Thiacalix[4]arene ligands have the advantages of high recognition, derivatization, excellent stability and other advantages. Lanthanide (Ln) ions can coordinate with thiacalix[4]arene ligands to form multi?functional coordination clusters, which received increasing attention due to their unique catalytic, magnetic, optical properties. Thiacalix[4]arene can sensitize Ln ions to luminescence by the coordination of phenol and S groups via the "Antenna effect". This paper reviewed recent advances in structures, luminescent properties, and applications of luminescent Ln?thiacalix[4]arene complexes.

Polylactic acid/Poly(butylene adipate?co?terephthalate)/Poly(methyl methacrylate)?b?poly (butyl acrylate)?b?poly (methyl methacrylate)ternary blends (PLA/PBAT/MAM) were prepared by melt blending, and the effect of MAM relative molecular weight on the morphology, structure and properties of the blends was investigated. The results showed that the addition of MAM block copolymer can inhibits the crystallization of PLA，improve the compatibility of PLA/PBAT, reduce the particle size of the dispersed phase and make the distribution more uniform, improve the impact properties and elongation at break of the blends. And the relative molecular weight of MAM increased, the impact strength and elongation at break of the blend increased, the smaller the size of the dispersed phase particles, and the more uniform of particle size distribution.

Pollution caused by petroleum?based plastic products has become a problem that is difficult for human beings to solve, and the existing treatment methods are both energy?consuming and easy to cause secondary pollution. The study found that the bacteria that degrade plastic in the intestines of Galleria mellonella (Lepidoptera: Pyralidae) larvae can effectively accelerate the degradation of plastics. This experiment uses polystyrene (PS) packaging boxes, which are common in life, as the only food source to feed the larvae of the large wax borer, enriching the PS?degrading bacteria in the intestines of the G. mellonella larvae. After dissection, culture, and isolation, four strains were obtained: PD?1, PD?2, PD?3 and PD?4. The degradation capacity of MSM culture medium with PS film as the only carbon source was inoculated with each strain, and the degradation rate of PD?1 on PS film was the highest, which was 1.8%. PD?1 was observed by strain morphology, physiological biochemical determination and phylogenetic tree construction, and it was identified as Enterobacter colebella (Klebsiella). Meanwhile, the method of UV and nitric acid pretreatment of PS film were used to improve the degradation rate of the strain, and the results showed that the weight loss rate of PD?1 degradation of nitric acid?treated PS film was improved, which was 2.5%, while the UV group was 0.8%, indicating that PS film was more easily degraded by PD?1 after nitric acid treatment.

Li₂ZnTi₃O₈ (LZTO) anodes of lithium?ion batteries have been prepared by a sol?gel method. The effects of the calcination temperature and time on the electrochemical performance have been studied for LZTO in detailed. The optimum calcination temperature and time are 700 ℃ and 3 h, respectively. On the basis of the optimum preparation process, citric acid as the chelating agent has been introduced into the synthesis to modify LZTO. When the molar ratio of metal ions to citric acid is 2.00∶1.50, the obtained product is denoted as LZTO?2/1.50, which has small particle size, good dispersion, and then shows good electrochemical performance. The discharge specific capacity is 203.6 mA·h/g after 300 cycles at the current density of 0.5 A /g for LZTO?2/1.50.

The Fe/Mo ordering at B?sites of Ba₂FeMoO_6-δ (BFM) were changed by adjusting Fe/Mo amount of substance ratio (i.e., stoichiometric ratio), and then a new double?perovskite anode material Ba₂Fe_1.3Mo_0.7O_6-δ (BFM_0.7) for SOFC were obtained. The results indicated that the electrical conductivity of the BFM_0.7 anode is 15.0~20.0 S/cm at 600~800 ℃ in H₂, which is much larger than that of the lowest target for SOFC electrode (0.1 S/cm). The peak power density and polarization resistance of the BFM_0.7 anode cell attained 1 149 mW/cm² and 0.15 Ω·cm² at 850 ℃. Compared with BFM anode, the performance of BFM_0.7 is significantly improved. In addition, the performance of BFM_0.7 anode cell showed no degradation after testing for 39 h, indicating that the BFM_0.7 anode possesses has excellent electrochemical stability.

