Abstract: Considering the energy and environmental issues faced by human society, hydrogen has become increasingly important, and electrocatalytic water splitting is considered to be an ideal way to solve these energy issues. However, although most electrocatalysts will undergo a structural evolution when in service conditions, our understanding of the service behavior of catalysts is limited. To design highly active catalysts, operando characterization techniques must be used to study their dynamic structural evolution. Today, the development of synchrotron radiation devices has reached an important stage. Synchrotron-radiation-based X-ray characterization, which has high energy, large flux, and excellent collimation compared with the ordinary laboratory X-ray source, can capture the precise structure of catalytic materials. In this review, we present the development status of synchrotron radiation devices and the basic principles of operando X-ray absorption spectroscopy, X-ray diffraction spectroscopy, and X-ray photoelectron spectroscopy based on synchrotron radiation. In addition, we highlight studies related to the dynamic service behavior of water-splitting catalysts under real conditions and list a variety of operando studies of typical water-splitting catalysts, including NiFe hydroxide/(oxy)hydroxides, perovskite oxides, spinel oxides, and noble-metal-based catalysts. The use of operando X-ray techniques deepens our understanding of the catalyst reaction mechanism and provides a basis for identifying the dynamic structure–performance correlation of catalysts. We summarize the problems and challenges of operando X-ray-based techniques in complex electrochemical environments and propose the prospect of an advanced synchrotron radiation facility for operando X-ray characterization. With the development of the next-generation synchrotron radiation facility, adequately using this advanced X-ray light source to study the dynamic structure–activity correlation of catalytic materials throughout their life cycle to achieve the precise design and synthesis of complex pre-catalysts will advance the development of this field by enabling greater refinement and control.
Abstract: With the development of material design theories and synthesis technologies, clay-based composite materials have been controllably prepared and successfully applied in many fields, such as biomedicine, the automotive industry, petrochemical engineering, and wastewater treatment. To date, for the preparation of clay-based composite materials, the physical and chemical properties of clay must be fully considered, including the chemical composition, crystal structure, particle size, morphology, and surface charge. Halloysite, which has a tubular crystal structure, is a curly layered aluminosilicate clay with abundant reserves and a low price for constructing composite materials. The inner and outer surfaces of halloysite nanotubes are composed of Al?OH octahedrons and Si?O tetrahedrons, respectively, which ionize in opposite ways in water, resulting in opposite charges on the inner and outer surfaces. Therefore, the selective modification of halloysite can be achieved by chemical or electrostatic adsorption of the required chemical reagent. Additionally, the modified halloysite nanotubes can be used in catalysis and the loading and release of drug molecules. Moreover, because of its nanotube structure, the halloysite can be used to construct rough structures in micro- or nano-scale. By incorporation with low-surface-energy materials, the hydrophobic halloysite-based composite materials can be prepared for self-cleaning and oil-water separation. In this review, we introduced the rational design and preparation strategies of the hydrophobic halloysite-based composite materials. Then, we summarized the applications of these prepared composite materials in oil-water separation, hydrophobic self-cleaning coating, and the loading and sustained release of drug molecules. In addition, the related mechanisms and strategies for performance improvement were systematically discussed. Finally, the existing challenges and promising future directions in this research field were proposed. The halloysite-based composite materials have enhanced properties that are highly required, including enhanced mechanical and adhesive strength, excellent scratch and wear resistance, self-healing, and higher compatibility with living organisms. We believe fruitful promising results can be achieved in this field with more effort.
