摘要：
The RAD7 detector is widely used for measuring the radon exhalation rate from the surfaces of media such as soil, rocks, and building materials. However, during the measurement process, the accuracy of the results is prone to interference due to the instrument's inherent statistical errors and environmental noise. To reduce these measurement errors, the Kalman filtering was introduced in this study to correct the radon exhalation rate, which was obtained through data fitting of radon concentration measured by the RAD7 detector. Ten verified experiments were performed with a radon exhalation standard device. The experimental result shows that 80 % of the radon exhalation rate, corrected by Kalman filtering, significantly approached the theoretical value of the standard device, compared to the uncorrected experimental results. It confirms the effectiveness of the Kalman filtering in correcting RAD7 measurements, thereby enhancing the accuracy of radon exhalation rate measurements. The proposed method provides a reference technical pathway for improving the measurement accuracy of similar radon measurement instruments.
The RAD7 detector is widely used for measuring the radon exhalation rate from the surfaces of media such as soil, rocks, and building materials. However, during the measurement process, the accuracy of the results is prone to interference due to the instrument's inherent statistical errors and environmental noise. To reduce these measurement errors, the Kalman filtering was introduced in this study to correct the radon exhalation rate, which was obtained through data fitting of radon concentration measured by the RAD7 detector. Ten verified experiments were performed with a radon exhalation standard device. The experimental result shows that 80 % of the radon exhalation rate, corrected by Kalman filtering, significantly approached the theoretical value of the standard device, compared to the uncorrected experimental results. It confirms the effectiveness of the Kalman filtering in correcting RAD7 measurements, thereby enhancing the accuracy of radon exhalation rate measurements. The proposed method provides a reference technical pathway for improving the measurement accuracy of similar radon measurement instruments.
期刊：
Annals of Nuclear Energy,2026年226:111875 ISSN：0306-4549
通讯作者：
Zhao, PC
作者机构：
[Li, Feiyang; Liu, Zijing; Zeng, Youwei; Zhao, Pengcheng] Univ South China, Sch Nucl Sci & Technol, Hengyang 421001, Hunan, Peoples R China.;[Li, Feiyang; Liu, Zijing; Zeng, Youwei; Zhao, Pengcheng] Minist Educ, Key Lab Adv Nucl Energy Design & Safety, Hengyang 421001, Peoples R China.;[Li, Wei] Univ South China, Sch Resource Environm & Safety Engn, Hengyang 421200, Peoples R China.
通讯机构：
[Zhao, PC ] U;Univ South China, Sch Nucl Sci & Technol, Hengyang 421001, Hunan, Peoples R China.
关键词：
Lead-bismuth fast reactor;Active learning strategy;Integrated surrogate model;Passive system;Reliability analysis
摘要：
Passive residual heat removal systems ensure the safe operation of lead–bismuth fast reactors. However, the resistance of such systems is similar to natural driving forces, while small fluctuations in the surrounding environment and material parameters can cause system failure; thus, analyzing the reliability of passive residual heat removal systems is important for lead–bismuth cooling. This study utilizes the passive system in the lead–bismuth eutectic loop of the TALL-3D experimental facility and proposes a reliability analysis based on the active learning-integration (AL-I) surrogate model. The AL-I surrogate model is constructed first, and single-failure and multiple-failure region validations are performed to ensure accuracy and robustness of the model. Subsequently, the sensitivity and reliability of the TALL-3D non-energetic system is determined. The active learning ensemble surrogate model only needs 99 low-cost numerical calculations to obtain a reliable result with a failure rate of 0.0650%. This model not only significantly reduces the computational resources and time costs, but also allows high-precision failure probability assessments. Therefore, this study shows that the AL-I surrogate model is advantageous for lead–bismuth cooled non-energetic waste heat discharge systems and offers solid technical support for engineering such systems.
Passive residual heat removal systems ensure the safe operation of lead–bismuth fast reactors. However, the resistance of such systems is similar to natural driving forces, while small fluctuations in the surrounding environment and material parameters can cause system failure; thus, analyzing the reliability of passive residual heat removal systems is important for lead–bismuth cooling. This study utilizes the passive system in the lead–bismuth eutectic loop of the TALL-3D experimental facility and proposes a reliability analysis based on the active learning-integration (AL-I) surrogate model. The AL-I surrogate model is constructed first, and single-failure and multiple-failure region validations are performed to ensure accuracy and robustness of the model. Subsequently, the sensitivity and reliability of the TALL-3D non-energetic system is determined. The active learning ensemble surrogate model only needs 99 low-cost numerical calculations to obtain a reliable result with a failure rate of 0.0650%. This model not only significantly reduces the computational resources and time costs, but also allows high-precision failure probability assessments. Therefore, this study shows that the AL-I surrogate model is advantageous for lead–bismuth cooled non-energetic waste heat discharge systems and offers solid technical support for engineering such systems.