Monolayer Janus transition metal disulfides have low dimension, high mobility, and peculiar electronic structure properties, which have potential applications in electronics and optoelectronic devices. In devices made of monolayer Janus transition metal disulfide and substrate materials,are usually stressed due to lattice mismatch between monolayer Janus transition metal disulfides and substrate, it is significant to study the strain effect on physical properties of monolayer Janus transition metal disulfides through Raman scattering.This paper systematically investigate the biaxial strain effect on the atomic structure, electronic structure and Raman spectra of monolayer Janus MoSSe. The results show that monolayer Janus MoSSe can exhibit a band gap transition from direct to indirect one under biaxial strain, due to both the energy shift of bonding orbitals between the top of the valence band and the bottom of the conduction band and the sensitivity to strain. This paper also thoroughly study the strain effect on the Raman shift and intensity of monolayer Janus MoSSe. It is found that under biaxial strain modulation from decreasing compressive to increasing tensile, for the Raman shift, the three peaks of E¹, E², and A {}_{\mathrm{1}}^{\mathrm{1}} red?shift, while the peak of A {}_{\mathrm{1}}^{\mathrm{2}} blue?shifts abnormally with decreasing compressive strain; for the intensity, the peak intensity of the doubly?degenerate modes (E¹,E²) increases monotonically, while singly?degenerate modes shows the opposite trend, except for the A {}_{\mathrm{1}}^{\mathrm{1}} which intensity decreases with decreasing compressive strain and then increases with tensile strain. This paper propose a simple model to comprehend the strain effect. This theoretical study may supply an effective means to quickly and quantitatively characterize the strain size and type in Janus materials through the frequency difference and intensity ratio between typical Raman peaks.

At present,there are few studies on the influence of medium and low water saturation on the capacity of free gas storage.Therefore, this study simulates the multi?round gas injection?soaking?production process through laboratory experiments; The laboratory experiment was carried out to simulate the process of multi?round gas injection?well soaking?production. Combined with the mathematical model and numerical simulation results, the research shows that the reservoir capacity increases with the increase of injection?production rounds, but the increase after single?round injection?production decreases rapidly.When the initial water saturation is higher than 50%, the increase of water saturation is beneficial to the reconstruction of gas storage, but the increase of injection?production capacity and storage capacity is relatively slow in the early stage of reservoir construction. When the initial water saturation is increased from 50% to 85%, the gas saturation is reduced by about 9.27% after 6 injection?production cycles. When the injection?production cycles are increased to 20,30,50 cycles, the free gas storage capacity is increased by about 0.51%,3.33%,6.61%, respectively. The research results are expected to provide reference for the evaluation of injection?production capacity and storage capacity of reservoir?type gas storage.

In recent years, with the continuous increase of foreign crude oil imports and the decline of domestic oilfield production, different oil products may need to be transported together by the same oil pipeline during the transportation process.The fourth oil pipeline of Qingtie is taken as an example. Combined with the actual parameters, the pipe wall is discretized by using the finite element analysis method of ANSYS and the hexahedral structural grid. The thermal structure coupling problem of the buried pipeline is solved, and the corresponding thermal stresses of the straight pipe section and the bent pipe section at different temperatures are calculated respectively. Based on the theory of fracture mechanics,the number of annual limit cycles under different service life is calculated, and the influence of temperature alternation on pipeline fatigue life is analyzed, which provides a theoretical basis for the safe transportation of cold and hot crude oil pipelines.

Aiming at the bond?slip behavior of reinforced concrete, the finite element model of reinforced concrete bond?slip based on cohesion model was constructed by ABAQUS finite element software. The mesh sensitivity and cohesion parameter sensitivity of the simulation model were explored by energy and load?displacement curves. Aiming at the problem of bond strength of reinforced concrete, a nonlinear autoregressive exogenous network (NARX) was developed to predict the load?displacement curve for reinforced concrete by creating 20 sets of data with the variables of bond length, reinforcement diameter, and loading method. The study shows that the mesh size of 6 mm provides an ideal balance between prediction accuracy and computational cost. Based on the sensitivity of the finite element prediction results, the cohesive parameters are in the sequence of damage initiation strength, fracture energy, and stiffness. The NARX with the prediction accuracy of 99.6% is promising to replace time?consuming numerical simulations and experimental works to achieve an efficient and accurate prediction of the bond strength of reinforced concrete. Such an efficient and accurate prediction method provides a novel and convenient methodology of predicting and designing the bond strength of reinforced concrete.

