Simultaneous alpha and gamma discrimination with a phoswich detector using a rise time method and an artificial...

Area of Science:

• Nuclear Instrumentation
• Radiation Detection and Measurement

Background:

• Phoswich detectors are crucial for differentiating radiation types.
• Digital signal processing offers advanced methods for radiation discrimination.

Purpose of the Study:

• To compare the effectiveness of rise time discrimination (RTD) and artificial neural networks (ANN) for simultaneous alpha and gamma ray discrimination.
• To evaluate the performance of these methods using a phoswich detector.

Main Methods:

• Utilized a phoswich detector (50 μm BC-400 coupled to 3 mm CsI(Tl)).
• Employed digital methods: rise time discrimination (RTD) and artificial neural network (ANN) analysis.
• Extracted pulse features (rise time, pulse height ratio, charge ratio) for ANN training.

Main Results:

• RTD showed a broad rise time distribution for gamma rays (200-800 ns) and alpha particles (<40 ns).
• ANN achieved significantly better discrimination performance compared to RTD.
• Spectroscopy with 137Cs and 241Am sources confirmed ANN suitability for discrimination.

Conclusions:

• Artificial neural networks provide a more effective method for discriminating alpha particles and gamma rays with phoswich detectors.
• The ANN approach offers improved accuracy and performance in radiation detection applications.