2026-10-12T11:52:16Z https://www.scidb.cn/oai

10.57760/sciencedb.j00213.00197 2025-11-19T14:04:53Z

2025-11-19 Neutron capture cross-section measurement and extraction of neutron resonance parameters at 1–500 eV for 109Ag doi:10.57760/sciencedb.j00213.00197 en This work conducted neutron capture cross-section experiments on 109Ag isotope targets using a white light neutron source from the Chinese Spallation Neutron Source. By combining neutron flight time method and pulse height weighting technique, the neutron capture cross-section of 109Ag in the energy range of 1-500 eV was obtained. The resonance energy, neutron resonance width, and gamma resonance width parameters of 109Ag were extracted using the SAMMY program based on the R-matrix theory. This dataset includes a flowchart for obtaining resonance parameters, namely the graph methodology, as shown in Figure 2 of this article; The normalized counting table is the data obtained by normalizing the pulse height spectra of each target using a Li Si detector, as shown in Figures 4 and 5 of this article; Table detection efficiency refers to the detector detection efficiency before and after weighted counting using pulse height, as shown in Figure 6 of this article; Table fc shows the relationship between the simulated neutron to target thickness ratio and neutron energy variation, as shown in Figure 7 of this article; Table 109Ag cross-sectional data refers to the neutron capture cross-sectional data obtained experimentally, which is the data for This Work in Figure 8 of this article; The table resonance parameters refer to the 109Ag resonance parameter data extracted from the SAMMY program, which is the data for This Work in Table 3 of this article.  resonnance parameter; neutron capture cross-section; pulse height weighting technique xie wen Che Guoliang Jiang Wei Dong Gaoyang Weng Chuxuan Jiang Xin Li Xinxiang Feng Song Jiang Bing Ren Jie Lin Ziang Yin Mingyang Jiang Ting He Rui Wang Hongwei Fan Gongtao Liu Longxiang Zhang Yue Hao Zirui Zhang Suya Latu Wang Dexin Luo Wen PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset http://www.doi.org/10.7498/aps.75.20251270 Science Data Bank