Search Results (16)

Hydrogen-centered electrochemical technologies play a vital role in sustainable energy conversion and storage. One of the challenges in achieving cheap hydrogen is to bridge the gap between advanced electrocatalysts and highly effective electrodes. The key lies in designing electrocatalysts with high intrinsic activity and understanding the structure–activity relationship in water electrolysis. Being proposed as promising electrocatalysts, bulk oxides, with their compositional and crystal structure flexibility, provide a good platform for studying the correlation between intrinsic activity and electronic structure and also for screening superior catalysts for water electrolysis. In this review, we discuss the recent developments of oxide electrocatalysts in understanding the structure–activity relationship. Firstly, we present a thorough overview of recent advances from both theoretical and experimental aspects. Subsequently, we highlight the design principles to provide guidance for promoting performance. Finally, the remaining challenges and perspectives about this field are presented. This review aims to provide guidance for the design of highly advanced oxide electrocatalysts for water electrolysis and large-scale green energy supply. Full article

Numerical simulation has become a pivotal tool for analyzing airflow dynamics and temperature patterns during the precooling of postharvest horticultural products stacked in vented package. In this study, a three-dimensional mathematical model for iceberg lettuces stacked symmetrically in plastic crate was developed. The influence of the physical model at different gap sizes on the simulation accuracy was studied by assessing wall drag coefficient, airflow distribution, and heat transfer efficiency. The results show a reasonable decrease in the drag coefficient with an increasing gap size to 6 mm in terms of airflow distribution inside the plastic crate; any further increase in gap size and the average airflow velocity in both windward and leeward sides decreases rapidly. Interestingly, the gap size exhibited a limited impact on heat transfer characteristics during the cooling process. Thus, 6 mm was found to be the optimal distance to ensure good accuracy in simulation results and reduce the complexity of grid division. The numerical model was verified by experimental data. Moreover, the validation confirms good consistency between the simulated predictions and experimental measurements. This study provides a theoretical basis for establishing a reliable numerical model for the precooling of agricultural produce stacked symmetrically in a vented package. Full article

Urban transportation systems, particularly underground interchanges, present significant challenges for sustainable and resilient urban design due to their complex road geometries and dense traffic signage. These challenges are further compounded by the interaction of diverse road users, which heightens the risk of accidents. To enhance both safety and sustainability, this study integrates advanced driving simulation techniques with machine learning models to improve driving safety and comfort in underground interchanges. By utilizing a driving simulator and 3D modeling, real-world conditions were replicated to design key traffic safety features with an emphasis on sustainability and driver well-being. Critical safety parameters, including speed, acceleration, and pedal use, were analyzed alongside comfort metrics such as lateral acceleration and steering torque. The LightGBM machine learning model was used to classify safety and comfort grades with an accuracy of 97.06%. An important ranking identified entrance signage and deceleration zones as having the greatest impact on safety and comfort, while basic road sections were less influential. These findings underscore the importance of considering visual cues, such as markings and wall color, in creating safer and more comfortable underground road systems. This study’s methodology and results offer valuable insights for urban planners and engineers aiming to design transportation systems that are both safe and aligned with sustainable urban mobility objectives. Full article

Thermal storage technology has received increasing attention under the policy of encouraging the development of renewable energy and new clean energy. Optimizing the heat exchange system of phase change thermal storage heat exchangers to obtain better performance has become increasingly urgent. This study comprehensively investigated the actual process of heat transfer and assessed the heat transfer correlation laws between the heat transfer fluids, heat exchange tubes, fins, and phase change materials. Taking the heat exchange efficiency of the heat exchanger as a guide, a simulation was conducted on the effect of the presence and quantity of fins as well as the flow rate of the cooling liquid on the heat exchange efficiency of the heat exchanger. The simulation results showed that too many or too few fins were not conducive to improving heat transfer efficiency. In addition, no positive correlation was observed between the flow rate of the cooling liquid in the heat exchanger and the heat transfer efficiency of the heat exchanger. Specifically, models with slightly slower cooling liquid flow rates had a higher heat transfer efficiency. After a sensitivity analysis, it was found that the number of fins had a more significant effect on the heat transfer efficiency of the heat exchanger than the flow rate of the cooling liquid. The heat exchanger with five fins and a cooling liquid flow rate of 0.1 m/s demonstrated the best heat transfer effect, achieving a temperature drop of 14.76% within 5 min. Full article

This paper introduces a refractive index sensor based on Fano resonance, utilizing a metal–insulator–metal (MIM) waveguide structure with an Anchor-like cavity. This study utilizes the finite element method (FEM) for analyzing the propagation characteristics of the structure. The evaluation concentrated on assessing how the refractive index and the structure’s geometric parameters affect its sensing characteristics. The designed structure demonstrates optimum performance, achieving a maximum sensitivity of 2440 nm/RIU and an FOM of 63. Given its high sensitivity, this nanoscale refractive index sensor is ideal for detecting hemoglobin concentrations in blood, and the sensor’s sensitivity is 0.6 nm·g/L, aiding in clinical prevention and treatment. Full article

