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Covalent triazine frameworks (CTFs), noted for their rich nitrogen content, have attracted significant attention as promising photocatalysts. However, the structural complexity introduced by the diversity of nitrogen atoms in nitrogen‐rich CTFs poses a substantial challenge in discovering high‐performance CTFs. To address this challenge, a machine‐learning approach is developed to rationally design nitrogen‐rich CTFs, which is subsequently validated through experimental methods. A framework is employed based on the special orthogonal group in three dimensions (SO(3))‐invariant graph neural networks to predict photocatalytic properties of CTFs structures. This approach achieves exceptionally high accuracies with R2 scores exceeding 0.98. From a dataset of 14920 CTFs structures, this framework identifies 45 high‐performance candidates. Guided by these predictions, a novel CTF structure, pyridine‐2,5‐dicarbaldehyde (CTF‐DCPD) is selected and successfully synthesized, which exhibits an ultrahigh hydrogen evolution rate of 17.70 mmol g−1 h−1. This rate significantly surpasses that of the widely studied CTF‐1,4‐dicyanobenzene (CTF‐DCB, 10.41 mmol g−1 h−1). This work provides a new paradigm for machine learning to accelerate materials development, which can be generalized to the development of other functional materials. [ABSTRACT FROM AUTHOR]

Hydraulic fracturing stands as a pivotal technological approach for enhanced tight gas recovery. This paper investigates the influences of geological and engineering parameters on the vertical extension mechanism of hydraulic fractures. In addition, the feasibility and effectiveness of fracture height prediction method and various fracture height control techniques have been examined. The results indicate that the height of hydraulic fractures decreases with an increase in the thickness of the barrier layers, the stress difference between the barrier and reservoir layers, the difference in tensile strength, and the difference in fracture toughness, whereas it increases with the increasing of difference in elastic modulus between the barrier and reservoir layers. Compred with the difference in Poisson's ratio, the volume of fracturing fluid, discharge rate, and fluid viscosity have little impactd. The influence of these factors on fracture height, in descending order, is stress difference between barrier and reservoir layers, fracturing fluid viscosity, fracturing discharge, fracturing fluid volume, barrier layer thickness, tensile strength difference between barrier and reservoir layers, elastic modulus difference between barrier and reservoir layers, Poisson's ratio difference between barrier and reservoir layers. Furthermore, based on typical geomechanic and reservoir parameters of the target area, a fracture height prediction workflow has been developed. Engineering practice has proven the reliability of fracture height prediction method. The results of this study provide theoretical support and guidance for predicting fracture morphology, controlling fracture height in the hydraulic fracturing development of the tight gas reservoir, and optimizing fracturing process design. [ABSTRACT FROM AUTHOR]

Graphitic carbon nitride (g-C3N4) is an attractive photocatalyst and a thermal reflux method was used to significantly increase the yield of g-C3N4 nanostructures and enhance their photocatalytic activity for H2 production. When raw material was placed in an inclined quartz tube with the bottom in the high temperature zone and the top in the low temperature zone, the vapor of the raw material was condensed from the top and refluxed to the bottom to then participate in the reaction again. This method can significantly improve the yield of g-C3N4 with an increase of 28.2%. When used as the photocatalyst in water splitting, these g-C3N4 nanostructures exhibit excellent activity with an H2 production of 2102 μmol h−1 g−1 under visible irradiation, which is 43.2% higher than the sample prepared by a traditional thermal polymerization method. This method is also promising to use for the synthesis of similar two-dimensional nanostructures for effective H2 production. [ABSTRACT FROM AUTHOR]

