Investigations of lead-free multilayer shielding for diagnostic radiology using Monte Carlo simulations

The development of sustainable and lead-free shielding materials is of increasing interest for diagnostic radiology facilities, particularly in low- and middle-income countries where cost, material availability, and environmental considerations are important factors. This study evaluates the radiation shielding performance of fired clay bricks (FCB), concrete, and stainless steel (SS) as alternative structural materials for x-ray facilities operating up to 150 kVp using Monte Carlo simulations with the PHITS code. Mass attenuation coefficients and effective atomic numbers were computed to characterise photon attenuation properties and guide the design of multilayer shielding assemblies. Two concrete-encapsulated assemblies were engineered: a standard composite (C₈-FCB₂₀₀-C₈, 2.32 mm lead equivalent) and a steel-reinforced composite (SS₂-C₈-FCB₂₀₀-C₈, 2.73 lead equivalent). Their performance was benchmarked against a conventional 2 mm lead barrier. Photon flux distributions and effective dose rates (EDR) were evaluated at primary (Cell 20) and secondary (Cells 22, 24, 26) shielding boundaries for x-ray tube potentials ranging from 80 to 150 kVp. At 150 kVp, the lead reference barrier reduced the transmitted EDR to 7.09×10^-09µSv h^-1at the primary barrier and below 1.79×10^-12µSv h^-1at the secondary barriers. A comparative analysis of the EDR recorded behind the alternative barriers reveals that for the secondary barriers, the standard C₈-FCB₂₀₀-C₈configuration was fully adequate across the entire investigated tube voltage range (80-150 kVp). Conversely, for the primary barrier, the reinforced SS₆-C₈-FCB₂₀₀-C₈composite is strictly required to provide sufficient shielding at 150 kVp. These results demonstrate the potential of locally available, lead-free composite materials as cost-effective and environmentally sustainable alternatives for radiation shielding in diagnostic radiology facilities while supporting optimization and ALARA principles.