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[Display omitted] • Scintillator screen with micro/nano particles embedded into delignified wood. • Vertical column structured material suppressing the light lateral spreading. • Linear relationship between light yield and X-ray dose rate. • High spatial resolution X-ray imaging achieved. Nanocrystalline scintillators with low-cost, fast response, and high light yield are widely used for X-ray imaging. However, they fail in high-energy X-ray imaging because of the fundamental limitations due to lateral radiation spreading in thicker device-compatible active layers. This issue is resolved by using the novel nanocomposite containing CsPbBr 3 scintillation single-microcrystalites embedded into transparent, natural wood-derived light-guiding fibrous structures. The CsPbBr 3 crystals convert X-ray to visible photons with a high photoluminescence quantum efficiency (76 %), and an average fast photoluminescence decay time of 25.9 ns. The delignified wood-derived fiber-like lumina effectively guide light, while suppressing the lateral spreading of scintillation photons. This unique porous nanocomposite material offers an excellent X-ray detection performance, and linear response in a wide parameter range. The developed scintillator screen achieves well-resolved, high-contrast X-ray imaging, featuring a very high spatial resolution of 11.9 lp/mm at a modulation transfer function of 0.2, thus exceeding the benchmark industry standards and offering a new advanced materials platform for radiation detection and dosimetry applications. [ABSTRACT FROM AUTHOR]

Gadolinium is a soluble neutron poison for ensuring criticality safety of nuclear facility. A neutron induced gamma activation device was developed for the on-line measurement of gadolinium. The experimental device consisted of an 241Am–Be neutron source, six 3He detectors and a liquid scintillation detector. The size of sample container was optimized by using Monte Carlo simulations. Aqueous sample containing gadolinium nitrate were conducted with the device to obtain the calibration curve, and neutron self-shielding effect was also studied to correct the non-linear response. The results showed the minimum detectable concentration (MDC) of gadolinium was 0.426 mg/L. Two test samples were conducted to evaluate the performance of the device. The results demonstrated that the discrepancies were within 10%, which indicate the developed system can be successfully used for on-line monitoring of gadolinium. • Neutron induced gamma activation technique was applied for the on-line measurement of gadolinium. • An 241Am–Be neutron source, a liquid scintillation detector and six 3He detectors were used to develop the device. • The neutron self-shielding effect was corrected by using Monte Carlo simulations and experimental data. [ABSTRACT FROM AUTHOR]

In this study, neutron shielding composites (NSC) with an interpenetrating network structure are prepared with epoxy resin, B 4 C particles, and reinforced by different pore sizes reticulated porous ceramic skeletons (RPCS). The bonding strength between B 4 C particles and epoxy resin is improved via the surface modified process. The viscosity of B 4 C/epoxy resin is decreased with the increase in temperature. As increasing the curing temperature, the time to reach the gelation point decreases. After reaching the gelation point, the composite viscosity of B 4 C/epoxy resin is increased sharply. Because of adding the RPCS, flexural strength and thermal conductivity of the NSC specimens are increased, while the thermal expansion coefficient is progressively decreased. Compared with the specimen without RPCS, the flexure strength and thermal conductivity of the NSC specimen 30 PPI (pores per inch) are increased by 129.27% and 756%, but the thermal expansion coefficient is reduced by 81.66%. Under the same thickness, the NSC specimens from 10 PPI to 30 PPI, the sub-cadmium neutron (E < 0.4 eV) shielding capacity is increased first and then decreased. The NSC specimen 15 PPI has the best sub-cadmium neutron shielding capacity, the sub-cadmium neutron shielding capacity reaches 80.67% (0.5 cm). • A new strategy for preparing neutron shielding composites to enhance the mechanical properties and neutron shielding performance. • The viscosity of B 4 C/epoxy resin decreases with the increase of temperature. • High thermal conductivity and low thermal expansion coefficient. • The sub-cadmium neutron (E＜0.4 eV) shielding capacity of neutron shielding composites (0.5 cm) is 80.67%. [ABSTRACT FROM AUTHOR]