Abstract: In the real world, the development model of optimization problems tends to be diversified and large scale. Therefore, optimization technologies are facing severe challenges in terms of nonlinearity, multi-dimensionality, intelligence, and dynamic programming. Multiobjective optimization problems have multiple conflicting objective functions, so the unique optimal solution is impossible to obtain when optimizing, and multiple objective values must be considered to obtain a compromise optimal solution set. When traditional optimization methods treat complex multiobjective problems, such as those with nonlinearity and high dimensionality, good optimization results are difficult to ensure or even infeasible. The evolutionary algorithm is a method that simulates the natural evolution process and is optimized via group search technology. It has the characteristics of strong robustness and high search efficiency. Inspired by the foraging behavior of bird flocks in nature, the particle swarm optimization algorithm has a simple implementation, fast convergence, and unique updating mechanism. With its outstanding performance in the single-objective optimization process, particle swarm optimization has been successfully extended to multiobjective optimization, and many breakthrough research achievements have been made in combinatorial optimization and numerical optimization. Consequently, the multiobjective particle swarm algorithm has far-reaching research value in theoretical research and engineering practice. As a meta-heuristic optimization algorithm, particle swarm optimization is widely used to solve multiobjective optimization problems. This paper summarized the advanced strategies of the multiobjective particle swarm optimization algorithm. First, the basic theories of multiobjective optimization and particle swarm optimization were reviewed. Second, the difficult problems involving multiobjective optimization were analyzed. Third, the achievements in recent years were summarized from five aspects: optimal particle selection strategies, diversity maintenance mechanisms, convergence improvement measures, coordination methods between diversity and convergence, and improvement schemes of iterative formulas, parametric and topological structure. Finally, the problems to be solved and the future research direction of the multiobjective particle swarm optimization algorithm were presented.
Abstract: The simultaneous localization and mapping (SLAM) technique is an important research direction in robotics. Although the traditional SLAM has reached a high level of real-time performance, major shortcomings still remain in its positioning accuracy and robustness. Using traditional SLAM, a geometric environment map can be constructed that can satisfy the pose estimation of robots. However, the interactive performance of this map is insufficient to support a robot in completing self-navigation and obstacle avoidance. One popular practical application of SLAM is to add semantic information by combining deep learning methods with SLAM. Systems that introduce environmental semantic information belong to semantic SLAM systems. Introduction of semantic information is of great significance for improving the positioning performance of a robot, optimizing the robustness of the robot system, and improving the scene-understanding ability of the robot. Semantic information improves recognition accuracy in complex scenes, which brings more optimization conditions for an odometer, pose estimation, and loop detection, etc. Therefore, positioning accuracy and robustness is improved. Moreover, semantic information aids in the promotion of data association from the traditional pixel level to the object level so that the perceived geometric environmental information can be assigned with semantic tags to obtain a high-level semantic map. This then aids a robot in understanding an autonomous environment and human–computer interaction. This paper summarized the latest researches that apply semantic information to SLAM. The prominent achievements of semantics combined with the traditional visual SLAM of localization and mapping were also discussed. In addition, the semantic SLAM was compared with the traditional SLAM in detail. Finally, future research topics of advanced semantic SLAM were explored. This study aims to serve as a guide for future researchers in applying semantic information to tackle localization and mapping problems.
Abstract: Considering the unstable performance of geopolymeric materials due to the large fluctuation of the raw-material composition and the high alkalinity of the system, this study investigated the effect of limestone powder on red mud–based geopolymeric grouting materials; moreover, the influence mechanism was analyzed via X-ray diffraction (XRD), mercury intrusion porosimetry (MIP), and scanning electron microscopy (SEM). Also, the study provided some reference to reduce the storage of red mud and realize the collaborative utilization of limestone powder and red mud–based grouting materials. The results show that the mechanical strength of specimens first increases and then decreases with the increase in the limestone powder content. The compressive strength of the specimen with 5% limestone content was the best: the 3-day compressive strength could reach 5.65 MPa, which was 18.94% higher than that of the specimen with 0% limestone powder content. Moreover, the slurry bleeding rate of the 5%-limestone specimen was only 9.85% higher than that of the 0%-limestone specimen, and the porosity of the former on day 28 was 18.35% lower than that of the latter. Therefore, 5% is the best content of limestone powder in red mud–based grouting material. When the mean particle size of limestone powder was 8 μm, the “filling effect” and “nucleation effect” of specimens were significant, and the slurry viscosity rose sharply; the compressive strengths of day-3 and day-28 samples increased by 11.86% and 10% than those of the corresponding bulk-limestone samples, respectively. Thus, the smaller the mean particle size of limestone powder, the more significant the improvement effect of red mud based grouting material. The optimum proportion of red mud–based grouting materials was 47.5% red mud, 47.5% blast furnace slag, and 5% limestone powder. The macro analysis confirms that limestone powder participates in the slurry hydration process, providing nucleation sites for N–A–S–H, C–A–S–H, and C–S–H gel, which can be used for geopolymer gel precipitation and growth and accelerate the slurry hydration.