Billets have oxidized layers and defects on their surface due to the production process, so they must be surface?regulated by grinding. There is no special equipment for surface regrinding of large square steel billets; a square steel regrinding equipment was designed. Kinematic simulation verification was completed using ADAMS software. The results show that the regrinding equipment can simultaneously and smoothly complete the grinding operation on two adjacent surfaces. Using finite element software ANSYS to carry out stress analysis and modal analysis of the regrinding machine under load, and improve the structure; according to the simplified kinematic model, static analysis was carried out to get the required input driving torque, and the selection of the critical components of the spring was completed. Theoretical calculations and simulation results show that this regrinding machine can efficiently grind the surface of large square billets.

The paper aims to study the problem of obstacle avoidance in air?ground cooperative tracking control for the unmanned aerial helicopter (UAH),in which a new approach of designing the path obstacle avoidance plan and controller design is proposed.Initially, as for the uncertain linear UAH,by processing and judging two?dimensional environmental information within the warning range for the UAH,an obstacle avoidance strategy is proposed with the help of wall?following algorithm,and the flight angle of obstacle avoidance path and the tracking speed that can make up for bypass distance are calculated.Secondly,the proposed obstacle avoidance method is extended to the three?dimensional case,and the flight angle of the UAH is determined based on the obstacle information in the horizontal and vertical directions,which can reduce the bypass distance caused by the obstacle avoidance link as possible.Thirdly,based on two derived obstacle avoidance algorithms above,the artificial neural network (ANN) is introduced to estimate model uncertainty,and then the tracking control design schemes are established by using feedforward compensation and optimal control technologies.some simulations demonstrate the effectiveness of the proposed obstacle avoidance strategy and control algorithm.

The COVID?19 epidemic is facing the influence of a variety of complex practical factors, which makes the development of the epidemic uncertain. In order to overcome the problem of large error in epidemic forecasting results due to the limitations of many ideal assumptions based on the infectious disease compartment model, a time series forecasting model based on deep learning is adopted to predict the epidemic development, and an informer model based on transformer model is established. Attention mechanism and distillation mechanism are applied to the time series forecasting of epidemic data. The threshold autoregressive (TAR) model and a variety of mainstream recurrent neural time series prediction models are used as comparison models. Through simulation experiments, the current number of remaining infections in the epidemic data of China, America and Britain is predicted in the short term, and RMSE and MAE are used as evaluation indicators, and then the best model is selected for medium ? and long?term prediction. The experimental results show that the indicator value of the informer model is optimal in both RMSE and MAE, further indicating that the prediction accuracy of the informer model is higher than that of other comparative models in China, America and Britain. Finally, the Informer model is used for the development of the epidemic in China，America and Britain medium and long?term prediction.

With the improvement of environmental uncertainty, the demand for supply chain stability of petrochemical enterprises in China is rising day by day. The evaluation of supply chain resilience of petrochemical enterprises has become an important means to judge the risk coping ability of petrochemical enterprises. This paper constructs a supply chain resilience evaluation index system in the petrochemical enterprises. And fuzzy analytic hierarchy process and BP neural network are used to evaluate the toughness strength of petrochemical enterprise supply chain, so as to determine the toughness level of petrochemical enterprise supply chain.It is found that the strength of supply chain toughness of petrochemical enterprises is uneven, and the overall level of supply chain resilience is low. On the basis of the research results, some practical suggestions are put forward for the forging of resilient supply chain in petrochemical enterprises.

Gasoline molecular blending technology on?line requires rapid access to detailed molecular composition information of various types of component oils. In this paper, an autoencoder?based method for the rapid resolution of gasoline molecular composition is developed, which can directly predict the detailed monomeric hydrocarbon composition of gasoline from near?infrared spectra. The constructed autoencoder model of gasoline molecular composition can explore the potential features and recover the original molecular composition by decoding the potential features. The artificial neural network algorithm is used to correlate the NIR spectral information with the potential features of gasoline composition. The accuracy of the model is verified by using hydrogenated gasoline with the average absolute error is 0.033. The model developed in this work applies the current popular autoencoder algorithm to the traditional petrochemical process, which is an important guideline for blending online and real?time optimization of gasoline molecules.

