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Boron neutron capture therapy(BNCT) is a binary targeted radiation therapy in which neutron does not directly provide tumor dose. The dose produced by the 10B(n, α)7Li capture reaction will be deposited in tumor cells by using targeted 10B agents. Therefore, understanding the biological distribution of 10B agents in the blood, tumor and normal tissue is essential for BNCT. 4-borono-L-phenylalanine(BPA) is the mainly used 10B agent in BNCT clinical trials worldwide. In order to support and facilitate the preparation of BPA-based BNCT clinical trials, information on the structure, physicochemical properties, cellular uptake mechanisms and human biological distribution of BPA are summarized in this paper.

Fiber-reinforced plastic (FRP) is prone to invisible damage caused by low-velocity impact (LVI) during service. The structural health monitoring system is of great significance for damage monitoring and maintenance of composite materials. In this study, four fiber Bragg grating sensors were employed to collect the time domain strain signals of composite materials subjected to LVIs. Furthermore, a numerical simulation model was established to rapidly obtain impact signal dataset. The signal arrival time, peak time, and peak amplitude were selected as signal features, and the backpropagation neural network was successfully applied to determine the location and energy of LVIs. To address the issue of peak feature extraction in the strain signal processing, a genetic algorithm-based sliding window peak detection optimization method was proposed, which significantly improved the final prediction accuracy. The experimental results indicated that within a position range of 300 mm × 300 mm, the average positioning error can reach 5.1 mm; and in an energy range of 0.5–1 J, the average energy prediction error can reach 0.030 J. The proposed method achieved accurate identification of the LVI location and energy for FRP.

Vanadium dioxide (VO2) has attracted extensive attention due to the specific metal-insulator phase transition as well as the wide device applications. The practical performance of VO2-based device strongly depends on the quality of VO2, since the higher quality of VO2 film always shows much more pronounced phase transition behavior. Thus, the preparation of high quality VO2 film is essential and highly desirable. In this work, we have prepared high-quality VO2 film on SiC substrate by water vapor oxidation with graphene (G) buffer layer, which showed excellent phase transformation properties. Compared with the VO2/SiC sample without G buffer layer, the VO2/G/SiC films show the resistance changes up to four-orders of magnitude across the phase transition boundary and superior optoelectronic properties, which indicates the significant role of G layer in the film growth process. The current study not only provides an economical and feasible method for VO2/G/SiC thin film preparation with high quality, but also supply some clues for the application of G-based VO2 devices in the future.

The polyurea elastomer (PUA) powder modifier was prepared by the method of spraying–initial crushing–fine grinding, and then, the PUA-modified asphalt was produced. The typical functional structure of PUA was identified and characterized. The apparent viscosity of PUA-modified asphalt was tested at different temperatures. The impact of particle size and content of PUA on creep and recovery properties of asphalt at high temperature was investigated through the multiple stress creep recovery test. The mesothermal fatigue behavior of PUA-modified asphalt was evaluated by means of time sweep and linear amplitude sweep. Results indicated that the high elastic properties of PUA materials might depend on the spherical structure inside PUA material. The diameter of functional structure was around 20 µm and presented as 3D ball structure. The increase in PUA particle size would lead to the increase in cracks and folds in the bonding surface PUA modifier could improve by about 50% of the apparent viscosity significantly. Furthermore, PUA modifier could promote the high-temperature rutting resistance and middle-temperature fatigue property of asphalt. The improving effect on R could reach almost 28% and the 0.075 mm could be the best application size of PUA.

This work presents the design and application of a low-cycle reciprocating loading test on 23 recycled aggregate concrete-filled steel tube columns and 3 ordinary concrete-filled steel tube columns. Additionally, a systematic study on the influence of various parameters (e.g., slenderness ratio, axial compression ratio, etc.) was conducted on the seismic performance of the specimens. The results show that all the specimens have good hysteresis performance and a similar development trend of skeleton curve. The influence of slenderness ratio on the seismic index of the specimens is more significant than that of the axial compression ratio and the steel pipe wall thickness. Furthermore, artificial intelligence was applied to estimate the influence of parameter variation on the seismic performance of concrete columns. Specifically, Random Forest with hyperparameters tuned by Firefly Algorithm was chosen. The high correlation coefficients (R) and low root mean square error values from the prediction results showed acceptable accuracy. In addition, sensitivity analysis was applied to rank the influence of the aforementioned input variables on the seismic performance of the specimens. The research results can provide experimental reference for the application of steel tube recycled concrete in earthquake areas.