In this work, prompt gamma ray neutron activation analysis technique was used to monitor the REEs saturation in resin. A facility consisted of a D-T neutron generator, a BGO detector and a 3He detector was established and applied to analyze REEs (Gd and Sm) samples. Neutron self-shielding effect was also corrected. The enriched Gd and Sm in resin were close to saturation at about 400 min. The results showed a satisfactory agreement with the XRF tests, which demonstrated that PGNAA was sufficient for monitoring REEs saturation in resin. • A PGNAA method for rare earth ion exchange resin saturation analysis was proposed. • The change of REEs content in resin column was monitored directedly for resin saturation analysis. • A PGNAA setup with DT neutron generator and BGO detector was used to monitor the REEs saturation in resin. [ABSTRACT FROM AUTHOR]

A DT neutron source-based prompt gamma ray neutron activation (PGNAA) facility for bulk sample analysis was designed and developed in this research. The aqueous samples containing chlorine and boron with known concentration were determined for the calibration curve by the facility. The neutron self-shielding effect was corrected by internal standard method. The minimum detectable concentration of boron and chlorine are 1.37 ± 0.42 and 12.51 ± 3.80 mg/L, respectively. Finally, five mixture aqueous solution samples were measured for the facility performance test. The maximum relative deviation of boron and chlorine are 4.49% and 5.32% respectively. • A PGNAA facility combined with DT neutron source and a BGO detector was developed for elements determination in aqueous solution. • Nonlinearly response caused by the neutron self-shielding effect was corrected by internal standard method. • The detector shielding layer was optimized with signal-to-noise ratio (SNR) chosen as the evaluation. • Lower minimum detectable concentrations of boron and chlorine using this facility. [ABSTRACT FROM AUTHOR]

During a nuclear accident, estimating the source terms using environmental measurements is vital for emergency decision-making. In this study, we propose a forecasting model based on a temporal convolutional network to estimate the release rates of seven radionuclides (Kr-88, Te-132, I-131, Xe-133, Cs-137, Ba-140, and Ce-144) based on off-site sequential gamma dose rates and meteorological monitoring data. To determine the best structure of the neural network, Bayesian optimization and hyperband (BOHB) was used on the hyperparameters of the model to reduce the testing loss. Additionally, a gradient boosting regression model was used to predict missing gamma dose rates to ensure the model offers a relatively reliable estimate under certain circumstances. The international radiological assessment system (InterRAS) was used to generate datasets for model training and testing. The results showed that the optimal hyperparameters selected by BOHB can reduce the valid loss of the model to 0.0153, and the mean absolute percentage error of prediction for the seven radionuclides was below 12%, three of which (Kr-88, Te-132, Cs-137) reached 8% at 10 h. When the first and second time-steps of the data were missing, the mean absolute percentage error of the prediction for all radionuclides was less than 30% after using a gradient boosting regression. • Improving the estimation accuracy of multi-nuclide source term estimation method based on Temporal Convolutional Network. • Use Bayesian optimization and hyperband to search the optimal hyperparameters of the model. • Use a gradient boosting regression to complete the missing data to obtain a more accurate estimation. • Fast response and does not require priori information. • The mean absolute percentage error of prediction for the seven radionuclides below 12%. [ABSTRACT FROM AUTHOR]

In China, the annual output of kitchen wastewater with high oil content has exceeded 90 million tons, which poses a threat to the environment. Anaerobic digestion is considered a suitable treatment approach to realize the harmless and resource utilization of kitchen wastewater of the available bioresource. This study explored a pretreatment method based on gamma radiation to reduce the oil content in kitchen wastewater and improve its anaerobic digestion performance. In addition, response surface analysis was used to optimize the pretreatment conditions and build the production of kitchen wastewater gas prediction model. The results show that the deviation between the predicted value of the model and the actual value is less than 1.5%. The results show that the oil content decreases by 61% and the amount of anaerobic digestion gas production increases by 59% under the absorbed dose of 11.76 kGy, pH of 8.6, and the hydrogen peroxide concentration of 3.5 mmol/L, compared with those of the unirradiated wastewater. The gas chromatography and Fourier transform infrared spectroscopy analysis results show that there are more biodegradable organic substances in the wastewater after irradiation. [Display omitted] • We explored the best pre-treatment conditions for AD of kitchen wastewater. • The predicted and actual experimental gas production values differed by 1.4%. • Upon γ-ray pre-treatment, oil content of kitchen wastewater decreased by 61%. • Gas production generated through AD increased by 59%. • Enhancement of wastewater AD performance was related to changes in organic matter. [ABSTRACT FROM AUTHOR]

