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In order to systematically understand the relationship between the structure and catalytic performance of the AMn2O5mullite catalyst, five kinds of A-site cation (La3+, Nd3+, Gd3+, Sm3+, and Y3+) manganese mullite catalysts were prepared for acetone degradation. XRD characterization results show that all catalyst samples successfully formed a pure-phase mullite structure. SEM, H2-TPR, O2-TPD, and other characterization results show that the morphology and redox properties of the catalyst strongly depend on the A-site elements, and the cationic effects of different A-sites have a significant impact on the catalytic activity. The activity sequence of the AMn2O5catalyst for acetone degradation is SmMn2O5> LaMn2O5> YMn2O5> NdMn2O5> GdMn2O5. Compared with the other four catalysts, SmMn2O5shows a higher Mn4+/Mn3+molar ratio and abundant Oadscontent, excellent reactive oxygen species desorption capacity, strong reduction, large specific surface area, and other advantages, which are conducive to the catalytic oxidation of acetone gas. On the basis of the best active catalyst SmMn2O5, the study shows that the preparation method of the catalyst and the addition of active agent F-127 also have an important influence on the activity of the catalyst. In addition, in situ diffuse infrared Fourier spectroscopy was used to analyze the reaction intermediates of oxidized acetone, and the specific catalytic mechanism was discussed. This study provides an important experimental basis for making full use of the rare-earth cation effect, modifying and optimizing the AMn2O5catalyst, and promoting catalytic oxidation of acetone.

In recent years, people are increasingly interested in CO2hydrogenation to produce value-added chemicals and fuels (CH4, CH3OH, etc.). In the quest for an efficient treatment in CO2methanation and methanolization, several technologies have been practiced, and DBD plasma technology gain attention due to its easily handling, mild operating conditions, strong activation ability, and high product selectivity. In addition, its reaction mechanism and the effect of packing materials and reaction parameters are still controversial. To address these problems efficiently, a summary of the reaction mechanism is presented. A discussion on plasma-catalyzed CO2hydrogenation including packing materials, reaction parameters, and optimizing methods is addressed. In this review, the overall status and recent findings in DBD plasma-catalyzed CO2hydrogenation are presented, and the possible directions of future development are discussed.

Graphical Abstract:

•Comprehensive summary on alkali metal behavior of high-alkali coal combustion.•Advantages/limitations of common measurement methods for alkali metals.•Highlights the contribution of alkali metal release/transformation in ash problems.•Effect of combustion condition and fuel optimization on alkali metals.•Challenges associated with the progress of alkali metal control technologies.

Volatile organic compounds (VOCs) are atmospheric pollutants that have been of concern for researchers in recent years because they are toxic, difficult to remove, and widely sourced and easily cause damage to the environment and human body. Most scholars use low-temperature plasma biological treatment, catalytic oxidation, adsorption, condensation, and recovery techniques to treat then effectively. Among them, catalytic oxidation technology has the advantages of a high catalytic efficiency, low energy consumption, high safety factor, high treatment efficiency, and less secondary pollution; it is currently widely used for VOC degradation technology. In this paper, the catalytic oxidation technology for the degradation of multiple types of VOCs as well as the development of a single metal oxide catalyst have been briefly introduced. We also focus on the research progress of composite metal oxide catalysts for the removal of VOCs by comparing and analyzing the metal component ratio, preparation method, and types of precursors and the catalysts’ influence on the catalytic performance. In addition, the reason for catalyst deactivation and a correlation between the chemical state of the catalyst and the electron distribution are discussed. Development of a composite metal oxide catalyst for the catalytic oxidation of VOCs has been proposed.

