  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 labor-intensive 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 twelve radioactive substances, including
a uranium-glazed legacy Fiestaware, natural uranium and thorium sources, a
$^{226}$Ra sample, and the medical radionuclides $^{225}$Ac, $^{177}$Lu, and
$^{99\text{m}}$Tc. 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.
