Monte Carlo investigation and optimization of coincidence prompt gamma-ray neutron activation analysis

Abstract

Normal Prompt Gamma-Ray Neutron Activation Analysis (PGNAA) suffers from a large inherent noise or background. The coincidence PGNAA approach is being investigated for eliminating almost all of the interfering backgrounds and thereby significantly improving the signal-to-noise ratio (SNR). This can be done since almost all of the prompt gamma rays from elements of interest are emitted in coincidence except hydrogen. However, it has been found previously that while the use of two normal NaI detectors greatly reduces the background, the signal is also greatly reduced so that very little improvement in standard deviation is obtained. With the help of MCNP5, the general-purpose Monte Carlo N-Particle code, and CEARCPG, the specific purpose Monte Carlo code for Coincidence PGNAA, further optimization of the proposed coincidence system is being accomplished. The idea pursued here is the use of a large area plastic scintillation detector as the trigger for coincidence events together with a normal large NaI detector. In this approach the detection solid angle is increased greatly, which directly increases the probability of coincidence detection. The 2D-coincidence spectrum obtained can then be projected to the axis representing the NaI detector to overcome the drawback of low energy resolution and photopeak intensity of the plastic scintillation detector and utilize the overall higher coincidence counting rate. To reach the best coincidence detection, the placement of detectors, sample, and the moderator of the neutron source have been optimized through Monte Carlo simulation.