• Enhanced the flexural strength of SiC RPCs via in-situ carbon fibers. • The rheological behavior of SiC slurry with fibers was investigated. • The thermal stress in SiC RPCs was carried out using finite element modeling. Due to the poor strength of silicon carbide reticulated porous ceramics prepared by polymer sponge replica method, vacuum infiltration using a low viscosity infiltration slurry is performed to fill the flaws created during pyrolysis of the polymer sponge to improve the compressive strength. However, the flexural strength and thermal shock resistance of the porous silicon carbide ceramic are not significantly improved through this method. This paper investigates the improvement in thermal shock resistance and flexural strength of porous silicon carbide ceramics through the addition of different lengths and amounts of carbon fibers to the infiltration slurry. With the addition of 3 mm long carbon fibers at a concentration of 0.5 wt% to the infiltration slurry, the flexural strength of the porous silicon carbide ceramic was improved by 142%. Moreover, the thermal shock resistance of the SiC specimens was effectively enhanced through the addition of carbon fibers, as evidenced by a 74.4% increase in the residual strength ratio of the specimens. Due to the low thermal expansion coefficient of the carbon fibers, compressive residual stresses were generated in coating layers of SiC RPCs after sintering, which was inhibited the propagation of cracks in the coating layers. Thus, adding carbon fibers to the infiltration slurry can open more possibilities for application of SiC reticulated porous ceramics. [ABSTRACT FROM AUTHOR]

When severe nuclear accidents at nuclear power plants release radioactive material into the atmosphere, the source term information is typically unknown. Estimating the emission rate of radionuclides is essential to assess the consequences of the accident before adequate decision-making can be performed. A recurrent neural network-based model, optimized with the Bayesian method, is proposed to estimate the emission rates of multi-nuclides using off-site sequential gamma dose rate monitoring data. Compared with the existing method that is based on least squares, this new model does not require a priori information and the complicated and time-consuming process of conducting atmospheric dispersion simulations following a nuclear accident, which is conducive to a faster response. Six typical radionuclides (Sr-91, La-140, Te-132, Xe-133, I-131, and Cs-137) were set as mixed source terms, combined with meteorological parameters, and input into the International Radiological Assessment System for simulation to generate data sets for model training. The results indicate that with the input of data describing the sequential gamma dose rate, the accuracy of the nuclide emission rates estimated by this new method is continuously improved, with a mean absolute percentage error for Te-132 of below 7% over 10 h. [Display omitted] • Source term estimation method based on recurrent neural network. • Estimate the emission rate of 6 radionuclides using gamma dose rates. • Use Bayesian optimization to search the optimal structure of the model. • Fast response and does not require priori information. • Mean absolute percentage error of estimated results for Te-132 below 7%. [ABSTRACT FROM AUTHOR]

