Simulation-Driven Framework Optimizes Signal-to-Noise Ratio in Elemental Analysis, Enhancing Accuracy.
Prompt Gamma Neutron Activation Analysis (PGNAA) based on compact, high-yield deuterium–deuterium (D–D) neutron generators holds significant promise for on-site quantitative elemental analysis. However, while the intense neutron flux enhances signal yield, it also produces substantial increased background, resulting in a low signal-to-noise ratio that compromises analytical accuracy. To address these issues, a simulation-driven optimization framework was developed using the TopMC Monte Carlo code and experimentally validated to maximize the signal-to-noise ratio. This was used to optimize the design of a multi-component shielding and collimation system, comprising an optimized borated polyethylene (BPE) moderator, an inverted-conical neutron collimator, and a lithium fluoride–polyethylene composite shield surrounding the LaBr 3 (Ce) detector, effectively suppressing thermal neutron-induced background. Additionally, a hydrogen-based internal standard method was implemented to correct for neutron self-shielding in liquid samples. Using a D–D neutron generator with an average yield of ∼7 × 10 9 n/s, highly linear calibration curves were achieved for cadmium and chlorine in aqueous solutions (R 2 = 0.998 and 0.9917, respectively), with minimum detectable concentrations of 0.024 ± 0.007 g/L for Cd and 0.85 ± 0.26 g/L for Cl. Moreover, the optimized inverted-conical collimator is compatible with neutron imaging systems, paving the way for future integration of PGNAA and neutron imaging technologies.
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Li et al. (2026) studied this question.
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