摘要：
Single-phase concentrated solid-solution alloys have garnered widespread attention due to their remarkable irradiation resistance properties. In this study, the molecular dynamics method was employed to investigate the collision cascade process in Ni-Fe alloys. The generation and evolution of point defects under uniaxial strain were systematically analyzed for alloys with varying Fe concentrations. It was observed that the peak number of point defects increased under tensile strain but decreased under compressive strain as the uniaxial strain magnitude rose. However, the uniaxial strain exhibited only a minor influence on the surviving number of defects. The calculated formation energies revealed that Fe vacancies possessed higher formation energies compared to Ni vacancies. Consequently, an increase in Fe concentration led to greater participation of Fe atoms in collision cascades, resulting in fewer point defects during the thermal peak stage. Owing to the elevated defect formation energies of Fe relative to Ni, the proportions of Fe vacancies and interstitials in the total point defects were consistently lower than the Fe atomic concentration. These findings indicate that higher Fe concentrations impede the formation of point defects. (c) 2025 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license(https://creativecommons.org/licenses/by/4.0/).
通讯机构：
[Liu, M ] U;Univ South China, Coll Nucl Sci & Technol, Hengyang 421200, Hunan, Peoples R China.
关键词：
Atomic emission spectroscopy;Curie temperature;Layered semiconductors;Manganese compounds;Metal ions;Mossbauer spectroscopy;Single crystals;Spin glass;Superparamagnetism;X ray powder diffraction;Zinc alloys;Zinc compounds;Cr substitutions;Magnetic behavior;Magnetic ions;Manganese zinc spinel ferrite;Mossbauer spectra;Nonmagnetics;Powder samples;Sol- gel methods;Spinel ferrites;Superparamagnetic clusters;Sol-gel process
摘要：
Mn 0.4 Zn 0.6 Fe 2-2 x Cr 2 x O 4 ( x = 0, 0.1, 0.2, 0.3, and 0.4) powder samples were prepared using the sol-gel method. X-ray powder diffraction (XRD) showed that all samples belong to the cubic spinel crystal system with an Fd-3m space group. The Scanning Electron Microscope (SEM) results show that the substitution of Cr leads to a reduction in grain size . The magnetothermal curves obtained from the Multi-Purpose Physical Property Measurement System (PPMS-9) indicated the presence of a spin glass state at low temperatures. With increasing Cr 3+ doping, the Curie temperature decreased and dropped below room temperature at x = 0.4. The unsaturated hysteresis loops of the samples reveal the presence of anomalous paramagnetism below the Curie temperature . Mössbauer spectrum confirmed the coexistence of ferromagnetism and paramagnetism at room temperature. Mössbauer spectrum analysis indicates an interesting superparamagnetic cluster phenomenon caused by the presence of excess non-magnetic ions in the sample. Additionally, Cr doping altered the distribution of metal ions in the samples, causing fluctuations in the area of the superparamagnetic clusters, which verifies that this phenomenon is primarily driven by the magnetic behavior influenced by non-magnetic ions.
Mn 0.4 Zn 0.6 Fe 2-2 x Cr 2 x O 4 ( x = 0, 0.1, 0.2, 0.3, and 0.4) powder samples were prepared using the sol-gel method. X-ray powder diffraction (XRD) showed that all samples belong to the cubic spinel crystal system with an Fd-3m space group. The Scanning Electron Microscope (SEM) results show that the substitution of Cr leads to a reduction in grain size . The magnetothermal curves obtained from the Multi-Purpose Physical Property Measurement System (PPMS-9) indicated the presence of a spin glass state at low temperatures. With increasing Cr 3+ doping, the Curie temperature decreased and dropped below room temperature at x = 0.4. The unsaturated hysteresis loops of the samples reveal the presence of anomalous paramagnetism below the Curie temperature . Mössbauer spectrum confirmed the coexistence of ferromagnetism and paramagnetism at room temperature. Mössbauer spectrum analysis indicates an interesting superparamagnetic cluster phenomenon caused by the presence of excess non-magnetic ions in the sample. Additionally, Cr doping altered the distribution of metal ions in the samples, causing fluctuations in the area of the superparamagnetic clusters, which verifies that this phenomenon is primarily driven by the magnetic behavior influenced by non-magnetic ions.
摘要：
The i-SANEX process has been developed as a promising strategy for the separation of trivalent lanthanide-actinides, which can effectively overcome the poor solubility of N-donors in nonpolar solvents. In this study, four hydrophilic phenanthroline-based ligands (L1-L4) with different terminal groups were synthesized to evaluate their water solubility and masking effects on An(III) in aqueous solutions using competitive extraction dominated by TODGA. Among these ligands, BHEO-DAPhen (L1), featuring an ethoxyethanol-modified side chain, demonstrated the best overall performance in both solubility and selectivity. Competitive two-phase extraction experiments confirmed that L1 significantly enhanced the separation factor (SF(Eu/Am)), reaching a striking maximum value of 558 in 0.6 M HNO(3). The coordination behavior of L1 with trivalent metal ions was comprehensively investigated using UV-visible titration, (1)H NMR titration, IR spectroscopy, ESI-HRMS, TRLFS spectroscopy, and X-ray single-crystal diffraction. DFT calculations also revealed that the exceptional selectivity of L1 toward Am(III) is attributed to stronger covalent interactions than Eu(III). These results demonstrated the potential of L1 as a promising masking agent for the selective separation of An(III) and Ln(III), providing valuable insights for the treatment of next-generation nuclear wastes.
摘要：
Background and purpose The image quality of single-energy CT (SECT) limited the accuracy of automatic segmentation. Dual-energy CT (DECT) may potentially improve automatic segmentation yet the performance and strategy have not been investigated thoroughly. Based on DECT-generated virtual monochromatic images (VMIs), this study proposed a novel deep learning model (MIAU-Net) and evaluated the segmentation performance on the head organs-at-risk (OARs).