Featured Application: Sowing Rapeseed. The direct sowing of rapeseed requires shallow tillage for stubble removal, which can cause significant vibrations that impact the seed metering device, thereby affecting the quality of seeding. This study focuses on a double-row hole-wheel-type seed metering device on the 2BYG-220 type combined rapeseed planter. Initially, vibrations experienced by the seed drill during field operations were measured and analyzed, revealing that the vibration frequencies during field operations predominantly ranged between 0 and 25 Hz. Consequently, an eccentric wheel–return-spring-type vibration seed metering test rig was designed, manufactured, and set up. By swapping out the eccentric wheel on the test rig, the amplitude was mainly concentrated within 3 mm. The test results indicate that amplitude had a minimal impact on the performance of the double-row hole-wheel-type rapeseed seed metering device, whereas vibration frequency had a more significant effect. When the vibration frequency was between 0 and 10 Hz, the seed metering device maintained a stable output between 7.6 and 8.2 g/min, with minimal impact from vibrations: the coefficient of variation for seeding uniformity ranged between 35.81% and 44.58%, indicating stability and good uniformity. However, when the vibration frequency ranged from 10 to 24 Hz, the output of the seed metering device decreased rapidly and exhibited a linear relationship with frequency changes, with a determination coefficient (R2) of 0.92376. The coefficient of variation for seeding uniformity increased rapidly and also showed a linear relationship with frequency changes, with a determination coefficient (R2) of 0.87973. Vibrations with frequencies greater than 10 Hz had a considerable impact on the performance of the seed metering device. [ABSTRACT FROM AUTHOR]

Timely and effective drying of agricultural products is crucial for ensuring the quality and yield of grains. Biomass drying enhances energy utilization and reduces energy pressure. To this end, a novel multi-channel circulating biomass hot air furnace was designed to provide precise control of the heat source for grain drying, thereby improving the efficiency and quality of the drying process. The combustion process utilizes a multi-channel combined air supply to ensure complete combustion of biomass pellet fuel. During the heat exchange process, heat exchange plates isolate hot and cold areas, discharging combustion exhaust, while ensuring a pure air output. Using rapeseed as the drying subject, a temperature controller based on adaptive fuzzy PID was designed, targeting the biomass hot air furnace's heat exchange system for modeling and verifying the model with the step response method. Model simulations were conducted in Matlab's Simulink module using both adaptive fuzzy PID and traditional PID controllers, for a given signal. The settling times for the conventional PID and fuzzy PID were 445 s and 364 s, respectively, with overshoots of 20.1% and 6.3%, showing that the fuzzy PID controller performed better in terms of control performance. The validation tests showed that both control methods could maintain the temperature within ±5 °C. Compared to traditional PID control, the adaptive fuzzy PID control achieved a precision of ±3 °C. At the target temperature of 90 °C, the error was reduced to 3.7%, with a stabilization time of 1014 s. The use of fuzzy PID control exhibited better dynamic response characteristics, meeting the drying needs of rapeseed. This study provides a theoretical basis for the structural design and control system design of biomass hot air furnaces. [ABSTRACT FROM AUTHOR]

In agricultural engineering, the discrete element simulation of the operational structure, object of movement, and force has become a standard method of modern agricultural equipment design. The selection and development of an appropriate contact model are critical factors affecting the accuracy of the process of the simulation calculation of the movement and force. Understanding how to choose or establish suitable contact models according to different research fields, objects, and purposes has become the focus of present research. This paper gives an overview of contact models for discrete element simulation, summarizes and analyzes the simulation calculation basis of different contact models, and focuses on the application status and scenarios of different models at this stage. It analyzes and summarizes the selection basis and application fields of contact models. The next direction in the development of discrete element simulation contact models should be the hybrid application of multicontact models and the precise development of specialized contact models. It is necessary to establish a standardized parameter-calibration process for different contact models to guarantee the accuracy of the models, to improve the application of computer arithmetic, and to establish an efficient and accurate simulation contact model selection and application in the field of agricultural engineering. Efficient and accurate simulation contact model selection, design theory, and calculation processes will improve the efficiency of modern agricultural machinery design. [ABSTRACT FROM AUTHOR]

