Nuclear Science & Technology Research Institute

Effective radiation shielding is crucial in protecting against neutron and gamma radiation in nuclear facilities and medical radiol.This study aims to develop and evaluate Bisphenol A (BPA)-based composite shields infused with neutron-absorbing and gamma-attenuating fillers, including boron carbide (B₄C), boron nitride (BN), gadolinium oxide (Gd₂O₃) and bismuth oxide (Bi₂O₃).Shielding performance was evaluated through a combination of theor. calculations, Monte Carlo N-Particle (MCNP) simulations, and exptl. measurements.BPA-based shielding materials containing 5%, 10%, 20%, 30%, and 40% concentrations of B, Bi, and Gd additives were assessed for key shielding parameters, including d., fast neutron removal cross-section (∑_R), Half-Value Layer (HVL), Mean Free Path (MFP), and gamma attenuation coefficient (μ).Exptl. measurements were conducted using an Am-Be neutron-gamma source, with neutron and gamma discrimination ensured through a digital detection system.Addnl., the structural properties of the composites were characterized using SEM with Energy-Dispersive X-ray spectroscopy (SEM-EDX) and stress-strain anal. to evaluate their mech. performance.Exptl. densities matched theor. predictions, confirming fabrication reliability.Shields with higher additive concentrations exhibited improved attenuation.Exptl. measurements using the Digital Neutron-Gamma Discrimination system revealed that the B₄C/BPA-30 composite (containing 30 wt% boron) achieved a half-value layer (HVL) of 5.353 cm and a mean free path (MFP) of 7.812 cm for fast neutrons.Among the tested materials, Bi₂O₃/BPA composites exhibited the most effective neutron shielding performance.For gamma radiation, Gd₂O₃/BPA composites exhibited the highest attenuation efficiency.Specifically, the Gd₂O₃/BPA-5 sample achieved the maximum mass attenuation coefficient (μ/ρ) of 0.0291 cm²/g and linear attenuation coefficient (μ) of 0.0335 cm^-1, highlighting its superior performance in gamma radiation fields.BPA-based composites demonstrated good performance compared to conventional borated polyethylene, especially at higher additive concentrationsBy adjusting the type and concentration of additives, these composites offer customizable shielding properties suited to specific radiation environments.The results showed strong agreement between exptl. measurements, theor. calculations, and simulation outcomes.At an equal additive concentration of 5%, Gd₂O₃/BPA-5 and Bi₂O₃/BPA-5 composites exhibited outstanding attenuation capabilities, making them particularly effective for shielding in mixed fast neutron and gamma radiation fields.BPA-based composite shields are customizable and effective solutions for radiation attenuation, with significant potential for applications in nuclear safety, medical radiol., and radiation detection systems.Future work will focus on enhancing filler distribution, long-term stability, and incorporating high-performance additives for optimized shielding.

Owning catalytical active Zr^IV-OH sites, prototypical Zirconium-based metal-organic framework, UIO-66 emulate the phosphotriesterase enzyme action, indicating promising activity in catalytic hydrolysis of organophosphorus nerve agents.Herein, a solid-phase fabrication of plasma-defected UIO-66 (P-UIO-66) was presented based on dielec. barrier discharge plasma, for enhanced catalytic hydrolysis of dimethyl-4-nitrophenyl phosphate (DMNP), as a well-known nerve agent simulant.Plasma treatment was carried out using atm. air instead of any inert gas (Ar/He) for only up to 4 min, which is shorter than previously reported 30 min.Various plasma parameters were optimized to improve the catalytic activity of P-UIO-66.Interestingly, an amazing improvement in the hydrolysis rate of DMNP was achieved with the P-UIO-66 catalyst, increasing the hydrolysis efficiency more than 2.3-fold compared to pristine UIO-66.The conversion % of DMNP under hydrolysis catalyzed by P-UIO-66 was obtained as high as 68 %, while a negligible destruction of DMNP (30 %) was obtained with pristine UIO-66.Addnl., the half-life time (t_1/2) of DMNP for the hydrolysis catalyzed by P-UIO-66 (t_1/2 = 11.3) was obtained to be lower than of that for pristine UIO-66 (t_1/2 = 15.7) under the same conditions.According to exptl. results, surface activation of P-UIO-66 is regulated by voltage, inter-electrode distance, and time of plasma irradiation, which leads to optimize the accessibility of catalytically active Zr^IV sites for DMNP.This study introduces the plasma-based modification strategy as a novel green PSM approach for enhancing catalytic activity of MOF-based catalysts for environmental-related applications.

A promising material used in radiation synovectomy of small joints is hydroxyapatite, labeled with 177Lu. During the design and production of radiopharmaceuticals, the condition of the radiolabeling process directly influences the radiochemical yield and consequently the quality of the final product so this process necessitates precise optimization.

In this investigation, a central composite design based on response surface methodology and artificial neural networks modeling coupled with genetic algorithm technique is applied to build predictive models and explore key parameters' effect in hydroxyapatite's radiolabeling process with 177Lu radionuclide. The variables that directly affected the labeling reaction were the initial 177Lu radioactivity, pH, radiolabeling reaction time, and temperature.

Based on the validation data set, the statistical values demonstrate that the artificial neural networks model performs better than the response surface methodology model. The artificial neural networks model has a small mean squared error (9.08 artificial neural networks < 12.36 response surface methodology) and a high coefficient of determination (R2: 0.99 artificial neural networks > 0.93 response surface methodology). The optimum conditions to achieve maximum radiochemical yield based on response surface methodology using artificial neural networks modeling coupled with genetic algorithm were at the initial radioactivity of 177Lu radionuclide = 0.082 Gigabecquerel (GBq), pH = 6.75, time= 22 (min), and temperature = 37.8 (oC)

The ability to generate more data with fewer experiments for optimization and improved production is a pertinent advantage of multivariate optimization methods over traditional methods in radiation-related activities. The central composite design and artificial neural network- genetic algorithm optimization approaches are successfully utilized to create prediction models and investigate the impact of critical variables in the radiolabeling of hydroxyapatite with 177Lu radionuclide.