The image quality of single-energy CT (SECT) limited the accuracy of automatic segmentation. Dual-energy CT (DECT) may potentially improve automatic segmentation yet the performance and strategy have not been investigated thoroughly. Based on DECT-generated virtual monochromatic images (VMIs), this study proposed a novel deep learning model (MIAU-Net) and evaluated the segmentation performance on the head organs-at-risk (OARs).
Methods and Materials The VMIs from 40 keV to 190 keV were retrospectively generated at intervals of 10 keV using the DECT of 46 patients. Images with expert delineation were used for training, validation, and testing MIAU-Net for automatic segmentation. The performance of MIAU-Net was compared with the existing U-Net, Attention-UNet, nnU-Net and TransFuse methods based on Dice Similarity Coefficient (DSC). Correlation analysis was performed to evaluate and optimize the impact of different virtual energies on the accuracy of segmentation.
The VMIs from 40 keV to 190 keV were retrospectively generated at intervals of 10 keV using the DECT of 46 patients. Images with expert delineation were used for training, validation, and testing MIAU-Net for automatic segmentation. The performance of MIAU-Net was compared with the existing U-Net, Attention-UNet, nnU-Net and TransFuse methods based on Dice Similarity Coefficient (DSC). Correlation analysis was performed to evaluate and optimize the impact of different virtual energies on the accuracy of segmentation.
Results Using MIAU-Net, average DSCs across all virtual energy levels were 93.78 %, 81.75 %, 84.46 %, 92.85 %, 94.40 %, and 84.75 % for the brain stem, optic chiasm, lens, mandible, eyes, and optic nerves, respectively, higher than the previous publications using SECT. MIAU-Net achieved the highest average DSC (88.84 %) and the lowest parameters (14.54 M) in all tested models. The results suggested that 60 keV-80 keV is the optimal VMI energy level for soft tissue delineation, while 100 keV is optimal for skeleton segmentation.
Using MIAU-Net, average DSCs across all virtual energy levels were 93.78 %, 81.75 %, 84.46 %, 92.85 %, 94.40 %, and 84.75 % for the brain stem, optic chiasm, lens, mandible, eyes, and optic nerves, respectively, higher than the previous publications using SECT. MIAU-Net achieved the highest average DSC (88.84 %) and the lowest parameters (14.54 M) in all tested models. The results suggested that 60 keV-80 keV is the optimal VMI energy level for soft tissue delineation, while 100 keV is optimal for skeleton segmentation.
Conclusions This work proposed and validated a novel deep learning model for automatic segmentation based on DECT, suggesting potential advantages and OAR-specific optimal energy of using VMIs for automatic delineation.
This work proposed and validated a novel deep learning model for automatic segmentation based on DECT, suggesting potential advantages and OAR-specific optimal energy of using VMIs for automatic delineation.
通讯机构：
[Feng, SY ] U;Univ South China, Sch Resource Environm & Safety Engn, Hengyang 421001, Hunan, Peoples R China.
摘要：
In geological and engineering practices, determining fracture intensity of rock masses is critical for the exploitation of resources such as oil, natural gas, uranium, and geothermal energy. Due to the lack of technological means to directly measure the distribution of rock fractures, it is very difficult to obtain the rock fracture intensity. This paper proposes an integrated approach to predicting rock fracture intensity based on artificial neural network (ANN) and radon tracing. Firstly, a radon migration model was established to numerically simulate radon exhalation rate of fractured rock masses under different fracture parameters. In the model, rock fractures were generated using the discrete fracture network (DFN). 900 sets of data were numerically calculated as learning data for the ANN using the model. The proposed method has good prediction accuracy with a coefficient of determination of 0.907. The number of hidden layers and neurons are key factors determining the accuracy of model prediction. Finally, the model was used to predict the fracture intensity of a fractured rock mass with outcrop. The predicted fracture intensity is close to the measured value, with a difference of 7.5 %.
In geological and engineering practices, determining fracture intensity of rock masses is critical for the exploitation of resources such as oil, natural gas, uranium, and geothermal energy. Due to the lack of technological means to directly measure the distribution of rock fractures, it is very difficult to obtain the rock fracture intensity. This paper proposes an integrated approach to predicting rock fracture intensity based on artificial neural network (ANN) and radon tracing. Firstly, a radon migration model was established to numerically simulate radon exhalation rate of fractured rock masses under different fracture parameters. In the model, rock fractures were generated using the discrete fracture network (DFN). 900 sets of data were numerically calculated as learning data for the ANN using the model. The proposed method has good prediction accuracy with a coefficient of determination of 0.907. The number of hidden layers and neurons are key factors determining the accuracy of model prediction. Finally, the model was used to predict the fracture intensity of a fractured rock mass with outcrop. The predicted fracture intensity is close to the measured value, with a difference of 7.5 %.