Uranium is the heaviest naturally occurring radioactive element in nature, and it is widely distributed in the earth’s crust. With the improvement of the technical accuracy of mass spectrometry to measure uranium isotope ratios, it is gradually recognized that uranium isotopes in the natural environment also have fractionation effects. In this paper, the recent research results on uranium isotope fractionation is reviewed and the geochemical behavior of uranium in nature and the analytical methods of uranium isotopes is introduced. The natural uranium isotope fractionation is related to the nuclear volume effect, which leads to a greater tendency for heavy uranium isotopes to be enriched in the reductant equivalent, and the δ238U of U(Ⅵ) reduction to U(Ⅳ) reaches 1.0‰. The isotopic fractionation mechanism of uranium in redox exchange reactions is revealed by the sensitivity of uranium isotopes to the oxidation-reduction environment, and it is found that δ238U is significantly isotopically fractionated between deposits formed in different oxidation-reduction environments, and moreover, it is shown that the bioreduction-induced isotopic fractionation of uranium is greater. Therefore, uranium isotope fractionation has an important tracer role in the inversion of uranium ore formation environment and the study of radioactive environmental chemistry and environmental remediation in the in-situ leaching of uranium mining. Finally, how to better address the environmental remediation of groundwater in the in-situ leaching of uranium mining is suggested, thus promoting the research and application of uranium isotope systems in the field of earth sciences.

4D printing is a new technology to fabricate active smart materials, which can change the configuration according to environmental stimuli. To obtain shape memory graphene oxide/bisphenol A epoxy acrylate (GO/Bis-A EA) composites with outstanding shape memory properties and significant thermal conductivity, GO was introduced into Bis-A EA to prepare shape memory GO/Bis-A EA composites by light curing. Through the shape recovery and heat transfer experiments, the shape recovery rate and heating rate were tested to characterize the shape memory and heat transfer performance. The relationship between various influencing factors and the properties of composites were investigated, and the optimal fitting model was established to optimize the preparation process by setting shape recovery rate and heating rate as response values. The results showed that when the content of diphenyl (2,4,6-trimethylbenzoyl) phosphine oxide was 4.4%, 1,6-hexanediol diacrylate/Bis-A EA was 0.6, curing power was 40 W, GO content was 0.05%, and curing time was 14 s, the shape recovery rate of the experiments was 87.22% with the heating rate being 0.1532°C/s. The predicted values of shape recovery rate and heating rate inferred by the response surface optimization model were 86.35% and 0.1520°C/s, respectively, which were within 2% error. Through the process optimization research, the 4D-printed shape memory GO/Bis-A EA can achieve excellent shape recovery and heat transfer performance to meet the application of shape memory composites in extreme environments.

The performance of asphalt mixture affects the service of pavement. Nano-alumina was employed as asphalt mixture modification to improve pavement performances. Properties of asphalt mixtures including high-temperature properties, low-temperature properties, water stability properties, and fatigue properties were investigated through rutting tests, dynamic creep tests, low-temperature bending tests, indirect tensile tests, Marshall stability tests, freeze-thaw splitting tests, and indirect tensile fatigue tests. Considering the various performance of nano-alumina-modified asphalt mixture, the optimization decision was made based on 21 sets of performance data, and the optimal dosage of nano-alumina was further clarified. The results demonstrate that nano-alumina improved all properties of asphalt mixtures, except for low-temperature properties. The decision revealed that the performance of the modified asphalt mixture was the most balanced when the content of nano-alumina is 9%. When the optimal dosage of nano-alumina was 9%, the dynamic stability of the asphalt mixture at 60°C was increased by 34.2%, the cumulative permanent strain was reduced by 36.5–49.5%, the water stability performance was improved by 8.3–19.5%, and the fatigue performance was improved by 3.8–7.2%. However, the low-temperature flexural tensile strain was reduced by 2.1% but still meets the specification requirements. Nano-alumina can be used to modify asphalt pavement materials in high-temperature and rainy areas.

In the course of the construction of deep foundation pits during the winter in seasonally frozen areas, the pit wall soil is often unstable due to frost heave and thawing settlement, which leads to hidden safety hazards in engineering construction. Based on the analysis of the deformation data of a pile-anchor supporting a deep foundation pit in Harbin obtained from monitoring during the winter, the influence of freezing and thawing cycles was investigated. The results show that the horizontal displacement in the middle of the shallow layer of the foundation pit is significantly larger than that on both sides during the freeze–thaw cycles, and the spatial effect becomes noticeable. The stress concentration at the external corner of the foundation pit, coupled with the effects of atmospheric precipitation and freeze–thaw cycles, led to the maximum growth rate of horizontal displacement up to 1.40 mm·day−1. The external corner effect is evident from 1 m in the shallow layer of the pit to the depth H/2 of the foundation pit. The support scheme is generally feasible, and we can appropriately enhance the support of the shallow layer of the foundation pit during the freeze–thaw cycles. For similar projects experiencing freeze–thaw cycles, the safety reserve can be appropriately enhanced when carrying out support design.