Abstract: Reinforcement corrosion, due to the presence of chloride ions, is a major cause of the degradation of reinforced concrete structures. Nowadays, electrochemical rehabilitation (ER) is becoming a common technique for repairing reinforced structures. Due to the transmission properties of the micro-pores in concrete, chloride ions can be transferred to the outside of the concrete through the pores under the driven force of electric field. Compared with other conventional technologies, ER presents many advantages, such as high efficiency and little influence on the environment and surroundings. However, previous studies indicate that ER exhibits negative effect on the interfacial bonding properties of steel concrete. As the main influence factor for ER, varying current densities may consequently change the bond loss between steel and concrete. In addition, large current density significantly reduces interfacial bond. However, current studies lack relevant quantitative research results and fail to propose an effective method to solve the problem after electrochemical repair since aiming at electrochemical rehabilitation will most likely result in the bond deterioration of reinforced concrete. In this study, the bond-slip curves were obtained through central pull-out specimens after ER with various electrochemical parameters, and the relationship between the electrochemical parameters (current density and conduction time) and the bond behaviors were investigated. Finally, a degradation model of bond strength considering the influences of the two parameters mentioned was established. Results show that the bond strength decreases significantly with high current density and long conduction time. Using a current density of 5 A·m–2, reduction of the max bond force increased up to 22.6% and 56.9% under a conduction time of 15 and 28 d, respectively. The proposed model can be used to quantitatively characterize the reduction of bond strength after electrochemical rehabilitation. Good consistency of results was observed after comparing the evaluated results with that of the experiment.
Abstract: The inclusions at the defects of tinplate originated from the entrainment of the mold flux, but their composition differed significantly from that of the mold flux. To investigate this difference, a kinetic model was established of the transformation of the composition of the slag inclusions, coupled with the thermodynamic equilibrium and kinetic diffusion. The influences of the size and density of slag inclusions on the variation of their composition were also evaluated. The residence times of the inclusions in the molten steel were studied by simulating the flow of molten steel and the movement of the inclusions in the mold and steel cavity. The results show that after entrainment into the molten steel, the mold flux reacts continuously with the molten steel, which results in a significant change in its composition. The time required for the transformation was related to the diameter and density of inclusions. The larger the diameter and the bigger the density, the longer the time was required for the transformation. The time required for the transformation had a root relationship with the diameter of inclusions, and had a quadratic function with density of the inclusions. The average residence time of the inclusions in the molten steel decreased with increases in the diameter of the inclusions and the pulling speed. There would be enough time for the small inclusions to transform into the compositions of defects once they are entrained into the molten steel. The average residence time of the large inclusions is less than the time required for the transformation, while the maximum residence time is much longer than the time required for the transformation, which indicates that some inclusions with larger size still have enough residence time to transform from the initial composition to the composition of defects.
Abstract: Electromagnetic stirring of strands by a traveling-wave magnetic field is a cutting-edge continuous casting technology for eliminating the columnar crystal structure that tends to develop in stainless- and/or silicon-steel slab castings. The common ridging defect on the surface of ferritic stainless strip products has been found to be closely related to the well-developed as-cast columnar crystal structure. To explore the various electromagnetic properties of the traveling-wave magnetic fields applied to the secondary cooling zone of a slab casting strand, we used the segmented computational domain method to develop a coupled math model to analyze the electromagnetic, fluid flow, heat transfer, and solidification behaviors, which had been previously determined in an electromagnetic measurement experiment to be a valid approach. The modeling analysis results regarding the traveling-wave magnetic fields show that molten steel stirring has some effect on the end of the slab strand. We also found that the intensity of the magnetic induction when using a box-type electromagnetic stirrer (B-EMS) is much greater on the inside of the strand than on the outside, as compared with its symmetric behavior when applying a roller-type electromagnetic stirrer (R-EMS). At an electrical power of 400 kW and frequency of 7 Hz, the current intensity of the R-EMS is higher than that of the B-EMS by 75 A, achieving a more efficient stirring effect for promoting equiaxed crystal nucleation in front of the solidified shell. In casting experiments in a stainless-steel slab caster, both the B-EMS and R-EMS are found to inhibit the growth of columnar crystals through nucleation of the heads of the dendrites, which realizes an equiaxed crystal ratio of the slab casting 45% higher than its threshold value. In addition, an R-MES with two pairs of rollers using inverse thrust EMS forces can produce an equiaxed crystal ratio 17% higher than that achieved by the B-EMS, and can thus be used in the casting production of ferritic stainless steels to obtain final strip products with no ridging defects.
