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Identification of active sites of a catalyst is the Holy Grail in heterogeneous catalysis. Here, the authors successfully identify the CuCu(100)- hydroxylated ZnO ensemble and CuCu(611)Zn alloy as the active sites of Cu-ZnO catalysts for water gas shift and CO hydrogenation reactions, respectively.

The conversion of CO2 to valuable chemicals is still challenged by catalyst developments. Herein, the authors found that GaN is an efficient catalyst for selective CO2 hydrogenation to dimethyl ether as the primary product, in contrast to the traditional methanol-intermediate route over hybrid catalysts.

Direct synthesis of ethanol from non-petroleum carbon resources via syngas (CO/H2) is a highly attractive but challenging target. Here, the authors report a triple tandem catalytic system for single-pass conversion of syngas into ethanol with selectivity as high as 90%.

CO2 conversion to liquid fuels provides an appealing means to remove the greenhouse gas, although it is challenging to find materials that are both active and selective. Here, authors show sulfur-doped indium to be a highly active and selective electrocatalyst that transforms CO2 into formate.

Cobalt nanoparticles were loaded onto mesoporous zeolite Naâ€"Y (Naâ€"meso-Y) by melt infiltration and impregnation methods. As compared to impregnation, melt infiltration resulted in Co nanoparticles with a narrower size distribution. The Co/Naâ€"meso-Y catalyst prepared by the melt infiltration exhibited higher C10â€"C20 (diesel fuel) selectivity. The hydrogenolysis of heavier hydrocarbons was confirmed to occur under Fischerâ€"Tropsch reaction conditions. Our studies for the hydrogenolysis of n-hexadecane revealed that the catalyst by the melt infiltration was more active and selective for the formation of C10â€"C15 hydrocarbons. We propose that the narrower Co size distribution favors the selective hydrogenolysis and thus the C10â€"C20 selectivity in Fischerâ€"Tropsch synthesis. The addition of Mn with a proper content could further improve the diesel fuel selectivity to 65% by suppressing the formations of CH4 and lighter hydrocarbons. The Mn-modified Co/Naâ€"meso-Y catalyst was very stable and no deactivation was observed in 1000 h. [ABSTRACT FROM AUTHOR]

Selectivity control is a challenging goal in Fischer-Tropsch (FT) synthesis. Hydrogenolysis is known to occur during FT synthesis, but its impact on product selectivity has been overlooked. Demonstrated herein is that effective control of hydrogenolysis by using mesoporous zeolite Y-supported cobalt nanoparticles can enhance the diesel fuel selectivity while keeping methane selectivity low. The sizes of the cobalt particles and mesopores are key factors which determine the selectivity both in FT synthesis and in hydrogenolysis of n-hexadecane, a model compound of heavier hydrocarbons. The diesel fuel selectivity in FT synthesis can reach 60%with a CH4 selectivity of 5% over a Na-type mesoporous Y-supported cobalt catalyst with medium mean sizes of 8.4 nm (Co particles) and 15 nm (mesopores). These findings offer a new strategy to tune the product selectivity and possible interpretations of the effect of cobalt particle size and the effect of support pore size in FT synthesis. [ABSTRACT FROM AUTHOR]

Among various microporous and mesoporous materials investigated, the Li+-exchanged zeolite faujasite has been found to be the most efficient support of iron catalyst for producing C hydrocarbon fuels via Fischer-Tropsch synthesis. The location of iron species in the catalyst is a key issue in obtaining high selectivities to C hydrocarbons. It is proposed that the Li+ cation and the supercage structure of zeolite faujasite both play important roles in improving the selectivities to C hydrocarbons over the Fe catalyst. [ABSTRACT FROM AUTHOR]

Autonomous vehicles must maintain awareness of their surroundings, encompassing other vehicles, pedestrians, traffic signs, and varying road conditions. Among numerous objectives, the most crucial one is the detection of vehicles and pedestrians. Despite advancements, complex traffic scenarios still pose challenges in target detection. Variations in target size and occlusion often lead to misjudgments and missed detections. To address these issues, an enhanced vehicle and pedestrian detection model, YOLOv8nRLD, is proposed. It integrates several innovations to enhance target detection accuracy. Firstly, the introduction of the Receptive-Field Convolutional Block Attention Module enhances the model's ability to detect and emphasize salient features, facilitating more precise target localization and identification. Additionally, the Spatial Pyramid Pooling Fast module within the backbone feature extraction network is refined with the inclusion of the Large Separated Kernel Attention module. This augmentation significantly boosts the network's feature extraction capabilities. Furthermore, the adoption of a dynamic target detection head, termed Dynamic Head, incorporating attention mechanisms and diverse perception capabilities, enhances the model's feature expression capacity. Experimental validation on the BDD100K and Cityscapes datasets demonstrates notable performance enhancements, with mean Average Precision increasing by 4% and 2.5%, respectively. Ablation experiments confirm the effectiveness of individual modules, underscoring the method's efficacy and versatility in vehicle and pedestrian detection tasks. [ABSTRACT FROM AUTHOR]