Low-carbon, green and intelligent production is urgently needed in China’s iron and steel industry. Accurate prediction of liquid steel composition at the end of basic oxygen furnace (BOF) plays an important role in promoting high-quality, high-efficiency and stable production in steelmaking process. A prediction model based on the principal component analysis (PCA) – genetic algorithm (GA) – back propagation (BP) neural network is proposed for BOF end-point P and O contents of liquid steel. PCA is used to eliminate the correlation between the factors, and the obtained principal components are seen as input parameters of the BP neural network; then, GA is employed to optimize the initialized weights and thresholds of the BP neural network. The flux composition and bottom blowing are considered in the input variables. The results indicate that the prediction accuracy of the single output model is higher than that of the dual output model. The root-mean-square error of P content between predicted and actual values is 0.0015%, and that of O content is 0.0049%. Therefore, the model can provide a good reference for BOF end-point control.

Gadolinium neutron capture therapy(GdNCT) is an innovative treatment that exert damage on tumor cells based on the capture reaction between thermal neutron and gadolinium. In comparison with other types of neutron capture therapy(NCT), gadolinium has the highest thermal capture cross section of any natural elements. Gadolinium-based agents are widely used in magnetic resonance imaging(MRI) as contrast agents. The improvements of multiple gadolinium-based agents have been applied to enhance therapeutic efficacy of GdNCT. In this review, principles of gadolinium neutron capture therapy were studied and diverse strategies to improve therapeutic efficacy of gadolinium-based agents were summarized. Giving a perspective on GdNCT to prompt its clinical use.

Based on micro morphology, a thermo-mechanical coupling model of shape memory graphene oxide/epoxy resin (SMGO/EP) was proposed. The heat transfer capability, mechanical property and shape memory ability of shape memory polymer (SMP) were further investigated. The reliability of the modeling was verified by comparing the heat transfer and shape fixation rate of the experimental and simulation data. The results showed that the maximum error of heat transfer was 6.04%, and shape fixing rate error was 2.33%. When the volume fraction of GO was 1.50 vol%, the maximum stress can reach 158.39 MPa, 46.52% higher than that of pure shape memory EP. With the increase in the volume fraction of GO in the SMGO/EP composites, the heat transfer enhancement and recovery rate of SMGO/EP were directly affected by the doping content of GO. The surface temperature of the composites with GO doping content of 1.50 vol% was 20.26°C higher than that of pure SMEP after heating for 300 s. Under the coupling effect of heat transfer and stress characteristics, the mechanism of shape memory effect of SMGO/EP composites was revealed. The thermo-mechanical coupling modeling of SMGO/EP can effectively predict the shape memory characteristics of the SMGO/EP composites.

The number density, size and composition of inclusions in U75V heavy rail steel during ladle furnace (LF)–RH refining process were studied by an Aztec-Feature inclusion automatic software which equipped with a field emission microscope. The results showed that the MnO–SiO2–Al2O3-type inclusions were the main inclusions at LF start. The MnO–SiO2–Al2O3-type inclusions were transformed into the CaO–SiO2–Al2O3-type inclusions during the LF refining process because of the Ca and Al elements which were brought by ferroalloy. At the RH start stage, the main inclusions were CaO–SiO2–Al2O3-type inclusions with low melting temperature and CaO–MgO–Al2O3-type inclusions with high melting temperature in the sample. And, the CaO–MgO–Al2O3-type inclusions were obviously removed during RH vacuum treatment. The average compositions of CaO–SiO2–Al2O3-type inclusions had no obvious change from RH vacuum holding for 15 min, RH vacuum break to RH soft blowing.

Conductive elastomer materials based on carbon black (CB) filled bromo-isobutylene-isoprene rubber (BIIR)/polypropylene (PP) thermoplastic vulcanizate (TPV) were prepared by two step method and one step method. The microstructure, mechanical properties, electrical resistivity, thermal stability, electromagnetic interference shielding performance, and fracture surface morphology of composite materials were studied. The result shows the serious aggregation of CB in one-step TPV, but the uniform dispersion of CB in two-step TPV. In addition, the two-step TPV shows a higher electromagnetic interference (EMI) shielding performance and lower conductivity penetration threshold. The penetration threshold of the two-step TPV is 9.1%, and the maximum reflection loss of the two-step TPV16 is −29.5 dB. Therefore, this research offers an uncomplicated and scalable melt mixing approach method to manufacture conductive thermoplastic vulcanizates with excellent EMI shielding.