Abstract: With the rapid growth in the demand for portable/wearable electronic products, the demand for high-performance, flexible, and lightweight power is becoming stronger. Given the excellent cyclic stability, high rate of charge/discharge, and high power density of supercapacitors, they have become ideal devices to meet the power requirements of portable/wearable electronic products. The most effective method to enhance supercapacitor performance is to improve the electrode materials. Lately, researchers have concentrated on exploring and developing excellent-performance electrode materials. Two-dimensional (2D) materials are the most prospective supercapacitor materials owing to their outstanding properties. Transition-metal carbides and nitrides (MXene), a novel family of 2D materials, have been found to exhibit relatively better chemical stability, higher surface area and active surface sites, excellent hydrophilicity, and higher electrical conductivity. The earliest explored and the most widely applied MXene is Ti3C2Tx. In several types of energy-storage systems, such as electrochemical hydrogen storage, supercapacitors, and lithium-ion batteries, Ti3C2Tx has shown exceptional performance as potential electrode material. In this work, Ti3C2Tx colloidal solution was prepared by etching Ti3AlC2 with a LiF–HCl mixed solution and a flexible MXene film was obtained via vacuum filtration. The physical structures and morphologies of graphene and chemical elements were characterized via X-ray diffraction, scanning electron microscopy, energy-dispersive X-ray spectroscopy, and X-ray photoelectron spectroscopy. The capacitance properties of the MXene film electrode were studied via cyclic voltammetry, galvanostatic charge–discharge, and electrochemical impedance spectroscopy. The research shows that in H2SO4 electrolyte, the MXene film thickness is 6.6 μm, and the mass-specific capacitance can reach 228 F·g?1 at 5 mV·s?1. When the scanning speed increases to 100 mV·s?1, the capacitance retention rate can reach 51%, which is three times that of the 40.2 μm MXene film electrode. The research shows that acidic electrolyte and thin film are beneficial to improve the performance of MXene supercapacitors.
Abstract: To address environmental issues and decrease production costs, the disruptively innovative solidstate steelmaking process was investigated. In this process, a high-carbon sheet is continuously decarburized using an oxidizing gas to achieve a low-carbon sheet. A significant benefit of the process is the elimination of several conventional processes, including the basic oxygen process, secondary refinement processes, and continuous casting, and the absence of inclusions. The most important feature of the process is the use of high-carbon iron melts to avoid inclusion formation, so that secondary refinement processes are eliminated. To study the gas–solid reaction kinetics of the decarburization of Fe–C alloy strips in H2/H2O, the effects of the decarburization temperature, strip thickness, and decarburization time on the decarburization effect of the Fe–C alloy strips were studied by a controlled-atmosphere high-temperature tube decarburization furnace. The results show that prolonging the decarburization time, increasing the decarburization temperature, and reducing the strip thickness can improve the decarburization effect. The Fe–C alloy strip cross section is composed of the complete decarburization layer, partial decarburization layer, and nondecarburized layer at 1353 K. The microstructure of the complete decarburization layer is ferrite. The partial decarburization layer is composed of ferrite, cementite, and a small amount of graphite phase. The nondecarburized layer is composed of pearlite and a large amount of graphite phase. The thickness of the decarburized layer has a good linear relationship with the square root of the decarburization time, which can be described by the function y = kt0.5. The diffusion activation energy of the decarburization reaction of the 1.5 mm Fe–C alloy strip is 122.36 kJ?mol?1. The variations of the average carbon content were studied, and the apparent activation energy of the decarburization reaction of the Fe–C alloy strips was 153.79 kJ?mol?1.