The direct method was used to prepare polyurea lubricating grease, and the effects of several different types of additives on the extreme pressure and anti?wear performance for polyurea lubricating grease were investigated and studied. The results demonstrate that several types of additives have good compatibility with polyurea grease, and they have little undesirable influence on colloidal stability of polyurea grease, and they can also enhance thermal stability of polyurea grease. Moreover, the addition of additives can significantly improve the performance of extreme pressure and wear resistance for polyurea lubricating grease. And in the experiments, it was found that the composite multifunctional additive containing sulfur and phosphorus has a relatively better effect on improving the extreme pressure and wear resistance of polyurea lubricating grease. The research results can provide a reference basis for the improvement of extreme pressure and anti?wear property for polyurea lubricating grease, achieving a relatively optimized comprehensive performance, thereby enhancing its practical utilization performance under the harsh working conditions for high load and high speed mechanical equipment.

Aerobic oxidative desulfurization is a safe and environmentally friendly desulfurization method, but oxygen usually needs to be activated under harsh conditions, the synthesis of efficient catalyst is an effective way to improve desulfurization activity. In this work, flower?like cobalt molybdate with large specific surface area was synthesized by one?step hydrothermal method using cobalt chloride and ammonium molybdate as raw materials. In addition, urea is used as precipitation agent and structure control agent. The morphology and structure of the CoMoO₄ were characterized by FT?IR, XRD, SEM, XPS and N₂ adsorption desorption techniques. Dibenzothiophene in simulated oil was removed using CoMoO₄ as catalyst and molecular oxygen as oxidant. The effects of reaction temperature, the flow of oxygen, the amount of CoMoO₄ and the type of sulfur compounds on the desulfurization rate were investigated. In addition, the recycling performance of flower?like CoMoO₄ was studied. The experiment shows that the desulfurization rate can reach 98.2% under the optimal reaction conditions. The catalyst can be reused for 5 times without significant reduction in oxidative desulfurization activity. The formation of superoxide radical in the oxidation desulfurization process resulting in high desulfurization activity.

As an electrochemical inert cation, Mg²⁺ has an ionic radius (0.072 nm) similar to that of Li⁺ (0.076 nm), which is widely used to replace Li⁺ in Li?rich layered oxides (LLOs) materials. However, the influence of Mg²⁺ on the crystal structure of LLOs materials is still controversial. In this work, the Mg?doped Li?rich cathode materials Li_1.2-x Mg _x Mn_0.54Ni_0.13Co_0.13O₂ were synthesized by a sol?gel and high?temperature calcination method. The crystal structure, and valence state of elements in synthesized materials were systematically studied via X?ray diffraction, and X?ray photoelectron spectroscopy. These results indicated that Mg²⁺ doping can increase the cell parameters of LLOs materials. At the same time, compared with Li_1.2Mn_0.54Ni_0.13Co_0.13O₂, Mg?doping can effectively improve the electrochemical performance of LLOs materials. After optimization, the Mg?0.03 sample exhibits anomalous electrochemical performance, that is, the initial discharge?specific capacity is 291.9 mA?h/g and the initial coulomb efficiency is 78.40%.

A new type of Ruddlesden?Popper cobalt?rich layer perovskite oxide La_1.5Ca_0.5Ni_0.2Co_0.8O_4+δ (LCNC) was synthesized by a sol?gel process. The results show that the conductivity of LCNC in air at 400 ℃ to 800 ℃ is 4~58 S/cm, which is better than that of most reported SOFC cathode materials. The polarization impedance of symmetrical battery LCNC|LSGM|LCNC is 0.16 Ω·cm² at 800 ℃. The maximum power density of the single cell supported by 300 μm thick La_0.9Sr_0.1Ga_0.8Mg_0.2O_3-δ (LSGM) with the LCNC cathode was 527 mW/cm², and the performance of the single cell decreases slightly after working continuously for 50 hours. The experimental results show that LCNC is a potential SOFC cathode material.