The goals of this paper are to study the frost resistance of steel slag concrete (SSC), research the damage mechanisms, and predict the service life of SSC in cold regions. First, the stability of steel slag (SS) was tested, and then SS samples with different treatment dosages were used as aggregates to replace natural aggregates of equal volumes in the preparation of C40 concrete. The microstructures of concrete and micro properties of cement hydration products were investigated in nanospace in this research. In addition, rapid frost resistance durability tests were carried out under laboratory conditions. The results revealed that the ordinary concrete (OC) exhibited a more serious damage phenomenon, and the mass loss and relative dynamic elastic modulus of OC were changed by 5.27 and 62.30%, respectively. However, with increases in the SS content, the losses in mass were lowered. Furthermore, the relative dynamic elastic modulus decreased less, and the frost resistance of the specimens was stronger. The range of mass loss rate was between 2.233 and 3.024%, and the relative dynamic elastic modulus range was between 74.92 and 91.09%. A quadratic function with a good fitting degree was selected to establish a freezing-thawing damage calculation model by taking the relative dynamic elastic modulus as the variable. Then, the freezing-thawing durability lifespan of concrete in the colder regions of northern China was successfully predicted by using the damage calculation model. The results of SSC20–60 showed the better frost resistance durability when the content of SS sand was 20% and the dosage of SS stone was 60%. Its frost resistance lifespan was more than twice that of OC, which demonstrated that SS as an aggregate could effectively improve the frost resistance lifespan of concrete to a certain extent.

HRB500E seismic steel bars are mainly used in high-rise buildings near the seismic zone. The influence of different niobium contents (0–0.023%) on the microstructure and mechanical properties of HRB500E seismic reinforcement was studied. Results showed that the grain size of ferrite was between 3.6 and 8.3 μm when only V was added. Meanwhile, as the niobium content increases, the ferrite particles are further refined. After adding niobium, the grain contribution increased by 9%. The addition of niobium significantly refined the grain size of HRB500E seismic reinforcement. The second-phase nano-elliptic precipitate is NbC. The precipitated phase is dispersed on the grain boundary and the matrix, and the dislocation density on the matrix promotes the precipitation of NbC particles along the dislocation line. The second-phase precipitation of niobium can form an effective pinning effect and then refine the pearlite spacing. The microhardness and the tensile strength also significantly improved. The yield strength increased from 509 to 570 MPa.

In this paper, the microstructure and wear resistance of Zr-17Nb alloy treated by high current pulsed electron beam were studied in detail. A phase change occurs after pulse treatments using X-Ray Diffraction (XRD) analysis, showing β (Nb) phase and α (Zr) phase transformed by a part of β (Zr, Nb) phase. Also, narrowing and shifting of β (Zr, Nb) diffraction peaks were found. Scanning Electron Microscope (SEM) and metallographic analysis results reveal that the microstructure of alloy surface before high current pulsed electron beam (HCPEB) treatment is composed of equiaxed crystals. But, after 15 and 30 pulse treatments, crater structures are significantly reduced. Besides, it was also found that the alloy surface has undergone eutectoid transformation after 30 pulse treatments, and the reaction of β (Zr, Nb) → αZr + βNb had occurred. Microhardness test results show that microhardness value presents a downward trend as the number of pulses increases, which is mainly due to the coarsening of the grains and the formation of a softer β (Nb) phase after phase transformation. The wear resistance test results show that the friction coefficient increases first, then decreases and then increases with the increase of pulse number.

CaO–MgO–Al2O3–SiO2 glass-ceramics with diopside as the main crystalline phase were prepared by melting blast furnace slag obtained from Baotou Iron and Steel Company. The effect of heat treatment on the crystallization behavior of glass-ceramics, containing a large proportion of melted blast furnace slag, was studied by means of differential thermal analysis and scanning electron microscopy. The optimum heat-treatment regime was obtained by orthogonal experimental results for glass-ceramics in which blast furnace slag comprised 70% of the composition and 1% Cr2O3 and 4% TiO2 were used as nucleating agents. The nucleation temperature was 750°C for 2.5 h and the crystallization temperature was 930°C for 1 h. Under this regime, the performance of the glass-ceramic was better than that of other groups in the orthogonal experiment.