摘要：
PURPOSE: 3D U-Net deep neural networks are widely used for predicting radiotherapy dose distributions. However, dose prediction for lung cancer IMRT is limited to conventional radiotherapy, with significant errors in predicting the intermediate and low-dose regions. METHODS: We included a mixed dataset of conventional radiotherapy and simultaneous integrated boost (SIB) radiotherapy with various prescription schemes. In addition to inputting CT images and anatomical structures, we incorporated dose mask information to provide richer local low-dose details. We trained five models with varying numbers of dose masks to investigate their impact on dose prediction models. RESULTS: The inclusion of dose masks led to significant improvements in prediction accuracy for both the PTV and OARs. In particular, the mean absolute error (MAE) of dosimetric metrics for most OARs fell below 2%, and voxel-wise MAE within each structure steadily decreased as more dose masks were supplied-most notably in low-dose regions. These results demonstrate that incorporating dose masks effectively enhances training efficiency and prediction stability. Among models receiving varying numbers of dose masks, the configuration with ten masks achieved the highest predictive accuracy. CONCLUSION: This study proposes a dose mask-assisted method for lung cancer IMRT dose prediction. It demonstrates high accuracy and robustness in clinical radiotherapy scenarios with various prescription schemes, including conventional radiotherapy and SIB. The inclusion of additional dose masks significantly improved model performance, with prediction accuracy increasing as the number of masks increased.
作者：
Wang, B.;Guo, C.;Xie, Y. G.;Hu, T.;Yu, B. . X.;...
期刊：
Journal of Instrumentation,2025年20(3):P03028 ISSN：1748-0221
通讯作者：
Tang, Q
作者机构：
[Tang, Q.; Wang, B.; Ling, X.; Tang, Q] Univ South China, Sch Nucl Sci & Technol, Hengyang, Peoples R China.;[Guo, C.; Yu, B. . X.; Zhang, Y. P.; Xie, Y. G.; Cai, X.; Hu, T.] Chinese Acad Sci, Inst High Energy Phys, Expt Phys Div, Beijing, Peoples R China.;[Guo, C.; Yu, B. . X.; Zhang, Y. P.; Xie, Y. G.; Cai, X.; Hu, T.] Univ Chinese Acad Sci, Sch Phys, Beijing, Peoples R China.;[Guo, C.; Yu, B. . X.; Zhang, Y. P.; Xie, Y. G.; Cai, X.; Hu, T.] State Key Lab Particle Detect & Elect, Beijing, Peoples R China.
通讯机构：
[Tang, Q ] U;Univ South China, Sch Nucl Sci & Technol, Hengyang, Peoples R China.
关键词：
Neutrino detectors;Radiation monitoring;Gas systems and purification
摘要：
The Jiangmen Underground Neutrino Observatory (JUNO) is an under-construction multi-purpose neutrino experiment primarily aiming to determine the neutrino mass ordering and precisely measure the neutrino oscillation parameters. The JUNO detector consists of a Central Detector (CD), a Water Cherenkov Detector (WCD), and a Top Tracker (TT). The target volume of JUNO is 20-kton ultrapure Liquid Scintillator (LS) purified by a system combining alumina oxide filter, distillation, LS mixing, water extraction, and gas stripping. Notably, the water extraction system necessitates a substantial volume of ultrapure water to eliminate radioactive metal ions from LS by fully mixing in the extraction tower. Since the radon gas is much easier to dissolve in LS than in water, the radon concentration in the ultrapure water must be strictly controlled. An ultrapure water system has been developed for the water extraction system. The radon is removed from water by degassing membranes, and the radon concentration in water is measured online by a highly sensitive radon measurement system. This paper will present the ultrapure water system, the radon measurement system, and current radon concentration results at different process sections of pure water system.
通讯作者：
Zhu, Liqiang;Chen, Xun;Zhang, HZ;Chen, X;Zhou, K;Huang, M
作者机构：
[Zhang, Hanzhong; Chen, Xun; Zhu, Liqiang] Cent China Normal Univ, Key Lab Quark & Lepton Phys MOE, Wuhan 430079, Peoples R China.;[Zhang, Hanzhong; Chen, Xun; Zhu, Liqiang] Cent China Normal Univ, Inst Particle Phys, Wuhan 430079, Peoples R China.;[Chen, Xun] Univ South China, Sch Nucl Sci & Technol, Hengyang 421001, Peoples R China.;[Chen, Xun] INFN Ist Nazl Fis Nucleare, Sez Bari, Via Orabona 4, I-70125 Bari, Italy.;[Zhou, Kai] Chinese Univ Hong Kong, Sch Sci & Engn, Shenzhen CUHK Shenzhen, Shenzhen 518172, Guangdong, Peoples R China.
通讯机构：
[Zhang, HZ ; Zhou, K ; Chen, X; Zhu, LQ] C;[Chen, X ; Huang, M ] U;Cent China Normal Univ, Key Lab Quark & Lepton Phys MOE, Wuhan 430079, Peoples R China.;Cent China Normal Univ, Inst Particle Phys, Wuhan 430079, Peoples R China.;Univ South China, Sch Nucl Sci & Technol, Hengyang 421001, Peoples R China.