Abstract: Obtaining high-quality gear steel calls for strict requirements on the oxygen content, shape, composition, size, and distribution of nonmetallic inclusions to ensure high-quality steel and castability of the molten steel during the continuous casting process. Al2O3 inclusions with high melting point are easily generated in Al-deoxidized gear steel, and they easily result in nozzle clogging and deterioration in the properties of the steel. A reasonable calcium treatment can reduce the nozzle clogging and increase improving the castability of the molten steel, and thus it has been widely used in steel plants. Calcium treatment is often used to convert Al2O3 inclusions with high melting point to calcium aluminate with low melting point. The factors of calcium treatment on nonmetallic inclusions in gear steel were investigated through industrial trials. The dependency of calcium yield on various factors, namely, the amount of calcium addition, feeding speed of calcium wire, and feeding position and slag thickness were discussed. The effect of the amount of calcium addition on nonmetallic inclusions in the molten steel was studied at a feeding rate of 1.5 m·s?1. With the initial mass fraction of T.Ca lower than 10×10?6 in the steel and a feeding rate of 1.5 m·s?1, the calcium yield can be higher than 20% if the amount of calcium addition, clearance height, and slag thickness during the refining process are appropriate. Large numbers of nonmetallic CaS inclusions with high melting point are formed in the molten steel with the mass fraction of T.Ca higher than 17×10?6, and the inclusions are formed far away from the liquidus region. With increase in the T.Ca content in the steel, the average size and number density of the nonmetallic inclusions gradually increase. The effect of calcium treatment on the modification of nonmetallic inclusions studied by thermodynamic calculation results agrees well with the measurements taken via industrial trials.
Abstract: To study the friction and wear properties of 316L stainless steel filaments prepared by selective laser melting (SLM) for metal rubber under the condition of grease lubrication, the friction coefficient and wear rate of SLM-316L filaments under different loads, different friction velocities, and Fv factors of the combined effect with load (F) and friction velocity (v) were discussed. Scanning electron microscope (SEM) was used to observe the surface morphology of filaments after wear, and energy dispersive spectrometer (EDS) was used to detect the element types and atomic percentages of the worn surface. Based on these two methods, the wear mechanism was analyzed. Results show that under the grease lubrication condition and with increased load, the friction coefficient decreases, whereas the wear rate initially decreases and then increases. With increased friction velocity, both the friction coefficient and wear rate tend to initially increase and then decrease. The wear mechanism of SLM-316L filaments under the low load condition is mainly abrasive wear and slight oxidative wear. At a high load, oxidative wear is aggravated and accompanied by fatigue wear. The wear mechanism of SLM-316L filaments at low friction velocities is mainly fatigue wear and oxidative wear. At high friction velocities, oxidative wear weakens, and abrasive wear becomes dominant. With an increased Fv value, the friction coefficient decreases and wear rate tends to initially rise, which then decreases and finally rises again. Therefore, the best working parameter of the metal rubber prepared using SLM-316L filaments under grease lubrication conditions is Fv=0.04 N?m?s?1, which means that the load is equal to 10 N and the friction velocity is 240 mm?min?1.