With the promotion of China’s ”peak carbon and carbon neutrality” target, PV power generation is gradually entering the era of price parity, and cost will no longer be the main obstacle to its scale development, but grid consumption will become the main factor to restrict its further development. In order to further promote the consumption of PV and realize the low-carbon transformation of microgrid, this paper establishes a game pricing model led by Photovoltaic Cluster (PVC) based on the response of power demand, carries out the research on the optimal scheduling of PV in microgrid by establishing the game relationship among grid, PVC and users. Firstly, a new IEEE 33-node arithmetic simulation model is built, and secondly, three PVCs are divided among the nodes, and the feasibility of the model is verified by solving the optimal tariff strategy through genetic algorithm. The final results show that the optimal scheduling method is effective in meeting the demand response of users in PVCs while reducing the cost of electricity consumption and promoting the local consumption of PV; in addition, after increasing the proportion of PV access, PV will become the main supplier of electricity and the operation mode of PVCs will be free from dependence on the grid.

Adding hydrogen to the fuel can change the combustion characteristics and greatly improve the pollutants emission for the gas turbine. The numerical method was adopted to study the combustion process in a counter-flow combustor of a 100 kW micro gas turbine using methane doped by hydrogen and various distribution schemes of air flow. The combustion characteristics and pollutant emissions were explored to ascertain the influence of air distribution based on solving the validated models. It was shown that as the amount of premixed air increased in the swirling gas, the range of the recirculation region became larger and the range of the high-temperature zone in the combustion chamber gradually enlarged. When the amount of premixed air was 30%, the outlet temperature distribution of the combustor was excellent and the average temperature was 1172 K. Moreover, the concentration of NOXgradually increased and reached a maximum value of 23.46 ppm (@15% O2) as the premixed air increased in the range of the ratio less than 40%. It was reduced to 0.717 ppm (@15% O2) when the amount of premixed air increased to 50%. These findings may support the running of the micro gas turbine using the hybrid fuel of hydrogen and methane.

In recent years, with the rapid development of high-speed railways (HSRs), power interruptions or disturbances in traction power supply systems have become increasingly dangerous. However, it is often impossible to detect these faults immediately through single-point monitoring or collecting data after accidents. To coordinate the power quality data of both traction power supply systems (TPSSs) and high-speed trains (HSTs), a monitoring and assessing system is proposed to access the power quality issues on HSRs. By integrating train monitoring, traction substation monitoring and data center, this monitoring system not only realizes the real-time monitoring of operational behaviors for both TPSSs and HSTs, but also conducts a comprehensive assessment of operational quality for train-network systems. Based on a large number of monitoring data, the field measurements show that this real-time monitoring system is effective for monitoring and evaluating a traction-network system.

Conventional maintenance mode for the traction power supply system (TPSS) is to perform scheduled regular maintenance activities for power supply equipment, while such maintenance mode may result in undue maintenance tasks and low efficiency due to different degradation processes of different sorts of equipment. To address this problem, this paper introduces a preventive opportunistic maintenance (POM) method for TPSS based on equipment reliability. Firstly, a POM model is established by considering the equipment reliability degradation process based on Weibull distribution. Then, by considering the total power outage time in the planned operation cycle of TPSS as the optimization objective, the optimal maintenance scheme of TPSS is formulated by iterative method of maintenance strategies. The proposed method is verified by introducing practical maintenance strategies and fault record data of the traction transformer, circuit breaker and disconnector in an actual TPSS of a railway administration. Results show that the presented method can make full use of the existing fault data to develop a POM scheme for TPSS. It can improve maintenance efficiency and reduce power outage time, providing guidance to formulate scientific maintenance strategies for TPSS.