摘要：
We present a Bayesian holographic model constructed by integrating the equation of state and baryon number susceptibility at zero chemical potential from lattice quantum chromodynamics (QCD). The model incorporates error estimates derived from lattice data. With this model, we systematically investigate the thermodynamic properties of the 2 + 1 -flavor QCD system. Using Bayesian inference, we perform precise calibration of the model parameters and determined the critical end point (CEP) position under the maximum a posterior (MAP) estimation to be ( T c , μ B c ) = ( 0.0859 GeV , 0.742 GeV ) . Additionally, we predict the CEP positions within 68% and 95% confidence levels, yielding ( T c , μ B c ) 68 % = ( 0.0820 − 0.0889 , 0.71 − 0.77 ) GeV and ( T c , μ B c ) 95 % = ( 0.0816 − 0.0898 , 0.71 − 0.79 ) GeV , respectively. Moreover, to validate the reliability and predictive power of our approach, we conduct a comprehensive comparison between our predictions and potential CEP locations proposed by other theoretical models. This work not only establishes a novel Bayesian framework for holographic modeling but also provides valuable insights and theoretical support for exploring phase transitions in strongly interacting matter under extreme conditions.
作者机构：
[Ye, Fengjiao; Tang, Xian; Xie, Xiangmin; Xu, Meicheng; Wu, Haibiao] Univ South China, Sch Nucl Sci & Technol, Hengyang 421001, Peoples R China.;[Huang, Dong] Hunan Univ, Coll Mat Sci & Engn, Hunan Prov Key Lab Adv Carbon Mat & Appl Technol, Changsha 410082, Peoples R China.;[Huang, Dong] Hunan Toyi Carbon Mat Technol Co Ltd, Hunan Prov Engn Res Ctr High Performance Pitch bas, Changsha 410205, Peoples R China.;[Cao, Xingzhong; Xie, Xiangmin; Cao, XZ; Xu, Meicheng] Chinese Acad Sci, Inst High Energy Phys, Beijing 100049, Peoples R China.;[Cao, Xingzhong; Cao, XZ] Henan Acad Sci, Ctr High Energy Phys, Zhengzhou 450046, Peoples R China.
通讯机构：
[Tang, X ] U;[Cao, XZ ] C;Univ South China, Sch Nucl Sci & Technol, Hengyang 421001, Peoples R China.;Chinese Acad Sci, Inst High Energy Phys, Beijing 100049, Peoples R China.;Henan Acad Sci, Ctr High Energy Phys, Zhengzhou 450046, Peoples R China.
摘要：
Carbon/carbon (C/C) composites are critical structural materials for advanced reactors, including molten salt reactors. However, the irradiation mechanisms, particularly the differences in irradiation-induced damage between fibers and matrices, remain inadequately understood. In this study, the irradiation behavior of mesophase-pitch-based carbon-fiber-reinforced carbon matrix composites was investigated under 1.8-MeV Ar-ion irradiation at a dose of 3 × 1016 ions/cm2 at room temperature. Following irradiation, both the carbon fiber and matrix underwent amorphization and exhibited significant changes in surface morphology, the matrix exhibiting pronounced volumetric shrinkage compared to the fiber. Additionally, irradiation resulted in the degradation of the ordered graphite layers and closure of the initial cracks within the fiber and matrix. Notably, the matrix contained a greater number of initial cracks and crack closure was more pronounced during irradiation compared to the fiber. The differential shrinkage observed between the fiber and matrix is primarily attributed to the differences in the irradiation-induced closure behavior of the initial cracks in each component. These findings provide insights into enhancing the irradiation performance of C/C composites by adjusting the microstructural composition of the fiber and matrix.
Carbon/carbon (C/C) composites are critical structural materials for advanced reactors, including molten salt reactors. However, the irradiation mechanisms, particularly the differences in irradiation-induced damage between fibers and matrices, remain inadequately understood. In this study, the irradiation behavior of mesophase-pitch-based carbon-fiber-reinforced carbon matrix composites was investigated under 1.8-MeV Ar-ion irradiation at a dose of 3 × 1016 ions/cm2 at room temperature. Following irradiation, both the carbon fiber and matrix underwent amorphization and exhibited significant changes in surface morphology, the matrix exhibiting pronounced volumetric shrinkage compared to the fiber. Additionally, irradiation resulted in the degradation of the ordered graphite layers and closure of the initial cracks within the fiber and matrix. Notably, the matrix contained a greater number of initial cracks and crack closure was more pronounced during irradiation compared to the fiber. The differential shrinkage observed between the fiber and matrix is primarily attributed to the differences in the irradiation-induced closure behavior of the initial cracks in each component. These findings provide insights into enhancing the irradiation performance of C/C composites by adjusting the microstructural composition of the fiber and matrix.
摘要：
Water hyacinth is recognized as one of the top ten invasive weeds that pose significant environmental hazards globally. The resourceful utilization of water hyacinth offers substantial ecological benefits. In this work, water hyacinth is employed to synthesize a phosphorylated biochar for the efficient decontamination of uranium-containing radioactive wastewater, thereby achieving dual environmental benefits. The biochar with a large specific surface area of 1328 m2/g and a large pore volume of 0.94 cm3/g is obtained via carbonization of a freeze-dried water hyacinth-phytic acid composite. It possesses a high density of uranophilic phosphoric acid groups, with the surface phosphorus content reaching 0.78 at%. As anticipated, phosphorylated biochar demonstrates superior adsorption performance for uranium (VI) ions. The removal efficiency achieves 99 % in a uranium solution with an initial concentration of 100 mg/L at a dosage of 1.0 g/L within 30 minutes, while the maximum adsorption capacity reaches 478 mg/g. It is proficient in removing uranium across a pH range of 2.2–6.6 and exhibits tolerance under high ionic strength conditions. The distribution coefficient for uranium attains 28.5 L/g, which is significantly higher than that of many other metal ions. Moreover, the biochar is readily regenerated by elution with diluted HNO₃ and reused up to five times without any loss of efficiency. Delightfully, phosphorylated biochar effectively reduces the uranium concentration in actual nuclear wastewater from 16 μg/L to below 4 μg/L. The effective adsorptive decontamination of radioactive wastewater, followed by the incineration of spent biochar, significantly reduces the volume of radioactive waste.
