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LiF-BeF2-ZrF4-UF4 and LiF-BeF2 have been employed as fuel salt and coolant in liquid fueled molten salt reactor, respectively. A heat exchanger containing both fuel salt and cooling salt is placed inside the reactor vessel to dissipate the heat produced by the reactor. A molten salttoair heat exchanger outside the reactor vessel is used to cool the molten salt, and a molten salt pump is used to drive the circulation of the entire circuit of coolant system. As of the molten salt, LiF-BeF2 coolant, flows through the molten salt heat exchanger located inside the reactor vessel, nuclides in the coolant are activated by 19F(n, α)16N, 19F(n, γ)20F, and 19F(n, p)19O reactions with neutrons in the reactor core, and thus radionuclides such as 16N, 20F and 19O are produced. These radionuclides have radiation impact on the surrounding environment and equipment if they enter the rooms where equipment for molten salt coolant circuit locate. According to the flow process and distribution law of the cooling salt, theoretical calculation formulas to calculate the amount of radionuclide were given. Using theoretical formulas, calculated radioactivities of the three most important radionuclides 16N, 20F and 19O per unit volume of cooling salt are 9.05×106, 8.33×106 and 2.69×105 Bq/cm3 at the outlet of the molten salt heat exchanger, while the radioactivities of the three radionuclides at the same location calculated by ORIGENS program are 8.98×106, 8.58×106 and 2.76×105 Bq/cm3, respectively. The results calculated by the formulas are in good agreement with the data of the ORIGENS program, and the maximum relative deviation between the results of the two methods is 292%, indicating that applying the derived formulas to carry out cooling salt activation analysis is reasonable and feasible. These radionuclides, 16N, 20F and 19O, produced in the cooling salt of molten salt reactor release highenergy gamma rays as they decay. The total gamma emissivities of the cooling salt in equipment and pipelines located in the cooling salt storage tank room, in the molten salt-to-air heat exchanger room and in the cooling salt pump room are 8.71×1011, 9.51×1011 and 1.93×1012 s-1, respectively, and the most radioactive area is in the cooling salt pump room. The maximum absorbed dose rate at the location of the cooling salt auxiliary equipment is 45.7 mGy/h without shielding, which cannot meet the requirement of the radiation dose, and which should be less than 50 Gy for the entire life of the equipment (300 full power days). By setting a 30 cm thick concrete shielding wall between the cooling salt auxiliary equipment and the cooling salt pump, the absorbed dose rate at the location of the auxiliary equipment can be reduced to less than 7 mGy/h, thereby the radiation protection requirements for the cooling salt auxiliary equipment can be met.

The Ca-based organic framework (Ca-SINAP-1) loaded with silver was successfully prepared, which has a certain γ-ray irradiation resistance of 50 kGy. X-ray diffraction, scanning electron microscopy, Brunauer-Emmett-Teller specific surface area analysis, and pore volume analysis were used to characterize the sample and its Xe adsorption capacity. The results showed that loading of silver on the sample surface did not change the original structure of Ca-SINAP-1. However, the Xe uptake reached a maximum of 3.29 mmol/g and the Xe/Kr separation coefficient was 10.71 when silver loading was 0.93%. With increasing AgNO3 concentration in ethanol, the Xe adsorption quantity decreased because excess silver loading blocked the channels, and thus prevented Xe adsorption. The good irradiation resistance and high Xe/Kr selectivity make Ca-SINAP-1 a potential material for treating radioactive off-gas emitted from molten salt reactors.

As an ideal candidate for PbTe, which maintains excellent performance at mid-temperature, PbSe holds great application potential. In this work, based on an optimized dynamic doping material system, a series of entropy-enhanced n-type lead chalcogenides Pb1−ySnySe1−xTexSx-2at%Cu (x = 0 and y = 0; x = 0.1 and y = 0; x = 0.25 and y = 0; x = 0.25 and y = 0.125) are synthesized. The thermoelectric properties of PbSe are modulated by gradually increasing its configurational entropy through alloying with Te/S/Sn. Research results show that the increase in configurational entropy improves the crystal symmetry of PbSe and significantly increases the Seebeck coefficient while maintaining good electrical properties. The dense dislocations and nanoscale to submicron-scale incoherent precipitates generated lead to the localization of phonons, increase anharmonicity, and reduce the lattice thermal conductivity at room temperature to 0.73 W m−1 K−1. The total thermal conductivity drops significantly by 69.8%. Consequently, the thermoelectric properties of Pb0.875Sn0.125Se0.5Te0.25S0.25−2at%Cu are remarkably improved, with a maximum dimensionless merit ZTmax of ∼1.46 at 623 K and an average dimensionless merit ZTave of ∼1.15 at 300–700 K. In addition, the room-temperature dimensionless merit ZTRT ∼0.64 is the highest reported for n-type PbSe. This optimization strategy of dynamic doping combined with entropy engineering to regulate electron and phonon transport demonstrates a feasible means to improve thermoelectric performance. [ABSTRACT FROM AUTHOR]

