Computational generation of tailored radionuclide libraries for alpha-particle and gamma-ray spectrometry

Radionuclide identification is a radioanalytical method employed in various scientific disciplines that utilize alpha-particle or gamma-ray spectrometric assays, ranging from astrophysics to nuclear medicine. Radionuclide libraries in conventional radionuclide identification systems are crafted in a manual fashion, accompanying laborintensive and error-prone user tasks and hindering library customization. This research presents a computational algorithm and the architecture of its dedicated software that can automatically generate tailored radionuclide libraries. Progenitor-progeny recurrence relations were modeled to enable recursive computation of radionuclide subsets. This theoretical concept was incorporated into open-source software called RECURLIB and validated against four actinide decay series and 12 radioactive substances, including a uranium-glazed legacy Fiestaware, natural uranium and thorium sources, a 226Ra sample, and the medical radionuclides 225Ac, 177Lu, and 99mTc. The developed algorithm yielded radionuclide libraries for all the tested specimens within minutes, demonstrating its efficiency and applicability across diverse scenarios. The proposed approach introduces a framework for computerized radionuclide library generation, thereby trivializing library-driven radionuclide identification and facilitating the spectral recognition of unregistered radionuclides in radiation spectrometry.