Water hyacinth is recognized as one of the top ten invasive weeds that pose significant environmental hazards globally. The resourceful utilization of water hyacinth offers substantial ecological benefits. In this work, water hyacinth is employed to synthesize a phosphorylated biochar for the efficient decontamination of uranium-containing radioactive wastewater, thereby achieving dual environmental benefits. The biochar with a large specific surface area of 1328 m2/g and a large pore volume of 0.94 cm3/g is obtained via carbonization of a freeze-dried water hyacinth-phytic acid composite. It possesses a high density of uranophilic phosphoric acid groups, with the surface phosphorus content reaching 0.78 at%. As anticipated, phosphorylated biochar demonstrates superior adsorption performance for uranium (VI) ions. The removal efficiency achieves 99 % in a uranium solution with an initial concentration of 100 mg/L at a dosage of 1.0 g/L within 30 minutes, while the maximum adsorption capacity reaches 478 mg/g. It is proficient in removing uranium across a pH range of 2.2–6.6 and exhibits tolerance under high ionic strength conditions. The distribution coefficient for uranium attains 28.5 L/g, which is significantly higher than that of many other metal ions. Moreover, the biochar is readily regenerated by elution with diluted HNO₃ and reused up to five times without any loss of efficiency. Delightfully, phosphorylated biochar effectively reduces the uranium concentration in actual nuclear wastewater from 16 μg/L to below 4 μg/L. The effective adsorptive decontamination of radioactive wastewater, followed by the incineration of spent biochar, significantly reduces the volume of radioactive waste.
摘要：
This study investigates factors influencing the leaching process in uranium mining, using a uranium mine in Inner Mongolia, China, as a representative case. We used PHREEQC geochemical and COMSOL Multiphysics® software, as well as the coupling interface COMSOL PHREEQC (iCP), to simulate acid leaching of underground core mineral samples. The study systematically analyzes the effects of sulfuric acid concentration, permeability coefficient, and injection/leaching pressure differential on uranium leaching efficiency. It also reveals spatial and temporal variations of minerals throughout the leaching process. The findings include a positive correlation between sulfuric acid concentration and leaching rate. Increased permeability significantly enhanced the leaching effect, while the injection/leaching pressure differential had an optimal range. Additionally, mineral evolution characteristics suggested that acidophilic minerals dissolve rapidly in initial stages, whereas later stages may involve minerals such as kaolinite and quartz influencing pore structure. These findings provide a foundation for optimizing process parameters in uranium mining and offer a quantitative reference for micro-scale mineral changes, ultimately for efficient and sustainable uranium extraction.
摘要：
This study successfully synthesized Mg 0.5 Ni 0.5 Fe 2- x Nd x O 4 ( x = 0, 0.01, 0.03, 0.05) spinel ferrites using the sol-gel method. X-ray diffraction analysis revealed that doping with Nd 3+ enhanced lattice distortion, and a secondary NdFeO 3 phase emerged at higher concentrations. Mössbauer spectroscopy analysis revealed that Nd 3+ doping modified the distribution of metal cations within the samples and yielded theoretical values for the samples' magnetic moments. Magnetic analysis indicated that magnetic parameters, including saturation magnetization , remanence , and coercivity , displayed irregular variations with increasing Nd 3+ concentration, peaking at x = 0.03, while the presence of the NdFeO 3 secondary phase induced abnormal changes. These irregular variations may be attributed to the combined effects of microscopic magnetic mechanisms regulating the sample's magnetic response, such as lattice structure, metal cation distribution, the Yafet-Kittel spin canting effect, and the presence of the NdFeO 3 secondary phase.
This study successfully synthesized Mg 0.5 Ni 0.5 Fe 2- x Nd x O 4 ( x = 0, 0.01, 0.03, 0.05) spinel ferrites using the sol-gel method. X-ray diffraction analysis revealed that doping with Nd 3+ enhanced lattice distortion, and a secondary NdFeO 3 phase emerged at higher concentrations. Mössbauer spectroscopy analysis revealed that Nd 3+ doping modified the distribution of metal cations within the samples and yielded theoretical values for the samples' magnetic moments. Magnetic analysis indicated that magnetic parameters, including saturation magnetization , remanence , and coercivity , displayed irregular variations with increasing Nd 3+ concentration, peaking at x = 0.03, while the presence of the NdFeO 3 secondary phase induced abnormal changes. These irregular variations may be attributed to the combined effects of microscopic magnetic mechanisms regulating the sample's magnetic response, such as lattice structure, metal cation distribution, the Yafet-Kittel spin canting effect, and the presence of the NdFeO 3 secondary phase.