Aiming at the problem of the difficulty in solving the dynamics driving force of the parallel robot, a deep learning model is proposed to estimate the slider driving force of the 3-PRS parallel robot. The 3-PRS parallel robot is presented, and its dynamics model is established using the Newton-Euler method. The dynamics of the 3-PRS parallel robot is analysed by using the theory of the "black box model". The parameters of the designed 3-PRS parallel robot are used as input, and the driving force can be output directly through the deep learning algorithm. The regression convolutional neural network (CNN) algorithm based on deep learning is established to estimate the slider driving force. An overall framework is proposed according to the characteristics of the three sliders. The parameters of the parallel robot are collected, and the collected data are converted into a grayscale image to establish the data sets for driving force estimation. Two cases with friction and without friction are considered respectively in the experiment. The experimental results show that measuring the driving force using the regression CNN can improve calculation accuracy and efficiency, which lays a foundation for studying the dynamics of the parallel robot. [ABSTRACT FROM AUTHOR]

With the development of autonomous driving technology, the ESP (Electronic stability program) has been widely used in the vehicle field. The safety and stability of vehicle driving have always been a particularly important issue. The complexity of electronic control systems makes it impractical to conduct online electrical performance testing on real vehicles in research and development. In this paper, a new signal simulation method for the ESP dynamic electrical performance testing is proposed by comparing the HIL (Hardware-in-the-loop) simulation methods for vehicles and analyzing the impact of the ESP on vehicle safety and stability. To begin with, a comprehensive structural design scheme for the HIL simulation platform which is proposed by analyzing the ESP structure and control principle. Then, the principle of lateral acceleration and yaw rate that is generated by vehicle which is analyzed, and a three-dimensional model of the combined simulation device was built. Subsequently, the physical development of the simulation device was completed. Finally, the feasibility of the simulation device was verified. The experimental results indicate that the simulation device can generate continuous lateral acceleration and yaw rate signals. With the motor rotation changes, the generated signal error is different. But the generated overall error is relatively small. Therefore, the simulation device can meet the usage requirements. [ABSTRACT FROM AUTHOR]

The Electric Power Steering (EPS), as an advanced vehicle steering technology, is widely used in present-day society. The EPS provides great convenience for vehicle driving. More and more vehicles are starting to equip this technical configuration. For testing the performance of the EPS in the laboratory, the study independently develops an EPS test bench for dynamic simulation of vehicle EPS steering load. The EPS test bench detects in the mode of the whole vehicle in the loop. During the test, the vehicle is placed on a fixed platform of the EPS test bench and connected to the tensile component for testing. The EPS test bench provides dynamic simulation of vehicle steering load in a pneumatic way. And the load simulation system of the EPS test bench is simulated. The simulation test shows the feasibility of the EPS test bench. The EPS test bench is tested through the joint real vehicle. The test results shows that the experimental value and the theoretical value are within the error range. And the test results also shows that the EPS test bench is accurate. The EPS test bench provides valuable text for the future development of the EPS load simulation research. Moreover, the study points out the development trend of the EPS test bench. [ABSTRACT FROM AUTHOR]

The random SVPWM strategy can significantly suppress the clustering harmonic amplitudes of the traditional SVPWM strategy in the driving system of the electric vehicle (EV). Therefore, the principle of the random SVPWM strategy has been detailed. The expression for the signal randomization scheme is given, and then a comprehensive working time expression for the random switching frequency SVPWM, the random zero-vector distribution SVPWM, the random pulse position SVPWM and the hybrid random SVPWM schemes has been derived. An experimental validation has been carried out. The results show that the random SVPWM strategy has excellent performance on suppressing the harmonic amplitudes of the current and the electromagnetic torque. [ABSTRACT FROM AUTHOR]

HIL (Hardware-in-the-Loop) simulation is widely used in the development of automotive functional software because of its high efficiency and low cost. As one of the most widely used automotive active safety systems, the development and testing of ABS (Antilock braking system) are also more convenient due to the emergence of HIL. Firstly, this paper summarizes the research status of ABS HIL simulation in recent years from the following two aspects. Control strategies that include logic threshold control, fuzzy PID algorithm, selfoptimization control, and sliding-mode control will be introduced, and some researchers have also conducted HIL research on the coordination control strategy of ABS with other control institutions, such as EPS (Electric power steering) and DYC (Direct yaw-moment control). The other one is that new type test benches were designed for developing and improving ABS. Secondly, a wheel speed signal simulation mechanism was designed. When the dynamic electrical performance of the ABS is tested in the laboratory, the tested vehicle is stationary and its driven wheels do not rotate. At this moment this device can be used to simulate the driven wheel speed so as to provide basic data for future research on the dynamic electrical performance of the ABS. Finally, this paper points out the development trend of ABS HIL simulation. [ABSTRACT FROM AUTHOR]