In this paper, a rapid, simple and reliable quantitative analysis method for Phosphorus and Sulfur in milligram quantities of plant samples by EDXRF has been described. The method uses a thin film sample preparation procedure which includes drying, suspension samples, filtration and pressing of the thin film samples. By measuring four random points of the same thin film sample, the homogenization of thin layer samples was evaluated to ensure the stability of the quantitative analysis results. The calibration curves of P, S, Ca and Fe was established by changing the weight of certified reference materials (CRMs) deposited on the filter. Then, the emission-transmission (E-T) method was used for correcting the matrix absorption effects of phosphorus and sulfur in the thin layer samples. After the correction, the correlation coefficients (R2) of the calibration curves of P and S were higher than 0.99. To evaluate the accuracy of quantitative analysis method, three vegetation verification samples were synthesized by adding the analytical pure powder to CRMs. The quantitative analytical results of EDXRF and ICP-OES were compared to the synthesized value. For P and S elements, the relative error of EDXRF and ICP-OES were 1.2%–6.4% and 4.2 %to 11.4%, respectively. • EDXRF technology is used to quantitative analyze the P and S element in vegetation samples at minor and trace amounts. • The Calibration curves of target elements (P, S, Ca, Fe) were obtained by changing the deposition on the filter. • The emission-transmission method is used to correct the result of quantitative analysis to P and S. • The measurement results and ICP-OES results have a good consistency. [ABSTRACT FROM AUTHOR]

Neutron shielding materials should have low density, high strength and excellent neutron shielding performance. Ceramic/epoxy composites are one of the candidates for such materials. In this study, neutron shielding composites with three-dimensionally interwoven structure were prepared with matrix of epoxy resin with B 4 C fine-powders and reinforcement of Al 2 O 3 –ZrO 2 3D reticulated ceramic with Gd 2 O 3 -CA6 layer. The 3D reticulated ceramic was fabricated by polymer replica method. Vacuum infiltration with Al(OH) 3 /CaCO 3 /Cd 2 O 3 slurry was used to enhance the properties and structure of 3D reticulated ceramic. Furthermore, the epoxy with 15 wt% B 4 C powders was also vacuum infiltrated into the ceramic skeletons to form neutron shielding composite materials with three-dimensionally interwoven structure. The as-prepared composite materials shielding rates of fast neutrons and thermal neutrons reached 26.5% and 89.4%, respectively. The bulk density and compressive strength reached 1.65 g/cm3 and 71.14 MPa, respectively. This study demonstrated an effective technique for preparing neutron shielding materials with excellent properties. Image 1 • Neutron shielding composite materials with novel structure was fabricated. • Optimization of ceramic skeleton surface via vacuum infiltration with ceramic slurry. • The composition of infiltration slurry greatly influenced the structure of composite. • Three-dimensionally interwoven structure was formed in the neutron composite. • The composites were viewed as a promising potential application in nuclear reactor. [ABSTRACT FROM AUTHOR]

Food waste (FW) has a high organic content, but its moisture content (up to 75–95%) limits its application. Improvement of dehydration has great significance for the subsequent treatment. This study investigated the influences of gamma-ray irradiation on the dehydration performance of rice waste, a major ingredient of FW. The measurement of mechanical centrifugation dehydration, moisture distribution and bond energy (H b) indicated that the supernatant volume, free moisture content and decrease in bonding energy is significantly enhanced by gamma-ray irradiation. Moreover, the mechanism of dehydration performance enhancement was discussed based on particle size analysis, reducing sugar (RS) content, UV–Vis spectrum and pH-value. Image 1 • The 16.56 kGy absorbed dose can increase the supernatant volume of the rice after centrifugation by 174%. • The dehydration effect of rice is enhanced with the increase of absorbed dose. • The enhancement of rice dehydration performance is related on particle size. • The changes of rice paste dehydration performance is related on pH-value. [ABSTRACT FROM AUTHOR]

