Gamma-Ray Spectral Unfolding of CdZnTe-Based Detectors Using a Genetic Algorithm

Area of Science:

• Nuclear Physics
• Radiation Detection and Measurement

Background:

• Gamma-ray spectral analysis using semiconductor detectors is challenging due to distortions and artifacts.
• Accurate spectral shape restoration is crucial for identifying radioisotopes and quantifying radiation.
• Room temperature semiconductor detectors, like CdZnTe, offer portability but present unique analysis hurdles.

Discussion:

• A novel genetic algorithm was developed for gamma-ray spectral unfolding.
• The algorithm effectively corrects for instrumental distortions and artifacts in the spectra.
• This approach aims to recover the true energy distribution of incident gamma radiation.

Key Insights:

• The genetic algorithm successfully unfolded experimental gamma-ray spectra from four radionuclides (241Am, 57Co, 137Cs, 133Ba).
• Validation was performed using CdZnTe detectors with single pixel and drift strip geometries.
• Unfolded spectra revealed sharp, delta-like peaks corresponding to specific radioisotope emissions, demonstrating high resolution.

Outlook:

• This method enhances the reliability of gamma-ray spectroscopy with semiconductor detectors.
• Future applications include improved nuclear material identification and environmental radiation monitoring.
• Further optimization of the genetic algorithm could extend its applicability to more complex spectral analysis scenarios.