In order to understand the mechanism of CO₂ dissolved buried mechanism in high temperature and high pressure porous environment,physical simulation experiment was conducted to study CO₂ dissolved buried mechanism,mineralization buried mechanism and free buried mechanism in porous media by means of indoor physical model experiment.The results show that the solubility of CO₂ in formation water is mainly affected by temperature, pressure and salinity of formation water. CO₂ dissolved in formation water will mineralize with minerals in rocks, and the mineral content of rocks will change significantly before and after the reaction. The long core displacement experiment characterized the amount of free CO₂ storage and the oil displacement effect. The experiment reveal that CO₂ flooding in porous media has dual effects of burying and enhancing oil recovery.

In order to study the influence of cross?fracture on the mechanical properties and damage modes of deep shale, and better understand the damage evolution law of shale containing cross?fracture under high temperature and high pressure coupling, 15 groups of shale models containing cross?fracture with different inclination angles were established, and simulation experiments were carried out to study the stress?strain relationship, damage evolution and acoustic emission characteristics of the shale specimens. The results show that the compressive strength and modulus of elasticity of shale are negatively correlated with the inclination angle of the main cracks, and show an upward concave trend with the increase of the inclination angle of the secondary cracks, and the compressive strength of shale decreases significantly when there are cracks perpendicular to or close to perpendicular to the loading direction; the damage modes of shale specimens under the influence of cross?cracks are mainly divided into "X"?shaped damage, diagonal "N"?shaped damage, diagonal "W"?shaped damage, inverted "V"?shaped damage, damage along the main crack, "V"?shaped damage and "λ"?shaped damage; the fractal dimension of shale specimens is negatively correlated with the inclination angle of the main crack, and as the inclination angle of the main crack decreases, the value of fractal dimension tends to increase, and the corresponding damage pattern of the specimens is more complicated and the internal damage is more intense.

The Cu plate was fabricated by a novel grinding tool via multiple rotational grinding under deep cooling condition. The surface morphology, microstructures and properties of the grinding zone were analyzed via super depth of field microscope, optical microscope, friction and wear test, respectively. The results show that well surface formation and ultrafine grains were obtained after multiple rotational grinding under deep cooling condition. Combined with the temperature distribution simulation, the main grain refinement mechanism of 50 r/min is the breaking and split of the grain. The grain refinement mechanism at 500 r/min is dynamic recrystallization and forced cooling to inhibit the growth of recrystallized grains. Microhardness tests and wear tests showed that the ultrafine?grained zone prepared by multiple rotational grinding under deep cooling condition could improve the wear resistance of the materials.

Copper nickel alloys have excellent corrosion resistance and mechanical properties, therefore it is widely used in marine engineering. However, due to its complex service environment, copper nickel alloys are prone to corrosion and leakage, resulting in irreversible losses. A corrosion?resistant conversion film was prepared on the surface of copper nickel alloy to improve its corrosion resistance performance; Electrochemical impedance, Tafel polarization curve, scanning electron microscopy, and energy spectrum analysis were performed, and the surface covered corrosion products of the conversion film were observed by X?ray photoelectron spectroscopy (XPS). The results showed that when the B10 copper nickel alloy sample was immersed in a solution containing molybdate for 120 minutes, the solution transfer resistance (R_ct) and membrane resistance (R_p) reached their peak values, and the corrosion inhibition rate was as high as 92.5%; the conversion film contains copper and nickel oxides as well as hydroxides, while molybdenum exists in the form of +4 and +6 valence oxides.

The data of chemical processes often contains dynamic timing characteristics, and traditional fault detection has low usage of dynamic information, which limits the fault diagnosis performance. To address this problem,a new method of chemical process fault diagnosis based on an attention?enhanced encoder?decoder network model (AEN) was proposed. The coding part uses the LSTM to extract the feature information of the process data and combine it with the attention mechanism to utilize the dynamic information among the process data more effectively； the decoding part uses the LSTM and combines the context vector provided by the attention mechanism to provide more accurate state information for the softmax regression, and finally, the softmax regression is used to obtain the probability value of the fault category for each sample data. The introduction of the attention mechanism improves the efficiency of the model in using process dynamic information in the time domain. The proposed method is experimented with using Tennessee Eastman process data and compared with the results of standard PCA?SVM, DBN and ResNet, and the results show that the proposed method is more effective in diagnosing faults.