• The enrichment of TiO 2 NPs in Salvinia natans was studied by EDXRF technology. • The thin film samples of plants were prepared by suspension deposition for EDXRF analysis. • The individual analysis of each tissue in a single plant was achieved by EDXRF technology. • The physiological alterations induced by TiO 2 NPs in Salvinia natans were studied from the perspective of elemental analysis. In this work, the biological enrichment of TiO 2 nanoparticles (NPs) by Salvinia natans was studied, and the EDXRF technology was used to evaluate the ability of Salvinia natans to enrich TiO 2 NPs. At the same time, with the accumulation of TiO 2 Nps in Salvinia natans, the changes of nutrient elements (P, S, Ca, Fe, and Zn) in its leaves and root tissues of Salvinia natans were observed simultaneously. The experimental results indicate that the Salvinia natans showed a strong potential to enrich the TiO 2 NPs. It had accumulated about 14.9 mg/g and 2.2 mg/g of titanium in roots and leaves when they were cultured in the highest TiO 2 NPs concentration (20 mg/L) to saturation. By calculating the bioconcentration factors (BCF), the enrichment ability of TiO 2 NPs in S. natans was evaluated. It was found that the enrichment effect of Salvinia natans on TiO 2 NPs showed negative correlation with the culture concentration. As to nutrient elements, the contents of P, S, and Ca in the roots and leaves were significantly increased with the increase of Ti enrichment. It might mean that the TiO 2 NPs have a positive effect on the growth and development of Salvinia natans. Besides, the reduction of Fe might indicate that the absorption of TiO 2 NPs affects the bioaccumulation of metal ions in Salvinia natans. [ABSTRACT FROM AUTHOR]

A MCNP model of a252Cf source-based prompt gamma-ray neutron activation analysis (PGNAA) system for bulk sample analysis was benchmarked. The indium foils activation and aqueous samples containing chlorine were measured using the PGNAA system, and the experimental data compared to the simulations. The discrepancies between the measurements and simulations are within 6% and 20% for thermal neutron flux and prompt gamma-ray response, respectively. The results show that the simulations agree well with the measurements, and demonstrate the proposed MCNP model can represent the system. • MCNP benchmarking of a252Cf source-based PGNAA system was conducted. • The bulk aqueous samples containing chlorine were measured using the PGNAA system. • The MCNP simulations were in good agreement with the experimental results. [ABSTRACT FROM AUTHOR]

• Build an estimation model based on Backpropagation Neural Networks for the release of I-131. • Dimensionality reduction of original data using Kernel Principal Component Analysis. • Optimize Neural Network using Particle Swarm Optimization. Rapid estimation of the release rate of source items after a nuclear accident is very important for nuclear emergency and decision making. A source term estimation method, based on the Backpropagation Neural Network (BPNN), was developed. Kernel Principal Component Analysis (KPCA) is used to reduce the dimension of the input parameters, which can accelerate the training of the neural network. Particle Swarm Optimization (PSO) is used to optimize weights and thresholds of BPNN, so that the neural network can better find the global optimal value, avoid falling into the local minimum. The large amount of data required for neural network training is generated using InterRAS software, the model constructed demonstrates the feasibility of this method. The proposed method can estimate the release rate of I-131 after half an hour of release, which is helpful to the emergency response, or provide an initial value or priori information for other methods. [ABSTRACT FROM AUTHOR]