Based on the characteristics of plasmonic waveguides and resonators, we propose a refractive index (RI) sensor that couples a gear ring with a metal–insulator–metal (MIM) waveguide. Using the finite element method (FEM), we conduct extensive spectral analysis of the sensor’s properties in the near-infrared spectrum. Furthermore, we investigate the structural parameters affecting the refractive index sensing characteristics. This study reveals that the complexity of the ring cavity edge can significantly enhance the sensitivity of the nanosensor. Optimal structural performance parameters are selected when the number of gears is six, resulting in a sensitivity of 3102 nm/RIU and a Figure of Merit (FOM) of 57.4 for the sensing characteristics of the gear ring. It possesses the advantages of small size and high sensitivity. This nanoscale sensor design demonstrates high sensitivity in the field of industrial material temperature detection. Full article

Based on the unique properties of optical Fano resonance and plasmonic-waveguide coupling systems, this paper explores a novel refractive index concentration sensor structure. The sensor structure is composed of a metal–insulator–metal (MIM) waveguide and two identically shaped and sized double-tooth ring couplers (DTR). The performance structure of the nanoscale refractive index sensor with DTR cavity was comprehensively assessed using the finite element method (FEM). Due to the impact of various geometric parameters on the sensing characteristics, including the rotation angles, the widths between the double-tooth rings, and the gaps between the cavity and the waveguide, we identified an optimal novel refractive index sensor structure that boasts the best performance indices. Finally, the DTR cavity sensor achieved a sensitivity of 4137 nm/RIU and Figure of merit (FOM) of 59.1. Given the high complexity and sensitivity of the overall structure, this nanoscale refractive index sensor can be applied to the detection of oil concentration in industrial oil–water mixtures, yielding highly precise results. Full article

Traditional identification methods for Papaver somniferum and Papaver rhoeas (PSPR) consume much time and labor, require strict experimental conditions, and usually cause damage to the plant. This work presents a novel method for fast, accurate, and nondestructive identification of PSPR. First, to fill the gap in the PSPR dataset, we construct a PSPR visible capsule image dataset. Second, we propose a modified MobileNetV3-Small network with transfer learning, and we solve the problem of low classification accuracy and slow model convergence due to the small number of PSPR capsule image samples. Experimental results demonstrate that the modified MobileNetV3-Small is effective for fast, accurate, and nondestructive PSPR classification. Full article

In this paper, a new refractive index sensor based on Fano resonance is introduced. It is mainly composed of two parts: a metal–insulator–metal as a base waveguide and an annular resonant cavity with a double notch and a double convex circle as a coupling structure. The sensing characteristics of the design are investigated via finite element calculations. The influence of the remaining structure parameters on the system’s sensing performance and the relationship between the wavelength corresponding to the Fano trough and the refractive index are also investigated. Furthermore, the structure is applied to refractive index sensors, resulting in a type with a sensitivity of 2740 nm/RIU and a figure of merit of 52.69. Full article

Natural gas plays an important role in the transition from fossil fuels to new energy sources. With the expansion of pipeline networks, there are also problems with the safety of pipeline network operations in the process of transportation. Among them, third-party damage is a key factor affecting the safety of pipelines. In this paper, the risk factors of third-party damage are analyzed, and an evaluation model of natural gas pipeline damage is established using the GeNIe Modeler. Through Bayesian network reverse reasoning and a maximum cause chain analysis from the four aspects of personnel, environment, management, and equipment, it was found that the top five factors that have significant influence on third-party damage, are safety investment, the completeness of equipment, safety inspection frequency, the management of residents along the pipeline, and safety performance, with the posteriori probability in the model of 97.3%, 95.4%, 95.2%, 95.1%, 95.1%, respectively. Consequently, it is necessary for pipeline operation companies to secure investment on safety, to make sure that the safety equipment (system) works and is in a good condition, to maintain the safety inspection frequency in an organization, to build a management system for residents along the pipeline, and to conduct routine safety performance assessments accordingly. Full article

With the continuous development and utilization of clean energy, the thermal utilization of solar energy is an important research direction. In view of the problems of the low utilization rate of solar heat in alpine regions of solar energy, an air-type vacuum-tube solar collector (AVSC) with air as the heat-exchange medium was designed. The vacuum tube of the solar heat collector adopted a double-pass spiral direct-current structure, and the vacuum tube had a built-in heat-storage rod. In order to test the heat collection performance of the designed air evacuated-tube solar collector, a heat collection performance test of the collector was conducted. The results showed that the average heat collection efficiency of the vacuum tube solar collector without phase-change heat-storage rods was 38%. The evacuated-tube solar collector using water as the heat transfer medium had an average heat collection efficiency of 58%. The average equivalent heat collection efficiency of the AVSC with a built-in phase-change heat-storage rod was 61%. Full article