Abstract: The simulation of bolt joints affects the analysis accuracy of the dynamic characteristics of the whole structure in the dynamic modeling of bolted connection structures. In this study, the mechanical properties of the bolted thin-plate lap joint were simulated based on a nonuniformly distributed virtual material. The parameters of the virtual material were expressed based on a complex modulus, and the complex stiffness matrix can be directly generated to express the stiffness and damping characteristics of the lap joint. The steps used to generate a joint damping matrix in conventional modeling were omitted, and the modeling process was simplified to ensure model accuracy. We established a semianalytical model of a bolted thin plate structure to enable its dynamic analysis. In this study, we first described the modeling concept. The virtual material was assumed to have three types of nonuniform complex modulus distributions to simulate the mechanical properties of the bolted lap joint. We proposed a method for determining the storage modulus and energy dissipation modulus of the virtual material using a reverse identification technique. Based on the energy method and the assumed modes of orthogonal polynomials, we derived a semianalytical model of bolted thin plates and develop an innovative formula for solving the frequency response function at any hammering point and the vibration point of the semianalytical model. Finally, we conducted a case study on a bolted thin plate structure. Results show that the deviation between the simulated natural frequencies calculated using the semianalytical model and the experimental natural frequencies are less than 5%. Further, the calculated model shapes and frequency-response-function curves are close to those obtained based on the measured values. These results prove that a virtual material with a nonuniform complex modulus distribution can effectively simplify the modeling of a bolted joint and achieve high simulation accuracy.
Abstract: The screening efficiency and average transport speed of materials are important indicators for measuring the performance of screening machinery. In recent years, few breakthroughs have been made in traditional screening machinery. As high-efficiency vibration machinery, high-frequency vibrating screens have become widely used in recent years, but the operational methods of high-frequency vibrating mesh screens are relatively unique: the screen box is fixed and the screen is vibrated at a high frequency. Despite its wide use, there are relatively few studies about the materials movement law and screening characteristics of high-frequency vibrating screen. In this study, a discrete element method (DEM) was used in a simulation of the screening process of the spherical and nonspherical particle groups, and an experimental study was also conducted. The results show that changes in the screening efficiency in the simulation of spherical and nonspherical particles are consistent with those observed experimentally, but the simulation results for the nonspherical particles were closer to those obtained in the experiments. Orthogonal designs and multiple sets of simulation tests were conducted to analyze the influence of each vibration parameter (vibration frequency, amplitude and mesh inclination) on the particle distribution curve, screening efficiency, and average transport speed of the materials. Multivariate nonlinear fitting was performed on the data using the orthogonal test table, and the relationship between the screening efficiency and the vibration parameters was obtained. Based on this relationship, the optimal vibration parameters were obtained and verified in the simulation. The results obtained in this research provide a theoretical basis for the design of the vibration parameters of the high-frequency vibrating screen, and the experimental and simulation data provide support for the investigation of the screening mechanism of the high-frequency vibration system.
Abstract: The classification of imbalanced data has become a crucial and significant research issue in many data-intensive applications. The minority samples in such applications usually contain important information. This information plays an important role in data analysis. At present, two methods (improved algorithm and data set reconstruction) are used in machine learning and data mining to address the data set imbalance. Data set reconstruction is also known as the resampling method, which can modify the proportion of every class in the training data set without modifying the classification algorithm and has been widely used. As artificially increasing or reducing samples inevitably results in the increase in noise and loss of original data information, thus reducing the classification accuracy. A reasonable oversampling and undersampling algorithm are the core of the resampling method. To improve the classification accuracy of imbalanced data sets, a resampling algorithm based on the neighbor relationship of sample space was proposed. This method first evaluated the security level according to the spatial neighbor relations of minority samples and oversampled them through the synthetic minority oversampling technique guided by their security level. Then, the local density of majority samples was calculated according to their spatial neighbor relation to undersample the majority samples in a sample-intensive area. By the above two means, the data set can be balanced and the data size can be controlled to prevent overfitting to realize the classification equalization of the two categories. The training set and test set were generated via the method of 5 × 10 fold cross validation. After resampling the training set, the kernel extreme learning machine (KELM) was used as the classifier for training, and the test set was used for verification. The experimental results on a UCI imbalanced data set and measured circuit fault diagnosis data show that the proposed method is superior to other resampling algorithms.
Monthly, started in 1955 Supervising institution：Ministry of Education Sponsoring Institution：University of Science and Technology Beijing Editorial office：Editorial Department of Chinese Journal of Engineering Publisher：Science Press Chairperson：Ren-shu Yang Editor-in-Chief：Ai-xiang Wu ISSN 2095-9389CN 2095-9389