Thermochemical heat storage based on a gas–solid interaction is an effective long-term energy storage technology and is considered as one of the important technologies for the recovery of industrial waste heat and renewable energy sources such as solar energy. There are many working pairs used for thermochemical heat storage, among which ammonium halides are widely trusted for their good thermodynamic properties. It has attracted a lot of attention in the past decade, but it is still in the laboratory-scale research stage. In this study, the adsorption behavior of strontium bromide surfaces on the atomic scale is investigated using density functional theory with SrBr2/NH3as the working pair. The optimal adsorption location of ammonia molecules on the strontium bromide surface is determined. Meanwhile, different metal atoms were doped to explore the microscopic factors affecting the adsorption. The energy barrier of the SrBr2/NH3reaction was 4.507 kcal/mol, which was reduced to 4.145 kcal/mol after doping Mg. The thermodynamics of the Ca atoms doped with SrBr2were significantly improved, with a reduction in the energy barrier to 0.727 kcal/mol. Comparing the three energy barrier results, Ca doping has a significant optimization effect on the thermal storage process. The results could provide relevant information for the investigation of thermochemical adsorption heat storage, provide insight into the adsorption mechanism of ammonium molecules on strontium bromide, and also facilitate the design of efficient composite adsorbents.

Abstract

To investigate the effect of CeO2nanomaterial morphology on its performance for NO catalytic oxidation. Three kinds of CeO2nanomaterials including CeO2nanorods, nanospheres and nanoparticles were prepared by hydrothermal method and used for catalytic oxidation of NO at low temperature. The experimental results show that CeO2nanorods are of the best catalytic performance. Characterization techniques including TEM, XRD, H2-TPR, NO-TPD and XPS were used to determine the relationship between the morphology of CeO2nanomaterial and its catalytic performance. TEM images show that CeO2nanorods predominantly exposed (110) and (1 0 0) planes, while CeO2nanospheres and CeO2nanoparticles predominantly exposed (1 1 1) plane. The excellent catalytic performance of CeO2nanorods could be ascribed to the low crystallinity, high reducibility, strong NO adsorption ability and the presence of more surface chemisorbed oxygen.

Fe2O3, as a substance that exists in nature in large quantities, has been widely paid close attention by many scholars because of its excellent properties. Fe2O3can be divided into four phases depending on the crystal structure. As a narrow band gap semiconductor, β-Fe2O3has a band gap of about 1.77–1.83 eV, which is much lower than the average band gap of Fe2O3(2.1 eV), and its theoretical saturated photocurrent density is 35% higher than that of α-Fe2O3, showing excellent light absorption characteristics and water oxidation capacity, which is a promising photoanode material. As the only polycrystalline phase of iron oxide that exhibits paramagnetism at room temperature, it also has a very bright prospect in the field of magnetic resonance. This paper focuses on the review of rare phase β-Fe2O3. Firstly, the crystal structure, magnetism of β-Fe2O3and the mature methods for preparing pure β-Fe2O3are summarized. Secondly, the conversion relationships between β phase and other phases of Fe2O3is reviewed, and the important factors affecting this process are summarized. As for the improvement and applications, it points out a variety of improvement methods such as heterojunction, element doping and morphology control, and discusses the applications of β-Fe2O3in many fields such as photocatalysis, Fenton oxidation, photochemical hydrogen production, biomedicine and toxic gas detection. Finally, the application prospect and challenges of β-Fe2O3are prospected. This paper aims to further demonstrate the latent capacity of β-Fe2O3. It also provides ideas for the application of this substance in other environmental remediation fields.

The electric vehicle industry is becoming an increasingly important part of the automotive industry, and the high operating temperature requirements of the batteries at the heart of electric vehicles make the study of battery thermal management systems (BTMS) particularly important. Among these, heat pipe (HP) based battery thermal management systems have a very high heat transfer performance, but are lacking in ensuring uniform temperature distribution. A coupled battery thermal management system that combines the two can combine the advantages and compensate for the disadvantages of both, and is considered to be the most effective system because of its smaller and simpler structure compared to the traditional thermal management methods that mainly use air and liquid as the working medium. One of the most effective systems. This paper will focus on the coupled HP and PCM systems, which have been less studied and applied in the past, and classify and compare the above mentioned thermal management systems according to the types of heat pipes used and the different methods of PCM heat transfer enhancement, and analyse their advantages and disadvantages respectively. Finally, an outlook on future research directions is given, where the use of systems that use multiple thermal management methods in conjunction with each other to ensure continuous battery operation will be the future direction of battery thermal management systems. In addition, this review helps to update the sparse reference literature.