期刊：
Chemical Engineering Journal,2025年505:159469 ISSN：1385-8947
通讯作者：
Guibal, E;Hamza, MF
作者机构：
[Salih, Khalid A. M.; Zhou, Kanggen] Cent South Univ, Sch Met & Environm, Changsha 410083, Peoples R China.;[Guibal, Eric; Guibal, E] IMT Mines Ales, Polymers Compos & Hybrids PCH, Ales, France.;[Basiony, Ebtesam A.; Nassar, Lobna A.; Abdel-Rahman, Adel A. -H.] Menoufia Univ, Fac Sci, Chem Dept, Shibin Al Kawm 32511, Egypt.;[Ning, Shunyan; Wei, Yuezhou; Hamza, Mohammed F.; Hamza, MF] Univ South China, Sch Nucl Sci & Technol, Heng Yang 421001, Peoples R China.;[Wei, Yuezhou] Shanghai Jiao Tong Univ, Sch Nucl Sci & Engn, Shanghai, Peoples R China.
通讯机构：
[Hamza, MF ] U;[Guibal, E ] I;IMT Mines Ales, Polymers Compos & Hybrids PCH, Ales, France.;Univ South China, Sch Nucl Sci & Technol, Heng Yang 421001, Peoples R China.
关键词：
Adsorption isotherms;Alkali metals;Bioremediation;Gas absorption;Grafting (chemical);Membrane technology;Mendelevium;Solvent extraction;Thoria;Uranium compounds;Uranium metallurgy;Water absorption;X ray diffraction;B-y Ions;Carbamoylacetamide derivative grafted-chitosan;Comparative study of ion-imprinting and non-imprinting sorbent;Comparatives studies;Efficient urania recovery from acidic ore leachate;Enhancing U(VI) sorption by ion imprinting: improved uptake kinetic and selectivity;Ion imprinting;Leachates;Remarkable stability after 10 cycle of sorption and desorption;Sorption and desorptions;Uptake kinetics;Rare earth elements
摘要：
Uranium recovery from complex effluents requires the combination of different processes including metal sorption from low-concentration solutions containing several competitor metal ions. The design of efficient sorbents (BTC/CH(s), 2-(benzo[d]thiazol-2-yl)-N-carbamoyl acetamide grafted chitosan) that combine both high sorption capacity and high selectivity was achieved by adopting a dual strategy: (a) selecting efficient functional groups (amine, amide, thioester, and hydroxyl groups, in BTC/CH sorbents), and (b) adapting the arrangement of reactive groups appropriately to fit the specific shape of the complexes (ion-imprinting IP vs. non-ion-imprinted NIP materials). This dual strategy was applied to design a chitosan-based sorbent with high sorption capacity (≈1.5 mmol U g −1 ), fast uptake (equilibrium: 15–20 min), remarkable stability (limited loss of performances after 10 reuse cycles), and strong selectivity (tested on both equimolar multi-component solutions and pre-treated acid leachate), at moderately acidic pH (i.e., 4). Ion-templating strategy effectively improved selectivity by 5–10-folds. Uptake kinetics was fitted by the pseudo-first order rate equation, while the sorption isotherms were finely simulated by the Temkin equation. The sorption was exothermic, spontaneous, and the ion-templating allowed reaching more organized structure. The sorbent was highly selective against base metals, alkali and alkali-earth metals, but less efficient for the separation from thorium or rare-earth elements. The sorbent was successfully used for the recovery of residual uranyl from acidic leachates pre-treated with resins (Amberlite IRA-400 and DOWEX 50, for the recovery of U and rare-earth elements, respectively) and precipitation step (removal of Al(III)/Fe(III) at pH 4). The sorbents were characterized by elemental analysis, FTIR and XPS spectroscopy for analyzing the chemical structure of the materials and identifying their interactions with U(VI). Textural properties and pHpzc values were analyzed for supporting sorption behaviors.
Uranium recovery from complex effluents requires the combination of different processes including metal sorption from low-concentration solutions containing several competitor metal ions. The design of efficient sorbents (BTC/CH(s), 2-(benzo[d]thiazol-2-yl)-N-carbamoyl acetamide grafted chitosan) that combine both high sorption capacity and high selectivity was achieved by adopting a dual strategy: (a) selecting efficient functional groups (amine, amide, thioester, and hydroxyl groups, in BTC/CH sorbents), and (b) adapting the arrangement of reactive groups appropriately to fit the specific shape of the complexes (ion-imprinting IP vs. non-ion-imprinted NIP materials). This dual strategy was applied to design a chitosan-based sorbent with high sorption capacity (≈1.5 mmol U g −1 ), fast uptake (equilibrium: 15–20 min), remarkable stability (limited loss of performances after 10 reuse cycles), and strong selectivity (tested on both equimolar multi-component solutions and pre-treated acid leachate), at moderately acidic pH (i.e., 4). Ion-templating strategy effectively improved selectivity by 5–10-folds. Uptake kinetics was fitted by the pseudo-first order rate equation, while the sorption isotherms were finely simulated by the Temkin equation. The sorption was exothermic, spontaneous, and the ion-templating allowed reaching more organized structure. The sorbent was highly selective against base metals, alkali and alkali-earth metals, but less efficient for the separation from thorium or rare-earth elements. The sorbent was successfully used for the recovery of residual uranyl from acidic leachates pre-treated with resins (Amberlite IRA-400 and DOWEX 50, for the recovery of U and rare-earth elements, respectively) and precipitation step (removal of Al(III)/Fe(III) at pH 4). The sorbents were characterized by elemental analysis, FTIR and XPS spectroscopy for analyzing the chemical structure of the materials and identifying their interactions with U(VI). Textural properties and pHpzc values were analyzed for supporting sorption behaviors.