This paper studies in-situ synthesis of Fe2O3/reduced graphene oxide (rGO) anode materials by different hydrothermal process.Scanning Electron Microscopy (SEM) analysis has found that different processes can control the morphology of graphene and Fe2O3. The morphologies of Fe2O3 prepared by the hydrothermal in-situ and oleic acid-assisted hydrothermal in-situ methods are mainly composed of fine spheres, while PVP assists The thermal in-situ law presents porous ellipsoids. Graphene exhibits typical folds and small lumps. X-ray diffraction analysis (XRD) analysis results show that Fe2O3/reduced graphene oxide (rGO) is generated in different ways. Also, the material has good crystallinity, and the crystal form of the iron oxide has not been changed after adding GO. It has been reduced, and a characteristic peak appears around 25°, indicating that a large amount of reduced graphene exists. The results of the electrochemical performance tests have found that the active materials prepared in different processes have different effects on the cycle performance of lithium ion batteries. By comprehensive comparison for these three processes, the electro-chemical performance of the Fe2O3/rGO prepared by the oleic acid-assisted hydrothermal method is best.

The accuracy of insulators and their defect identification by UAVs (unmanned aerial vehicles) in transmission-line inspection needs to be further improved, and the model size of the detection algorithm is significantly reduced to make it more suitable for edge-end deployment. In this paper, the algorithm uses a lightweight GhostNet module to reconstruct the backbone feature extraction network of the YOLOv4 model and employs depthwise separable convolution in the feature fusion layer. The model is lighter on the premise of ensuring the effect of image information extraction. Meanwhile, the ECA-Net channel attention mechanism is embedded into the feature extraction layer and PANet (Path Aggregation Network) to improve the recognition accuracy of the model for small targets. The experimental results show that the size of the improved model is reduced from 244 MB to 42 MB, which is only 17.3% of the original model. At the same time, the mAp of the improved model is 0.77% higher than that of the original model, reaching 95.4%. Moreover, the mAP compared with YOLOv5-s and YOLOX-s, respectively, is improved by 1.98% and 1.29%. Finally, the improved model is deployed into Jetson Xavier NX and run at a speed of 8.8 FPS, which is 4.3 FPS faster than the original model.

Refill friction stir spot welding (RFSSW) was used to join 6061-T6 and 7075-T6 aluminum alloys in this work. Different sheet configurations and welding parameters were used to optimize joint strength. The effect of sleeve plunge depth on the microstructure and mechanical properties of the joints were investigated. The results showed that no defects were obtained when 6061-T6 aluminum alloy was placed as the upper sheet. The lap shear failure load of the joint using 6061-T6 aluminum alloy as the upper sheet was higher than that using 7075-T6 as the upper sheet. The maximum failure load of 12,892 N was attained when using the sleeve plunge depth of 3.6 mm. The joint failed at the upward flowing 7075 near the hook.

The effects of MgO, Al2O3, C/S (CaO/SiO2) and FeO on the viscosity and the liquidus temperature (TLQ) of blast furnace (BF) primary slag were analyzed by using multiphase equilibrium. The results show that the TLQ of primary slag exhibits a minimum value at 12 wt% Al2O3 and 14 wt% Al2O3 when MgO contents are 8 wt% and 10 wt%, respectively. It can be suggested that the content of MgO in primary slag is prone to be retained at different value when Al2O3 is different for smooth operation. The suitable value of MgO/Al2O3 ratio increases with the increase of Al2O3 content from 10 wt% to 18 wt% in the primary slag and the proper MgO/Al2O3 ratio is 0.4–0.55. The TLQ of the slag increases with the increase of C/S when Al2O3 content is lower than 14 wt%, while it decreases with the increase of the C/S when Al2O3 is higher than 14 wt%. The slag viscosity decreases with the increase of FeO content. The isoviscosity curves become closer and closer when FeO is in a low level. In the condition of the high Al2O3 content, improving the reduction degree of iron ore in the upper area of the BF can achieve a lower TLQ and have a smooth operation.

Plasma-sprayed cast iron splats were deposited onto polished aluminum substrates preheated to different temperatures ranging from 25°C to 250°C. The morphology of single splat was observed by a field emission scanning electron microscope. Quantitative characterization methods, including fractal dimension (FD) and circularity analyses of the splat profile, were employed to identify the difference in morphology of the splats with the change of the substrate temperature. The results showed that the substrate temperature has a significant effect on the spreading of molten droplets and the morphology of resultant splats through changing the solidification rate of the droplets. With the increment of substrate temperature, the homogeneous and sufficient spreading of the droplets resulted from low solidification rate reduces the splashing of the droplets. In addition, the evaporation of adsorbed moisture on the substrate improves the wettability between the spreading droplet and the substrate, then benefits the homogeneous spreading of the molten droplet. As a result, a distinct decline in the FD value was observed. It was also suggested that the FD analysis could be used to characterize the morphology of the splat more effectively while the circularity method was heavily dependent on the area of the splat.