•A correlation-graph-CNN method was proposed for fault diagnosis of wind turbine.•State tracking was proposed to obtain more abundant information of fault.•All the data were selected from SCADA system without adding any sensor.•Pearson correlation analysis facilitates the increase in accuracy rate of the model.•The accuracy rate of our proposed method can reach up to about 85%.

Catalytic oxidation of NO into NO2is a promising method for NOxemission control. The aim of this study was to develop an economic and environmental-friendly catalyst for NO catalytic oxidation. Herein a CeFeOxcomplex oxide catalyst for catalytic oxidation of NO was prepared by coprecipitation method. After that the catalytic performance of this catalyst was measured on a fixed-bed reactor. It was found that the intrinsic activity of CeFeOxwas higher than that of CeOxand FeOx. The characterization techniques of Brumauer-Emmett-Teller (BET), X-ray diffraction (XRD), temperature programmed reduction with H2(H2-TPR), temperature programmed desorption with NO+O2(NO+O2-TPD) and X-ray photoelectron spectroscopy (XPS) were performed to investigate the surface area, crystal structure, redox property and NOxadsorption behavior of the catalyst samples. From the characterization results, it was concluded that the low crystallinity of CeFeOxpromoted the dispersion of active species, as a result, enhancing the redox ability and NO adsorption capacity of CeFeOxcatalyst, which is favorable to NO catalytic oxidation. Furthermore, the presence of much chemisorbed oxygen on CeFeOxcatalyst also made a great contribution to its good catalytic performance.

The key of catalytic oxidation technology is to develop a stable catalyst with high activity. It is still a serious challenge to achieve high conversion efficiency of acetone with an integral catalyst at low temperature. In this study, the SmMn2O5catalyst after acid etching was used as the support, and the manganese mullite composite catalyst was prepared by loading Ag and CeO2nanoparticles on its surface. By means of SEM, TEM, XRD, N2-BET, XPS, EPR, H2-TPR, O2-TPD, NH3-TPD, DRIFT, and other characterization methods, the related factors and mechanism analysis of acetone degradation activity of the composite catalyst were discussed. Among them, the CeO2-SmMn2O5-H catalyst has the best catalytic activity at 123 and 185 °C for T50and T100, respectively, and shows excellent water and thermal resistance and stability. In essence, the surface and lattice defects of highly exposed Mn sites were formed by acid etching, and the dispersibility of Ag and CeO2nanoparticles was optimized. Highly dispersed Ag and CeO2nanoparticles have a highly synergistic effect with the support SmMn2O5, and the reactive oxygen species provided by CeO2and the electron transfer brought by Ag further promote the decomposition of acetone on the carrier SMO-H. In the field of catalytic degradation of acetone, a new catalyst modification method of high-quality active noble metals and transition metal oxides supported by acid-etched SmMn2O5has been developed.

•The slagging mechanism of high alkali coals is reviewed.•Summarized the efficient utilization method of pure high-alkali coal.•Summarizes the practical applications of relevant research and the bottlenecks.•Certain suggestions are made for the utilization of high-alkali coal.

With the current proliferation of multi-core processors and hardware acceleration, large-data processing methods are increasingly being modified for use in parallel and distributed computing environments. In this paper, we present a hybrid architecture for the visualization and processing of large-scale volumetric data. Various hardware environments and technologies are integrated in this architecture to perform interactive operations on very large volumetric datasets. All of the datasets are stored in a data center with a gigabit network environment. Time-consuming data-processing tasks are allocated to compute nodes connected to the same network, while the visualization and interaction operations are executed on a high-performance graphics workstation. OpenCL and OpenMP are used to implement volume rendering algorithms to accelerate visualization of a hierarchical volume data structure using GPUs and multi-core CPUs. Various out-of-core algorithms are also presented to process the large dataset directly. The experimental results indicate that the proposed hybrid architecture and methods are effective and efficient in processing and visualizing very large-volumetric datasets. [ABSTRACT FROM AUTHOR]

