Generation of Proton- and Alpha-Induced Nuclear Cross-Section Data via Random Forest Algorithm: Production of Radionuclide <sup>111</sup>In
2021
Mohamad Amin Bin Hamid | Hoe Guan Beh | Yusuff Afeez Oluwatobi | Xiao Yan Chew | Saba Ayub
We investigated the generation of proton- and alpha-induced nuclear cross-section data in the production of Indium-111 (<sup>111</sup>In) for application in nuclear medicine. Here, we are interested in three reaction channels, which are <sup>109</sup>Ag (α, 2n), <sup>111</sup>Cd (p, n) and <sup>112</sup>Cd (p, 2n), in the production of <sup>111</sup>In. A random forest algorithm was used to generate nuclear cross-section data by using an experimental nuclear cross-section from the Experimental Nuclear Reaction Data (EXFOR) database as input. Hence, reasonably accurate regression curves of nuclear cross-section data could be produced with the evaluated nuclear data library ENDF/B-VII.0 set as the benchmark.
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