Blast furnace heat is the key to the blast furnace’s high efficiency and stable operation, and it is difficult to maintain a suitable temperature for large blast furnace operations. When designing the furnace heat prediction and control model, parameters with good reliability and measurability should be chosen to avoid using less accurate parameters and to ensure the accuracy and practicability of the model. This paper presents an effective model for large blast furnace temperature prediction and control. Using thermal equilibrium and the carbon-oxygen balance of the blast furnace’s high-temperature zone, the slag-iron heat index was calculated. Using the relation between the molten iron temperature and slag-iron heat index, the furnace heat parameter can be calculated while production conditions are changed,which can guide furnace heat control.

When performing multiple target detection, it is difficult to detect small and occluded targets in complex traffic scenes. To this end, an improved YOLOv4 detection method is proposed in this work. Firstly, the network structure of the original YOLOv4 is adjusted, and the 4× down-sampling feature map of the backbone network is introduced into the neck network of the YOLOv4 model to splice the feature map with 8× down-sampling to form a four-scale detection structure, which enhances the fusion of deep and shallow semantics information of the feature map to improve the detection accuracy of small targets. Then, the convolutional block attention module (CBAM) is added to the model neck network to enhance the learning ability for features in space and on channels. Lastly, the detection rate of the occluded target is improved by using the soft non-maximum suppression (Soft-NMS) algorithm based on the distance intersection over union (DIoU) to avoid deleting the bounding boxes. On the KITTI dataset, experimental evaluation is performed and the analysis results demonstrate that the proposed detection model can effectively improve the multiple target detection accuracy, and the mean average accuracy (mAP) of the improved YOLOv4 model reaches 81.23%, which is 3.18% higher than the original YOLOv4; and the computation speed of the proposed model reaches 47.32 FPS. Compared with existing popular detection models, the proposed model produces higher detection accuracy and computation speed.

The bidirectional reflection distribution function (BRDF) is among the most effective means to study the phenomenon of light–object interaction. It can precisely describe the characteristics of spatial reflection of the target surface, and has been applied to aerial remote sensing, imaging technology, materials analysis, and computer rendering technology. This study provides a comprehensive review of the development of devices to measure the BRDF. We gathered research in the area by using the Web of Science Core Collection, and show that work on the BDRF has been ongoing in the last 30 years. We also describe some typical measurement devices for the BRDF proposed in the literature. Finally, we summarise outstanding problems related to BRDF measurement and propose directions of future research in the area.

Electrochemical corrosion behavior of Sn-containing Al–Zn–Mg aluminum alloy has been studied in detail. The localized corrosion behaviors were studied by electrochemical impedance spectroscopy (EIS) analysis, and the potentiodynamic polarization measurements. The grain structure, grain-boundary microstructure, grain-boundary microchemistry, pitting and intergranular corrosion morphology were characterized and observed using SEM, EDS, TEM, SAED and HRTEM analyses. Based on these tests, the effects of grain-boundary on the corrosion resistance in our Sn-containing Al–Zn–Mg alloys before/after bake hardening were analyzed systematically. Finally, the relationship between chemical composition, microstructure evolution and corrosion behaviour was revealed. The results indicate that the bake hardening process improves the corrosion resistance compared to the pre-aging state. The grain size has little effect on the electrochemical corrosion bahavior.

Superconducting Bi _1.68 Pb _0.32 Sr _1.75 Ca _1.85 Cu _2.85 O _10+ _y (Bi-2223) powders were prepared by a conventional solid-state reaction using hand grinding and wet ball milling. The effects of the ball milling and sintering times on the phase evolution were examined by x-ray diffraction and magnetic susceptibility measurements. Single-phase Bi-2223 powders with a superconducting transition temperature of about 108 K were optimally prepared by wet ball milling for 20 h and sintering at 867 °C for 80 h. Finding these optimal preparation conditions were crucial for mass producing high-quality single-phase Bi-2223 precursor powders with a much lower cost of energy. Furthermore, we found that ball milling led to thinner grains than hand grinding.

The spallation behavior of oxide scale on the surface of low carbon microalloyed steel (510L) is investigated during the laminar cooling of hot rolling strip. Surface, cross-section morphology and phase composition of oxide scale in different laminar cooling rate are observed by scanning electron microscopy (SEM) and X-Ray Diffraction (XRD). Moreover, a spallation mathematic model is established based on empirical formula to predict the critical thickness of oxide scale and the test of high temperature oxidation kinetics at different temperatures between 500 °C to 900 °C provides oxidation rate constant for the model calculation. The results of heat-treatment test and model calculation reveal that laminar cooling rate plays an important role in controlling the thickness of oxide scale and suppressing spallation behavior.