Acetone, as a kind of typical volatile organic compounds (VOCs), is mainly discharged into the atmosphere through exhaust emissions, fuel combustion, pharmaceuticals, and printing, etc. It not only causes water pollution but also inhibits the people’s central nervous system, posing a great threat to the ecological environment and human health. Due to its economy and compatibility, the catalytic oxidation method is considered to be one of the effective methods for removing acetone. The development of low-cost and high-efficiency catalysts can bring higher economic benefits. This review covers the research progress of acetone oxidation by noble metal and non-noble metal catalyst systems, and discusses the effects of metal composition, support, preparation method, and morphology on the catalyst activity. Comparison shows that both manganese-based and cobalt-based catalysts are the good substitutes for precious metal platinum-based and palladium-based catalysts, in which the concentration of oxygen vacancies, the number of active oxygen species, and the interaction between substrates are the key factors. In addition, the possible mechanism of catalytic oxidation of acetone is given, and the development of catalytic oxidation of acetone is prospected.

Alkali metal K in exhaust gas has a deactivation effect on NH3-SCR catalysts. In this work, it is discovered that the addition of Ho on CeTi catalyst can remarkably strengthen its K tolerance. The conclusions of Brunauer–Emmett–Teller (BET) , X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), NH3temperature programmed desorption (NH3-TPD) and H2temperature programmed reduction (H2-TPR) analyses demonstrate that the enhancement of K resistance mainly originates from its stronger surface acidity and redox capability, the higher concentration of Ce3+species and surface chemisorbed oxygen. In situDRIFT analysis reveals that the introduction of Ho on CeTi can remarkably improve the adsorption of NH3and NOxspecies on catalyst surface, accompanied by the intensified reactivity of ad-NH3species, which should also administer to improve the K resistance.

B-splines have been successfully applied to nonrigid image registration and are popular in various applications. They offer a reduced computational overhead because changes in the control points only affect the transformation within a local neighborhood. Optimization is a key stage in image registration. Most optimization methods only use the gradient direction to determine the update step that may be not optimal. A suboptimal update step may result in a large number of iterations, thus significantly increases the computational time or decreases the accuracy of the registration results. Levenberg–Marquardt (L-M) optimization is a superior algorithm that provides more precise steps during the iteration process. However, because of the large number of parameters in nonrigid image registration, the L-M method suffers from high computational complexity. In this paper, a dedicated optimization method is proposed for nonrigid CT image registration based on L-M optimization. A regular L-M step along with an additional L-M step is computed as the optimal vector, which reduces the computation time because the Jacobian matrix is reused for two calculations in every iteration. Besides, the parameters change automatically according to the calculated results in each step to make the method more efficient. In addition, a linear search for the trial step is introduced to enhance performance. Experimental results indicate that the proposed method is effective and efficient. [ABSTRACT FROM AUTHOR]

The rapid development of 3D digital technology has led to an increasing volume of 3D model data. In addressing the management of such large scale data, effective content-based 3D model retrieval and recognition methods are highly desirable. In 3D model retrieval and recognition tasks, the distance measure between two 3D models plays an important role. In this paper, we propose a novel 3D model retrieval and recognition method that employs both a distance histogram and 3D moment invariants as features that are invariant to 3D object scaling, translation, and rotation. Disjoint information is used to measure the distance between the feature histograms, and the Euclidean distance is applied in calculating the distance between two moment features. These measures are then combined as the 3D model distance. Using this distance measure, the relationships between all 3D models in the dataset are formulated as a graph structure. A semi-supervised learning process is then conducted to estimate the relevance among the 3D models, and this is employed for 3D model retrieval and classification. To evaluate the effectiveness of the proposed method, we conduct experiments on two datasets. Experimental results and a comparison with state-of-the-art methods demonstrate that the proposed method achieves improved performance for 3D model retrieval and recognition tasks. [ABSTRACT FROM AUTHOR]