MDA reduction in HPGe gamma-ray spectrometry using a digital-twin-based intrinsic background construction

Area of Science:

• Nuclear Physics
• Analytical Chemistry
• Environmental Science

Background:

• High-purity germanium (HPGe) spectrometry for radioactive waste analysis is hindered by background uncertainty, especially Compton continua.
• Current methods like side-window interpolation lead to high minimum detectable activities (MDAs) and uncertain peak identification.

Purpose of the Study:

• To develop a digital-twin framework for constructing intrinsic background spectra with controlled statistical uncertainty.
• To improve radionuclide determination accuracy and lower detection limits in radioactive waste characterization.

Main Methods:

• Utilized Geant4 Monte Carlo simulations to generate high-statistical-depth background contributions in list-mode.
• Reconstructed intrinsic background spectra for various activities via virtual-time post-processing of event-level data.
• Validated the framework using a certified reference material and applied it to real radioactive waste samples.

Main Results:

• Achieved MDA reductions of 46-75% compared to conventional methods.
• Enabled quantitative recovery of previously undetectable radionuclides, such as ⁹⁴Nb.
• Demonstrated objective rejection of false-positive peaks by reconstructing physical continua.

Conclusions:

• Radionuclide detectability is primarily limited by background uncertainty, not its magnitude.
• The digital-twin approach offers a practical method for enhancing characteristic limits and reliability in radioactive waste analysis.
• This framework allows independent suppression of background uncertainties without increasing physical counting time.