We present new data on the^(63)Cu(γ,n)cross-section studied using a quasi-monochromatic and energy-tunableγbeam produced at the Shanghai Laser Electron Gamma Source to resolve the long-standing discrepancy between e...We present new data on the^(63)Cu(γ,n)cross-section studied using a quasi-monochromatic and energy-tunableγbeam produced at the Shanghai Laser Electron Gamma Source to resolve the long-standing discrepancy between existing measurements and evaluations of this cross-section.Using an unfolding iteration method,^(63)Cu(γ,n)data were obtained with an uncertainty of less than 4%,and the inconsistencies between the available experimental data were discussed.Theγ-ray strength function of^(63)Cu(γ,n)was successfully extracted as an experimental constraint.We further calculated the cross-section of the radiative neutron capture reaction^(62)Cu(n,γ)using the TALYS code.Our calculation method enables the extraction of(n,γ)cross-sections for unstable nuclides.展开更多
In this study,an end-to-end deep learning method is proposed to improve the accuracy of continuum estimation in low-resolution gamma-ray spectra.A novel process for generating the theoretical continuum of a simulated ...In this study,an end-to-end deep learning method is proposed to improve the accuracy of continuum estimation in low-resolution gamma-ray spectra.A novel process for generating the theoretical continuum of a simulated spectrum is established,and a convolutional neural network consisting of 51 layers and more than 105 parameters is constructed to directly predict the entire continuum from the extracted global spectrum features.For testing,an in-house NaI-type whole-body counter is used,and 106 training spectrum samples(20%of which are reserved for testing)are generated using Monte Carlo simulations.In addition,the existing fitting,step-type,and peak erosion methods are selected for comparison.The proposed method exhibits excellent performance,as evidenced by its activity error distribution and the smallest mean activity error of 1.5%among the evaluated methods.Additionally,a validation experiment is performed using a whole-body counter to analyze a human physical phantom containing four radionuclides.The largest activity error of the proposed method is−5.1%,which is considerably smaller than those of the comparative methods,confirming the test results.The multiscale feature extraction and nonlinear relation modeling in the proposed method establish a novel approach for accurate and convenient continuum estimation in a low-resolution gamma-ray spectrum.Thus,the proposed method is promising for accurate quantitative radioactivity analysis in practical applications.展开更多
基金supported by the National Key Research and Development Program(Nos.2023YFA1606901 and 2022YFA1602400)National Natural Science Foundation of China(Nos.U2230133,12275338,and 12388102)Open Fund of the CIAE Key Laboratory of Nuclear Data(No.JCKY2022201C152).
文摘We present new data on the^(63)Cu(γ,n)cross-section studied using a quasi-monochromatic and energy-tunableγbeam produced at the Shanghai Laser Electron Gamma Source to resolve the long-standing discrepancy between existing measurements and evaluations of this cross-section.Using an unfolding iteration method,^(63)Cu(γ,n)data were obtained with an uncertainty of less than 4%,and the inconsistencies between the available experimental data were discussed.Theγ-ray strength function of^(63)Cu(γ,n)was successfully extracted as an experimental constraint.We further calculated the cross-section of the radiative neutron capture reaction^(62)Cu(n,γ)using the TALYS code.Our calculation method enables the extraction of(n,γ)cross-sections for unstable nuclides.
基金supported by the National Natural Science Foundation of China(No.12005198).
文摘In this study,an end-to-end deep learning method is proposed to improve the accuracy of continuum estimation in low-resolution gamma-ray spectra.A novel process for generating the theoretical continuum of a simulated spectrum is established,and a convolutional neural network consisting of 51 layers and more than 105 parameters is constructed to directly predict the entire continuum from the extracted global spectrum features.For testing,an in-house NaI-type whole-body counter is used,and 106 training spectrum samples(20%of which are reserved for testing)are generated using Monte Carlo simulations.In addition,the existing fitting,step-type,and peak erosion methods are selected for comparison.The proposed method exhibits excellent performance,as evidenced by its activity error distribution and the smallest mean activity error of 1.5%among the evaluated methods.Additionally,a validation experiment is performed using a whole-body counter to analyze a human physical phantom containing four radionuclides.The largest activity error of the proposed method is−5.1%,which is considerably smaller than those of the comparative methods,confirming the test results.The multiscale feature extraction and nonlinear relation modeling in the proposed method establish a novel approach for accurate and convenient continuum estimation in a low-resolution gamma-ray spectrum.Thus,the proposed method is promising for accurate quantitative radioactivity analysis in practical applications.