Theacrine and theaflavins are known for their potential to mitigate depression and cognitive impairment. Jianghua Kucha black tea (JH) contains both compounds, yet its antidepressant properties are seldom documented. This study evaluated the effects of JH on depression in chronic unpredictable mild stress (CUMS) mice and explored the underlying mechanisms through integrative analyses of gut microbiota and fecal metabolomics. JH was found to significantly alleviate CUMS-induced depression-like behavior by improving body weight, food intake, 1% sucrose preference, immobility time, and numbers of crossings and standings compared to Zhuyeqi black tea (ZYQ), which contains theaflavins. JH notably altered the gut microbiota composition, enriching genera such as Turicibacter, Faecalibaculum, Akkermansia, and Desulfovibrio, while inhibiting genera norank&#95;f&#95;&#95;Muribaculaceae and Lactobacillus. Additionally, JH modified the fecal metabolite profile, characterized by increased levels of several secondary bile acids (BAs) and decreased levels of several purine intermediate metabolites. Furthermore, JH upregulated levels of monoamine neurotransmitters (5-HT and DA) and brain-derived neurotrophic factor (BDNF), while downregulating pro-inflammatory cytokines IL-6 and TNF-α in brain tissue. These findings suggested that JH could mitigate CUMS-induced depression-like behavior, potentially by modulating gut microbiota composition and function, as well as brain neurochemicals and cytokines., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The segmented ringed gamma scanning (SRGS) technique represents an advancement in segmented gamma scanning (SGS) technology used for detecting the density of radioactive waste drums, offering enhanced measurement accuracy. However, significant occur errors in the reconstruction of matrix densities due to the non-uniform distribution of density in radioactive waste and the conical beam emitted from the transmission source collimator. This paper proposes a density correction method based on dichotomy to address this issue. The efficacy of this method was verified through both simulations and experiments on a sample containing five different materials, utilizing 137 Cs and 60 Co for transmission and emission measurements, respectively. The experimental results demonstrate that the errors in the corrected matrix densities are reduced, falling within a margin of 16.8%. Additionally, the corrected reconstruction error of the activity is approximately 25% of the uncorrected results., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Ionizing irradiation, as a new pretreatment method for the anaerobic fermentation of organic pollutants, is featured with fast reaction speed, good treatment effect, no need to add any chemical reagents, and no secondary pollution. This study explores the mechanism of improving anaerobic fermentation performance of rice samples pretreated by cobalt-60 gamma irradiation through the influence on fermentation substrate, acidogenic phase and methanogenic phase. The results reveal that the soluble chemical oxygen demand of the irradiated rice sample at an absorbed dose of 9.6 kGy increases by 12.4 times due to the dissolution of small molecules of fat-soluble organic matter. The yield of biogas in the acidogenic phase increases by 22.2% with a slight increase in hydrogen gas content. The yield of biogas and methane gas content in the methanogenic phase increases by 27.3% and 15%, respectively. Microbial genome analysis, performed with MiSeq high-throughput sequencing and metagenomic methods, suggests the microbial abundance and metabolic functions in the anaerobic fermentation process change significantly as a result of the pretreatment by gamma irradiation., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Raw dark tea (RDT) usually needs to be stored for a long time to improve its quality under suitable relative humidity (RH). However, the impact of RH on tea quality is unclear. In this study, we investigated the metabolites and microbial diversity, and evaluated the sensory quality of RDT stored under three RH conditions (1%, 57%, and 88%). UHPLC-Q-TOF-MS analysis identified 144 metabolites, including catechins, flavonols, phenolic acids, amino acids, and organic acids. 57% RH led to higher levels of O -methylated catechin derivatives, polymerized catechins, and flavonols/flavones when compared to 1% and 88% RH. The best score in sensory evaluation was also obtained by 57% RH. Aspergillus , Gluconobacter , Kluyvera , and Pantoea were identified as the core functional microorganisms in RDT under different RH storage conditions. Overall, the findings provided new insights into the variation of microbial communities and chemical components under different RH storage conditions., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Author(s).)

In lignocellulosic biomass biotransformation technology, pretreatment is the most important step to increase the conversion efficiency and reduce cost. The electron beam irradiation (EBI) pretreatment method was discussed in this study. First, the effects of a 0-1200 kGy irradiation dose on saccharification efficiency of lignocellulose biomass (birch) and analytically pure cellulose were studied. Then, the pretreated samples were tested for composition, X-ray diffraction, degree of polymerization, and Fourier transform infrared spectroscopy. Finally, the mechanism of the EBI pretreatment was analyzed from the aspects of lignin content, cellulose crystallinity, cellulose polymerization degree, and cellulose molecular structure. The results show that the EBI pretreatment can significantly improve the efficiency of enzymatic hydrolysis by degrading the lignin in lignocellulose, reducing the crystallinity and polymerization degree of cellulose, and destroying the cellulose molecules. It also obtained that the pretreatment of cellulose and lignocellulose with irradiation has a different trend in enzymatic hydrolysis efficiency with irradiation dose. This indicates that there is a difference in irradiation effects between pure cellulose and lignocellulose. And a possible degradation pathway of cellulose was proposed. This study has important guide for the application and development of EBI pretreatment methods., (Copyright © 2019 Elsevier B.V. All rights reserved.)