In order to realize comprehensive and massive treatment of boron mud secondary resource, fundamental study on boron mud applied to oxidized pellets production as additive was carried out in the paper under laboratory conditions. The effects of boron mud on the performance of oxidized pellets were investigated systemically, and boron mud was combined with other boron-rich material innovatively. The results showed that, within certain limits, boron mud can improve properties of oxidized pellets. The bentonite content decreased to 0.3 % when adding 1.0 % boron mud additive and the pellets met blast furnace requirements. With the combination additive content 0.8 %, bentonite content can be further decreased to 0.2 %, and the pellets properties were better than base pellet. Therefore, it was an effective way to reduce environmental pollution and optimize blast furnace operation by developing boron mud secondary resource as pellets additive.

Based on the fundamental characteristics of high chromium vanadium-titanium magnetite (HCVTM), the effects of roasting temperature and roasting time on the phase transition and oxidation consolidation during the oxidation were investigated systematically. It was shown that the oxidation of HCVTM pellet was not a simple process but complex. With increasing roasting temperature and time, the compressive strength of oxidized pellet was improved. The phase transition during oxidation was hypothesized to proceed as follows: (1) Fe3O4 → Fe2O3; (2) Fe2.75Ti0.25O4 → Fe9TiO15 + FeTiO3 → Fe9TiO15 + Fe2Ti3O9; (3) Fe2VO4 → V2O3 → (Cr0.15V0.85)2O3; (4) FeCr2O4 → Cr2O3 → Cr1.3Fe0.7O3 + (Cr0.15V0.85)2O3. The oxidation consolidation process was divided into three stages: (1)oxidation below 1,173 K; (2) recrystallization consolidation at 1,173 – 1,373 K; (3) particle refining recrystallization-consolidation by the participation of liquid phase at 1,373 – 1,573 K. To obtain the HCVTM oxidized pellet with good quality, the rational roasting parameters included a roasting temperature of 1,573 K and a roasting time of 20 min.

Effects of temperature and slag composition on dephosphorization in a 120 ton top-bottom combined blown converter steelmaking process by double slag method were studied. The slag properties were determined by scanning electron microscope- energy dispersive spectrometry (SEM-EDS), X-ray diffraction (XRD). The results show that the transition oxidation temperature between dephosphorization and decarbonization Tf is not the favorable temperature for the first deslagging. The optimum first deslagging temperature is confirmed to be approximately 1,673 K which is about 70 K higher than Tf. High melting temperatures phases (such as 3CaO·SiO2) in the slag with high basicity and MgO content are unfavorable to the dephosphorization. The optimum process condition for dephosphorization at the first deslagging in present work is approximately 1,673 K in temperature, 2.0 in slag basicity, 6 and 17 mass% in MgO and T.Fe content, 6 mass% ≤ MnO content.

Hydrous hydrazine (N2H4∙H2O) is a candidate for a hydrogen carrier for storage and transportation due to low material cost, high hydrogen content of 8.0%, and liquid stability at room temperature. Pt and Pt nanoalloy catalysts have been welcomed by researchers for the dehydrogenation of hydrous hydrazine recently. Therefore, in this review, we give a summary of Pt nanoalloy catalysts for the dehydrogenation of hydrous hydrazine and briefly introduce the decomposition mechanism of hydrous hydrazine to prove the design principle of the catalyst. The chemical characteristics of hydrous hydrazine and the mechanism of dehydrogenation reaction are briefly introduced. The catalytic activity of hydrous hydrazine on different supports and the factors affecting the selectivity of hydrogen catalyzed by Ni-Pt are analyzed. It is expected to provide a new way for the development of high-activity catalysts for the dehydrogenation of hydrous hydrazine to produce hydrogen.

Hydrogen energy is considered to be a desired energy storage carrier because of its high-energy density, extensive sources, and is environmentally friendly. The development of hydrogen storage material, especially liquid organic hydrogen carrier (LOHC), has drawn intensive attention to address the problem of hydrogen utilization. Hydrogen carrier is a material that can reversibly absorb and release hydrogen using catalysts at elevated temperature, in which LOHC mainly relies on the covalent bonding of hydrogen during storage to facilitate long-distance transportation and treatment. In this review, the chemical properties and state-of-the-art of LOHCs were investigated and discussed. It reviews the latest research progress with regard to liquid organic hydrogen storage materials, namely N-ethylcarbazole, and the recent progress in the preparation of efficient catalysts for N-ethylcarbazole dehydrogenation by using metal multiphase catalysts supported by carbon–nitrogen materials is expounded. Several approaches have been considered to obtain efficient catalysts such as increasing the surface area of the support, optimizing particle size, and enhancing the porous structure of the support. This review provides a new direction for the research of hydrogen storage materials and considerations for follow-up research.

