Journal of Radioanalytical and Nuclear Chemistry最新文献

A unique approach to remotely quantify Cm(III) (0–100 µg mL^− 1) in HNO₃ (1–12 M) using steady-state laser fluorescence spectroscopy and multivariate regression models was developed. Photoluminescence is amenable to remote measurements using fiber-optic cables and is sensitive to numerous lanthanide and actinide species. In-line measurements can provide feedback to support complex processing in harsh environments (e.g., hot cells) to help guide and optimize radiochemical separations. In this work, Cm(III) spectra were acquired remotely in a glove box as a function of HNO₃ concentration to better understand spectral characteristics and evaluate the utility of multivariate regression models in this system. The Cm(III) fluorescence peak shape, width, position, and intensity changed significantly as a function of HNO₃ concentration, likely because of the displacement of emission quenching inner-sphere water molecules and complexation with nitrate ions. Despite significant covariance and nonlinearity in the data, a D-optimal design strategy successfully minimized training set sample size and was used to build effective partial least squares regression models for Cm(III) and HNO₃ concentrations without a priori knowledge of solution conditions. Chemometrics for modeling complex fluorescence spectra are promising and may find widespread applicability for online analysis in numerous chemical systems found in the nuclear field.

A sensitive and selective ion chromatography (IC) method combined with on-line enrichment technology was developed for the determination of trace zinc ions (Zn²⁺) in the primary coolant of nuclear reactors. This method enables selective large-volume enrichment of Zn²⁺, overcoming interferences from high-concentration boric acid (>2000 mg/L) and lithium (3 mg/L) matrices. A 2.5 mM methanesulfonic acid—0.8 mM oxalic acid elution system was used in conjunction with direct conductivity detection. Under optimized conditions, the standard curve exhibited a linear relationship (R² > 0.999) within the Zn²⁺ concentration range of 10–100 μg/L. The boric acid concentration in the coolant matrix showed no interference with Zn²⁺ testing, while lithium hydroxide caused retention time shifts of Zn²⁺, which were eliminated by a matrix matching strategy. The spiked recovery of 15 μg/L in simulated samples was 99.47% (n=7, RSD=0.89%), and the method detection limit was 0.41 μg/L. This approach provides a robust and cost-effective solution for real-time monitoring of Zn²⁺ in nuclear coolants, contributing to corrosion control and radiation field optimization in nuclear power plants.

Accurate n/γ pulse shape discrimination (PSD) is essential in radiation detection. Utilizing EJ-276 scintillator data from an Am-Be neutron source and ¹³⁷Cs gamma source, this study proposes a Sparrow Search Algorithm-optimized BP network (SSA-BP). Under the same measurement conditions, SSA-BP achieves 99% accuracy, surpassing traditional methods by 96–98% and a GA-BP model by 58–75%, demonstrating a computationally efficient approach for rapid discrimination in mixed radiation fields.

This study investigated the spatiotemporal evolution of acid in-situ leaching (ISL) in the Bayan Ula uranium deposit’s C12 mining area. Tracer tests and anorthite dissolution analysis revealed progressive ore-layer clogging, reducing dispersion, most notably along the KZ15262 → KC15060 pathway. Anorthite dissolution generally decreased due to passivation but increased downstream owing to prolonged contact time. A dynamic "dissolution–precipitation–clogging–dispersion weakening" coupling mechanism was identified, with dissolution dominating near injection wells and precipitation-induced clogging prevailing farther away. These processes impaired leaching solution migration, ultimately lowering uranium recovery. The findings highlight the critical role of spatiotemporal dynamics in optimizing ISL efficiency.

Accurate prediction of the Maximum Detectable Distance (MDD) in mobile gamma spectrometry is essential for efficient surveying and reliable source detection. This study integrates a Physics-Informed Neural Network (PINN) with Monte Carlo N-Particle (MCNP) simulations to characterize how environmental and operational factors influence MDD. Local (OAT) and global (Sobol’) sensitivity analyses reveal nonlinear and asymmetric effects driven primarily by soil attenuation and detector velocity, while acquisition time exerts a dominant proportional influence (S₁ = 0.55). Uncertainty quantification, combining operational variability with stochastic Monte Carlo (MC) Dropout, shows that predicted MDD varies by ±5–10% under typical field conditions and up to ±15% in heterogeneous or shielded environments. By identifying the parameters that govern detection performance most strongly, this work provides a basis for developing adaptive survey strategies and improving decision-making in environmental radiation monitoring.

A timely hypothesis regarding the preferential binding of polonium-210 (Po-210) to the sulfhydryl (-SH) group of the amino acid cysteine is presented. This offers a mechanistic explanation for the bioaccumulation of Po-210 in the blood, liver, testes and hair, and insight into health risks, including cancer, infertility, and adverse birth outcomes, providing researchers with potential tools to track radioactivity exposures and assess certain incidences of cancer with suspected radiogenic environmental causes. The hypothesis has particular significance in regions of oil and gas production and infrastructure, and lays a foundation for future research, data collection and policy discussion.

An in-situ radiometric survey was carried out in Setibeni Region of western Nepal to evaluate the distribution and potential radiological hazards associated with naturally occurring radioactive materials (NORMs). The survey employed a portable gamma-ray spectrometer (PGIS-2). The mean values recorded for the absorbed dose rate (ADR), annual effective dose rate (AEDR), and radium equivalent activity ((Ra_textrm{eq})) were 131.30 nGy hr(^{-1}), 0.16 mSv yr(^{-1}), 277.79 Bq kg(^{-1}), respectively. Although these values exceeded the global averages, they remained within safe limits. The results highlight the need for continued environmental monitoring to safeguard public health in regions with elevated levels of natural radioactivity.

Thirty-six sand samples collected along the northeast coastal strip in Sri Lanka were analyzed using gamma-ray spectrometry. ²³²Th, ²²⁶Ra, and ⁴⁰K specific activities ranged from < MDL (Minimum Detection Limit) of each radionuclide to 2106 ± 47 Bq kg^− 1 (average 470 ± 3 Bq kg^− 1), 937 ± 20 Bq kg^− 1 (average 230 ± 2 Bq kg^− 1), and 345 ± 157 Bq kg^− 1 (average 152 ± 6 Bq kg^− 1), respectively. Annual effective dose rate (AEDR) ranged from 0.0079 ± 0.0008 mSv y^− 1 to 2.1 ± 0.04 mSv y^− 1. 10 locations in Pulmoddai, Kuchchaveli, and Arisimale regions exceeded the global AEDR.

The ability of plants to absorb and accumulate nutrients and metals is strongly influenced by environmental factors. This study employed neutron activation analysis to evaluate the transfer of essential and toxic elements from soil to rice stems and grains. Results indicated that concentrations of iron (Fe), cobalt (Co), and zinc (Zn) in Soc Trang soil were markedly higher than in Kien Giang, with Fe and Zn 1.8 and 2.9 times greater, respectively, while organic material (OM) was 3.4 times higher in Kien Giang. Variations in Fe and Zn affected arsenic (As) uptake, whereas OM negatively correlated with potassium (K) and Fe transport into grains, emphasizing the role of soil composition in nutrient absorption.