Magnetic tomography method has been widely used for nondestructive external inspection of buried and submarine pipelines, which is based on the principle of metal magnetic memory to discern the danger level and location of the stress concentration zone by measuring the anomalies in the spatial magnetic field distribution outside the pipeline. The distribution characteristics and spatial propagation law of pipeline inspection signal detected by magnetic tomography method, the energy distribution and change law of spatial magnetic memory signal in the stress concentration zone of magnetized pipelines are studied in this paper. The magnetic dipole field is used to establish the magnetic field model in the stress concentration zone of the inner wall of the pipeline, and the magnetic energy and energy density of spatial magnetic memory signals under different lift?off values outside the pipeline are finite element calculated based on the magnetic energy theory to derive the distribution law of spatial magnetic field and the correlation of magnetic energy density of magnetic signals under different lift?off value is analyzed. The results show that the spatial magnetic field energy outside the pipe decays with the increase of lift?off value, and the decay is the fastest within the distance of 50 mm from the outer wall of the pipe to the physical force; the correlation of magnetic energy density of different lift?off values shows that the magnetic signal detected by magnetic tomography method outside the pipe is homologous with the signal in the stress concentration zone of the inner wall of the pipe. Theoretically, it explains the effectiveness of magnetic tomography method and also provides evaluation indexes for extracting effective signals from the detection data.

In view of the irregularity of the bottom floor of working face and the diversity of the shape of the flying gangue in steeply dipping coal seam, based on the geographic information system data such as contour line of bottom floor of working face, the 3d grid model of bottom floor is established, combined with the energy tracking method(ETM) C + + programs, four typical shapes of flying gangue with the same mass and different shapes are simulated to obtain the motion trajectories of the migration of flying gangue in the actual working face, as well as the velocity, angular velocity and energy change curves at any time. The influence of the shapes on the motion of flying gangue is analyzed. In order to verify the accuracy and feasibility of the method in this paper, the trajectory simulated by Rockyfor3D software is compared. The results show that the transport capacity of ellipsoidal flying gangue is much higher than that of polyhedral flying gangue. Compared with common polyhedral flying gangue, the regular polyhedral flying gangue has farther migration distance and less energy loss due to collision. The number of edges of flying gangue of regular polyhedron is inversely proportional to the energy loss of flying gangue in collision, which indicates that flying gangue of regular polyhedron with multiple edges is most likely to cause danger．

Recognition of weather phenomena based on images is essential for the analysis of weather conditions. To address the problems that traditional machine learning methods are difficult to accurately extract various weather features and poor in classifying weather phenomena and the accuracy of deep learning for weather phenomena recognition is not high, a weather recognition model based on image block and multi?headed attention mechanism is proposed. The model introduces Swin Transformer into the field of weather recognition for the first time, and adopts a multi?headed attention mechanism combining window multi?head self?attention layer and shifted?window multi?head self?attention layer, whose regionally relevant features extraction capability makes up for the shortcomings of traditional methods and can extract complex weather features from images. The model is trained using transfer learning, and the fully connected parameters of the fine?tuned model are input to the Softmax classifier to achieve recognition of multi?category weather images with 99.20% recognition accuracy, which is better than several mainstream methods in comparison, and it can be applied to ground weather recognition systems as a weather recognition module.

The robustness of the particle swarm system is great, which is very helpful for solving ill?conditioned problems such as image reconstruction. However, the large number of pixels in the reconstructed image leads to a large dimension of particle and it is difficult for the particle to achieve the optimal solution in the optimization process. In order to solve this problem, a constraint is added to the particle position, imaging by Tikhonov regularization algorithm is used as the reference of particle position. The search for particles is constrained to the range of Tikhonov regularization algorithm reconstructs the image. Using the penalty function to solve the constraint problem to improve the particle search speed. Linearly decreasing weights as inertial weights for particle swarms optimization to realize the adaptive dynamic adjustment of the inertia weight and improve the flexibility of the algorithm; the chaotic operator is added to the position search process of the particle swarm optimization, when the particle falls into the local optimum, the chaotic variable will fluctuate within a certain range, reducing the missed rate of the optimal solution. The simulation results show that The improved particle swarm algorithm is more accurate and efficient than the traditional LBP algorithm and Tikhonov regularization algorithm.