In order to fully exploit the relationship between temporal features in photovoltaic power generation data and improve the prediction accuracy of photovoltaic power generation, a photovoltaic power generation forecasting method is proposed based on a hybrid model of the convolutional neural network (CNN) and extreme gradient boost (XGBoost). Taking the historical data of China's photovoltaic power plants as a sample, the high-dimensional mapping relationship of photovoltaic power generation variables is extracted based on the convolutional layer and pooling layer of the CNN network to construct a high-dimensional time-series feature vector, which is an input for the XGBoost. A photovoltaic power generation prediction model is established based on CNNXGBoost by training CNN and XGBoost parameters. Since it is difficult for a single model to achieve optimal prediction accuracy under different weather conditions, the k-means clustering algorithm is used to group the power datasets and train independent models to improve prediction accuracy. Through the actual data verification of photovoltaic power plants, the proposed photovoltaic power generation prediction model can accurately predict the power, which shows high prediction accuracy and generalization ability compared with other methods. [ABSTRACT FROM AUTHOR]

To distinguish the differences in volatile species and components of six wild honeys in Yunnan, headspace- gas chromatography-ion mobility spectroscopy (HS-GC-IMS) was used to analyze the characteristic flavor components of jiangcheng wild big dagua honey, wild black honey, wild cliff honey, wild small dagua honey, wild tree cave honey and lancang wild big dagua Honey. The volatile flavor fingerprints of different varieties of honey were constructed by LAV software to compare the differences in the characteristic flavor substances of different varieties of wild honey in Yunnan province and to determine the main characteristic flavor compounds and their relative contents. The results showed that there were some differences in the flavor substances of the six kinds of bees. The difference between jiangcheng wild dagua honey and wild xiaogua honey was the largest, followed by the difference between wild black honey and wild tree hole honey, and the similarity between wild cliff honey, wild wild xiaogua honey, wild tree hole honey and lancang wild dagua honey was higher. A total of 80 volatile substances were detected and 65 were qualitatively detected, including 24 aldehydes, 22 alcohols, 6 ketones, 7 esters, 3 furans, 1 pyrazine, and 1 hydrocarbon, 1 type of acids, 1 type of ethers. Twenty characteristic volatile markers (VIP>1) were screened by partial least squares- discriminant analysis, including 1 -heptanol, 6 -methyl -5 -hepten -2 -one, ethyl 2 -methylpropionate, ethyl acetate, hex- anal, cyclohexanone, linalool, butyraldehyde, dipropyl disulfide, citronellol, (E)-2-hexenal, oxidized linalool, 2-hex- anol, 2-pentylfuran, 1-heptanol, (E)-2-heptenal, phenylacetaldehyde, benzyl alcohol, isobutanol, and 2-furanyl alcohol. Principal component analysis and cluster analysis showed that different varieties of honey were clearly distinguished, indicating that the HS-GC-IMS technique can be used to distinguish honey. [ABSTRACT FROM AUTHOR]

BACKGROUND: Rice black‐streaked dwarf virus (RBSDV) is transmitted by small brown planthopper (Laodelphax striatellus [L. striatellus]) and causes devastating disease in rice. P9‐1 has silencing suppression activity and is the key protein for viroplasm formation in RBSDV‐infected plants and insects; however, its exact function is poorly understood. RESULTS: In this study, the P9‐1 of RBSDV interacted with L. striatellus 26S proteasome subunit RPN8. RBSDV accumulation in L. striatellus increased after the 26S proteasome was disrupted by silencing the RPN8 expression. This finding indicated that L. striatellus 26S proteasome played a defense role against RBSDV infection by regulating RBSDV accumulation. Further investigations revealed that P9‐1 could competitively bind to RPN8 with RPN7, thereby disrupting the assembly of 26S proteasome in L. striatellus and promoting the infection of RBSDV in insect vectors, and further affecting the transmission of the virus to rice by insect vectors. Similar to P9‐1, rice stripe virus (RSV) NS2, a weak silencing suppressor, regulated virus accumulation and transmission by hijacking RPN8 to interfere with the function of 26S proteasome in L. striatellus. CONCLUSION: These results suggest that viruses promote their own infection via interfering with ubiquitination pathway of insect vectors, and this mechanism might be of universal importance. These findings provide a new insight into the mechanism of virus transmission in insect vectors. © 2022 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]