The polarization and strain response of electrically poled lead zirconate titanate ceramics was reinvestigated under low-to-medium electric field loading. A phenomenon that is usually ignored was pointed out and discussed. That is, under low-to-medium cyclic electric field loading, remnant strains measured under a negative electric field loading are larger than those measured under a positive electric field loading. Here, ‘positive’ and ‘negative’ mean that the applied electric field is aligned or antiparallel to the pre-poling direction of the material, respectively. Moreover, a reverse trend was observed for remnant polarizations. Texture-dependent domain switching, defect dipole reorientation, and interactions between them were used to rationalize this phenomenon. In addition, the equation ${\rm{S}}\,=\,\left({{\rm{d}}}_{{\rm{init}}}+\alpha {{\rm{E}}}_{{\rm{0}}}\right)\ast {\rm{E}}\pm \tfrac{\alpha }{{\rm{2}}}\left({E}_{0}^{2}-{E}^{2}\right),$ which is used to describe the strain response, was modified by taking the asymmetry of the electric field versus strain curve into consideration. The modified equation can better describe the strain response than the original equation.

In this study, a hyperspectral imaging system of 866.4−1701.0 nm was selected and combined with multivariate methods to identify wheat kernels with different concentrations of omethoate on the surface. In order to obtain the optimal model combination, three preprocessing methods (standard normal variate (SNV), Savitzky−Golay first derivative (SG1), and multivariate scatter correction (MSC)), three feature extraction algorithms (successive projections algorithm (SPA), random frog (RF), and neighborhood component analysis (NCA)), and three classifier models (decision tree (DT), k-nearest neighbor (KNN), and support vector machine (SVM)) were applied to make a comparison. Firstly, based on the full wavelengths modeling analysis, it was found that the spectral data after MSC processing performed best in the three classifier models. Secondly, three feature extraction algorithms were used to extract the feature wavelength of MSC processed data and based on feature wavelengths modeling analysis. As a result, the MSC−NCA−SVM model performed best and was selected as the best model. Finally, in order to verify the reliability of the selected model, the hyperspectral image was substituted into the MSC−NCA−SVM model and the object-wise method was used to visualize the image classification. The overall classification accuracy of the four types of wheat kernels reached 98.75%, which indicates that the selected model is reliable.

In the recovery of low permeability reservoir, the capillary pressure has an important effect, which may reduce gas production. Due to the capillary end effect, there are two flow patterns in the vicinity of the production well: both water and gas phases can flow into the production well and only gas phase can enter the production well. Based on the analytical equations of one-dimensional radial flow considering the capillary end effect, an alternative numerical well model for low permeability gas reservoir is constructed. Numerical examples show that the proposed model can reflect the dramatic change for saturation and gas-phase pressure in the vicinity of the production well both for two flow patterns, and therefore can predict the gas and water productions accurately at different grid scales. In contrast, the original Peaceman well model for multi-phase flow, which is directly extended from that for single-phase flow, only can provide good prediction under the condition of that the grid size is enough small. Especially, for the original Peaceman well model, this problem is out of control since it is difficult to estimate a suitable grid size.

A novel and efficient oxidation of salicyl alcohols to the corresponding salicylaldehydes catalyzed by lipase is reported for the first time. Under the optimal reaction conditions, the method exhibited high yields (81–95%) and selectivities for salicylaldehydes. Moreover, this study expands the application of enzyme catalytic promiscuity in organic synthesis.

Hydrogen sulfide (H2S) has attracted attention in biochemical research because it plays an important role in biosystems and has emerged as the third endogenous gaseous signaling compound along with nitric oxide (NO) and carbon monoxide (CO). Since H2S is a kind of gaseous molecule, conventional approaches for H2S detection are mostly based on the detection of sulfide (S2−) for indirectly reflecting H2S levels. Hence, there is a need for an accurate and reliable assay capable of determining sulfide in physiological systems. We report here a colorimetric, economic, and green method for sulfide anion detection using in situ formation of silver nanoparticles (AgNPs) using dopamine as a reducing and protecting agent. The changes in the AgNPs absorption response depend linearly on the concentration of Na2S in the range from 2 to 15 μM, with a detection limit of 0.03 μM. Meanwhile, the morphological changes in AgNPs in the presence of S2− and thiol compounds were characterized by transmission electron microscopy (TEM). The as-synthetized AgNPs demonstrate high selectivity, free from interference, especially by other thiol compounds such as cysteine and glutathione. Furthermore, the colorimetric sensor developed was applied to the analysis of sulfide in fetal bovine serum and spiked serum samples with good recovery.