profiles based on the finite difference time domain(FDTD)method,and the results were compared with those obtained using the generalized Harvey-Shack(GHS)theory.It was shown that the FDTD approach can be used for an accurate simulation of the scattered field of a rough surface,and the superposition of results obtained from many surfaces that have the same roughness level was in good agreement with the result given by the analytic GHS model.A light scattering matrix(LSM)method was proposed based on the FDTD simulation results that could obtain rich surface roughness information.The classification effect of LSM was compared with that of the single-incidence scattering distribution(SISD)based on a ResNet-50 deep learning network.The classification accuracy of the model trained with the LSM dataset was obtained as 95.74%,which was 23.40%higher than that trained using the SISD dataset.Moreover,the effects of different noise types and filtering methods on the classification performance were analyzed,and the LSM was also shown to improve the robustness and generalizability of the trained surface roughness classifier.Overall,the proposed LSM method has important implications for improving the data acquisition scheme of current light scattering measurement systems,and it also has the potential to be used for detection and characterization of surface defects of optical components.