Vision sensing is a key technology to realize on-line detection of welding groove sizes and welding torch relative position and posture parameters during the arc welding process of intelligent production. For the specially designed vision sensor based on combined laser structured lights, an integrated calibration method for its internal parameters is proposed firstly, which improves the efficiency, accuracy and comprehensiveness of internal parameter calibration for a line structured light vision sensor and provides a good foundation for industrial application of the vision sensor. Then, the high precision integrated detection algorithms are derived for the V-groove size parameters and the spatial position and posture (SPP) parameters of the welding torch relative to the welding groove based on a single modulated laser lines image. The algorithms make full use of the data in a single modulated laser lines image, adopting data segmentation and plane fitting to realize the 3D reconstruction of V-groove surfaces and its adjacent workpiece surfaces of planar workpiece, so solving the parameters with high precision. In the verification tests, the relative detection error of V-groove size parameters of planar workpiece is less than 1%, and the relative detection error of SPP parameters of welding torch relative to the welding groove is less than 5%, which separately shows the effectiveness and accuracy of the calibration method and the detection algorithms. This research work provides a good technical support for the practical application of the specially designed vision sensor in the intelligent welding production. Full article

With the rapid development of industrialization, the excessive use of fossil fuels has caused problems such as increased greenhouse gas emissions and energy shortages. The development and use of renewable energy has attracted increased attention. In recent years, solar heat pump heating technology that uses clean solar energy combined with high-efficiency heat pump units is the development direction of clean heating in winter in northern regions. However, the use of solar energy is intermittent and unstable. The low-valley electricity policy is a night-time electricity price policy. Heat pump heating has problems such as frosting and low efficiencies in cold northern regions. To solve these problems, an exergy analysis model of each component of a phase-change heat-storage coupled solar heat pump heating system was established. Exergy analysis was performed on each component of the system to determine the direction of optimization and improvement of the phase-change heat-storage coupled solar heat pump heating system. The results showed that optimizing the heating-end heat exchanger of the system can reduce the exergy loss of the system. When the phase-change heat-storage tank meets the heating demand, its volume should be reduced to lower the exergy loss of the tank heat dissipation. Air-type solar collectors can increase the income exergies of solar collectors. Full article

Lake area, water level, and water storage changes of terminal lakes are vital for regional water resource management and for understanding local hydrological processes. Nevertheless, due to the complex geographical conditions, it is difficult to investigate and analyze this change in ungauged regions. This study focuses on the ungauged, semi-arid Gahai Lake, a typical small terminal lake in the Qaidam Basin. In addition to the scant observed data, satellite altimetry is scarce for the excessively large fraction of outlier points. Here, we proposed an effective and simple algorithm for extracting available lake elevation points from CryoSat-2, ICESat-2 and Sentinel-3. Combining with the area data from Landsat, Gaofen (GF), and Ziyuan (ZY) satellites, we built an optimal hypsographic curve (lake area versus water level) based on the existing short-term data. Cross-validation was used to validate whether the curve accurately could predict the lake water level in other periods. In addition, we used multisource high-resolution images including Landsat and digital maps to extract the area data from 1975 to 2020, and we applied the curve to estimate the water level for the corresponding period. Additionally, we adopted the pyramidal frustum model (PFM) and the integral model (IM) to estimate the long-term water storage changes, and analyzed the differences between these two models. We found that there has been an obvious change in the area, water level, and water storage since the beginning of the 21st century, which reflects the impact of climate change and human activities on hydrologic processes in the basin. Importantly, agricultural activities have caused a rapid increase in water storage in the Gahai Lake over the past decade. We collected as much multisource satellite data as possible; thus, we estimated the long-term variations in the area, water level, and water storage of a small terminal lake combining multiple models, which can provide an effective method to monitor lake changes in ungauged basins. Full article

With a serious food safety situation in China, lots of major food recalls have been initiated. This study examined the key determinants underlying consumers’ protection and behavioral intention in response to major food recalls. An augmented protection motivation theory model (PMT) was developed by incorporating trust in food safety management and food recall concern into the original PMT. Structural equation model analysis was conducted using survey data in China (N = 631). The results showed that perceived knowledge significantly and positively influence protection motivation via its positive influence on the threat appraisal and coping appraisal. Moreover, protection motivation, trust in food safety management (TFSM), and food recall concern (FRC) significantly affect protection behavior intention. It was indicated that the inclusion of TFSM and FRC into the PMT significantly increase the explanatory power of the PMT model. Further analysis of quadratic regression demonstrated that the relationship between perceived knowledge and protection motivation presented an inverted U shape, which indicates the importance of continuous education in developing consumers’ food safety knowledge. Implications for future research are discussed. Full article