A study of single-electron capture(SEC) in 18-240 keV O^(6+)-Ne collisions has been conducted employing a combination of experimental and theoretical methodologies.Utilizing a reaction microscope,state-selective SEC c...A study of single-electron capture(SEC) in 18-240 keV O^(6+)-Ne collisions has been conducted employing a combination of experimental and theoretical methodologies.Utilizing a reaction microscope,state-selective SEC cross sections and projectile scattering angle distributions were obtained.The translational energy spectra for SEC reveal the prevailing capture into n=3 states of the projectile ion,with a minor contribution from n=4 states.Notably,as the projectile's energy increases,the relative contribution of SEC n=4 states increases while that of SEC n=3 states diminishes.Furthermore,we computed state-selective relative cross sections and angular differential cross sections employing the classical molecular Coulomb over-the-barrier model(MCBM) and the multichannel Landau-Zener(MCLZ) model.A discernible discrepancy between the state-selective cross sections from the two theoretical models is apparent for the considered impact energies.However,regarding the angular differential cross sections,an overall agreement was attained between the current experimental results and the theoretical results from the MCLZ model.展开更多
Recent work has validated a new method for estimating the grain size of microgranular materials in the range of tens to hundreds of micrometers using laser-induced breakdown spectroscopy(LIBS).In this situation,a piec...Recent work has validated a new method for estimating the grain size of microgranular materials in the range of tens to hundreds of micrometers using laser-induced breakdown spectroscopy(LIBS).In this situation,a piecewise univariate model must be constructed to estimate grain size due to the complex dependence of the plasma formation environment on grain size.In the present work,we tentatively construct a unified calibration model suitable for LIBS-based estimation of those grain sizes.Specifically,two unified multivariate calibration models are constructed based on back-propagation neural network(BPNN)algorithms using feature selection strategies with and without considering prior information.By detailed analysis of the performances of the two multivariate models,it was found that a unified calibration model can be successfully constructed based on BPNN algorithms for estimating the grain size in the range of tens to hundreds of micrometers.It was also found that the model constructed with a priorguided feature selection strategy had better prediction performance.This study has practical significance in developing the technology for material analysis using LIBS,especially when the LIBS signal exhibits a complex dependence on the material parameter to be estimated.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant Nos.11934004,12064040,and 11974358)the National Key Research and Development Program of China(Grant No.2022YFA1602500)Strategic Key Research Program of the Chinese Academy of Sciences(Grant No.XDB34020000)。
文摘A study of single-electron capture(SEC) in 18-240 keV O^(6+)-Ne collisions has been conducted employing a combination of experimental and theoretical methodologies.Utilizing a reaction microscope,state-selective SEC cross sections and projectile scattering angle distributions were obtained.The translational energy spectra for SEC reveal the prevailing capture into n=3 states of the projectile ion,with a minor contribution from n=4 states.Notably,as the projectile's energy increases,the relative contribution of SEC n=4 states increases while that of SEC n=3 states diminishes.Furthermore,we computed state-selective relative cross sections and angular differential cross sections employing the classical molecular Coulomb over-the-barrier model(MCBM) and the multichannel Landau-Zener(MCLZ) model.A discernible discrepancy between the state-selective cross sections from the two theoretical models is apparent for the considered impact energies.However,regarding the angular differential cross sections,an overall agreement was attained between the current experimental results and the theoretical results from the MCLZ model.
基金supported in part by the National Key Research and Development Program of China(No.2017YFA0402300)National Natural Science Foundation of China(Nos.U2241288 and 11974359)Major Science and Technology Project of Gansu Province(No.22ZD6FA021-5)。
文摘Recent work has validated a new method for estimating the grain size of microgranular materials in the range of tens to hundreds of micrometers using laser-induced breakdown spectroscopy(LIBS).In this situation,a piecewise univariate model must be constructed to estimate grain size due to the complex dependence of the plasma formation environment on grain size.In the present work,we tentatively construct a unified calibration model suitable for LIBS-based estimation of those grain sizes.Specifically,two unified multivariate calibration models are constructed based on back-propagation neural network(BPNN)algorithms using feature selection strategies with and without considering prior information.By detailed analysis of the performances of the two multivariate models,it was found that a unified calibration model can be successfully constructed based on BPNN algorithms for estimating the grain size in the range of tens to hundreds of micrometers.It was also found that the model constructed with a priorguided feature selection strategy had better prediction performance.This study has practical significance in developing the technology for material analysis using LIBS,especially when the LIBS signal exhibits a complex dependence on the material parameter to be estimated.