摘要：
This study, adhering to the Chinese standard GB/T 34008-2017, introduces a penalty-function-based particle swarm optimization algorithm and proposes an innovative approach for optimizing the aggregate mix ratio in radiation-shielding concrete. Utilizing barite, magnetite, and hematite as aggregates, the proposed optimization method yielded optimal mix ratios tailored for shielding 4.5 and 10 MeV neutrons while achieving target compressive strengths of 35 and 40 MPa. Geant4 simulations and experimental validations confirm that the optimized concrete offers robust neutron and gamma-ray shielding properties. Compared to conventional concrete, it achieves a 20.89% reduction in maximum neutron absorption dose and enhances the gamma-ray linear attenuation coefficient by up to 43.17%. The developed optimization method offers valuable guidance for shielding design in nuclear technology application laboratories.
摘要：
The multiple nuclides identification algorithm with low consumption and strong robustness is crucial for rapid radioactive source searching. This study investigates the design of a low-consumption multiple nuclides identification algorithm for portable gamma spectrometers. First, the gamma spectra of 12 target nuclides (including the background case) were measured to create training datasets. The characteristic energies, obtained through energy calibration and full-energy peak addresses, are utilized as input features for a neural network. A large number of single- and multiple-nuclide training datasets are generated using random combinations and small-range drifting. Subsequently, a multi-label classification neural network based on a binary cross-entropy loss function is applied to export the existence probability of certain nuclides. The designed algorithm effectively reduces the computation time and storage space required by the neural network and has been successfully implemented in a portable gamma spectrometer with a running time of
$$t_\text {r}<{2\,\textrm{s}}$$
. Results show that, in both validation and actual tests, the identification accuracy of the designed algorithm reaches 94.8%, for gamma spectra with a dose rate of
$$d\approx {0.5\,\mathrm{\upmu Sv/h}}$$
and a measurement time
$$t_\text {m}={60\,\textrm{s}}$$
. This improves the ability to perform rapid on-site nuclide identification at important sites.
关键词：
Uranium reduction;Cobalt oxides;Oxygen vacancies;Recovery of uranium;Radioactive wastewater
摘要：
As the primary uranium species in aquatic systems, uranyl ions (UO 2 2+ ) readily form stable coordination complexes with organic contaminants, severely compromising the recovery and utilization of uranium. To address this challenge, we developed a novel photoelectrochemical (PEC) system featuring oxygen-vacancy-enriched cobalt oxide-modified carbon felt (OvCoO x /CF) as a functional cathode. In this PEC system, the photoanode is photoexcited to generate holes (h + ) and hydroxyl radicals (•OH) efficiently decomposing organic substances, thereby releasing uranium from complexes. Concurrently, photogenerated electrons migrate through the external circuit to the OvCoO x /CF cathode, where they reduce and fix the released UO 2 2+ into stable uranium compounds while simultaneously generating electrical output. This synergistic mechanism enables the system to achieve remarkable enhancements in contaminant removal efficiency, with substantial increases in rate constants ( k ) for both uranium reduction and organic degradation. The exceptional uranium extraction performance is primarily attributed to abundant active sites, the lower adsorption energy of UO 2 2+ , and the rapid electron transfer channel introduced by the incorporation of Ov. Notably, the PEC system maintains high efficiency across diverse conditions, including pH fluctuations, high salinity and various organic contaminant species and concentrations. Furthermore, its operational robustness extends to challenging environments such as polluted seawater and natural sunlight exposure. This work establishes a sustainable paradigm for radioactive wastewater remediation, integrating efficient uranium extraction with organic pollutant elimination and in situ electricity generation, offering a transformative solution for nuclear resource recovery and environmental protection.
As the primary uranium species in aquatic systems, uranyl ions (UO 2 2+ ) readily form stable coordination complexes with organic contaminants, severely compromising the recovery and utilization of uranium. To address this challenge, we developed a novel photoelectrochemical (PEC) system featuring oxygen-vacancy-enriched cobalt oxide-modified carbon felt (OvCoO x /CF) as a functional cathode. In this PEC system, the photoanode is photoexcited to generate holes (h + ) and hydroxyl radicals (•OH) efficiently decomposing organic substances, thereby releasing uranium from complexes. Concurrently, photogenerated electrons migrate through the external circuit to the OvCoO x /CF cathode, where they reduce and fix the released UO 2 2+ into stable uranium compounds while simultaneously generating electrical output. This synergistic mechanism enables the system to achieve remarkable enhancements in contaminant removal efficiency, with substantial increases in rate constants ( k ) for both uranium reduction and organic degradation. The exceptional uranium extraction performance is primarily attributed to abundant active sites, the lower adsorption energy of UO 2 2+ , and the rapid electron transfer channel introduced by the incorporation of Ov. Notably, the PEC system maintains high efficiency across diverse conditions, including pH fluctuations, high salinity and various organic contaminant species and concentrations. Furthermore, its operational robustness extends to challenging environments such as polluted seawater and natural sunlight exposure. This work establishes a sustainable paradigm for radioactive wastewater remediation, integrating efficient uranium extraction with organic pollutant elimination and in situ electricity generation, offering a transformative solution for nuclear resource recovery and environmental protection.