Flexible job shop scheduling problem is the allocation of available shared resources and the sequencing of processing tasks within a certain period of time to meet certain or certain specific production indicators. The research and application of effective scheduling methods and optimization technologies are the foundation and key to realizing advanced manufacturing and improving production efficiency. Improving the production scheduling plan can greatly improve production efficiency and resource utilization, thereby enhancing the competitiveness of enterprises. Therefore, the production scheduling problem has always been a research hotspot in manufacturing systems. In this paper, we introduce the opposition-based learning strategy and combine it with whale optimization algorithm to solving flexible job shop scheduling problem better. 10 FJSP cases are introduced to test the performance of our algorithm and other comparison algorithms. The results obtrain show that our algorithm is more better and practical than other algorithm when dealing with FJSP cases.

The recent progress in CuMnAs and Mn3X (X = Sn, Ge, Pt) shows that antiferromagnets (AFMs) provide a promising platform for advanced spintronics device innovations. Most recently, a switchable Fermi‐arc is discovered by the ARPES technique in antiferromagnet NdBi, but the knowledge about electron‐transport property and the manipulability of the magnetic structure in NdBi is still vacant to date. In this study, SdH oscillations are successfully verified from the Dirac surface states (SSs) with 2‐dimensionality and nonzero Berry phase. Particularly, it is observed that the spin‐flop transition only appears when the external magnetical field is applied along [001] direction, and features obvious hysteresis for the first time in NdBi, which provides a powerful handle for adjusting the spin texture in NdBi. Crucially, the DFT shows the Dirac cone and the Fermi arc strongly depend on the high‐order magnetic structure of NdBi and further reveals the orbital magnetic moment of Nd plays a crucial role in fostering the peculiar SSs, leading to unveil the mystery of the band‐splitting effect and to manipulate the electronic transport, high‐effectively, in the thin film works in NdBi. It is believed that this study provides important guidance for the development of new antiferromagnet‐based spintronics devices based on cutting‐edge rare‐earth monopnictides. [ABSTRACT FROM AUTHOR]

To achieve the rapid recognition and accurate picking of Camellia oleifera fruits, a binocular vision system composed of two industrial cameras was used to collect images of Camellia oleifera fruits in natural environments. The YOLOv7 convolutional neural network model was used for iterative training, and the optimal weight model was selected to recognize the images and obtain the anchor frame region of the Camellia oleifera fruits. The local binary pattern (LBP) maps of the anchor frame region were extracted and matched by using the normalized correlation coefficient template matching algorithm to obtain the positions of the center point in the left and right images. The recognition experimental results showed that the accuracy rate, recall rate, mAP and F1 of the model were 97.3%, 97.6%, 97.7% and 97.4%. The recognition rate of the Camellia oleifera fruit with slight shading was 93.13%, and the recognition rate with severe shading was 75.21%. The recognition rate of the Camellia oleifera fruit was 90.64% under sunlight condition, and the recognition rate was 91.34% under shading condition. The orchard experiment results showed that, in the depth range of 400–600 mm, the maximum error value of the binocular stereo vision system in the depth direction was 4.279 mm, and the standard deviation was 1.142 mm. The detection and three-dimensional positioning accuracy of the binocular stereo vision system for Camellia oleifera fruits could basically meet the working requirements of the Camellia oleifera fruit-picking robot. [ABSTRACT FROM AUTHOR]

In view of the current situation of the low degree of mechanized harvesting of rape shoots, combined with the study of the material characteristics of rape shoots, the core components of the harvester were designed and analyzed, and a rape shoots harvester was designed and manufactured. The front-end cutter of the harvester cuts the stalks of rape shoots, while the clamping and conveying device transports and steers the stalks flexibly to achieve low damage and orderly harvesting. The forward speed of the machine, the speed of the clamping belt and the clamping gap were selected as the test factors, while the rate of missed cut, missed clamping, and plant damage were selected as the evaluation indexes for the single-factor and response surface optimization tests. Field validation test showed that the machine could effectively cut and transport rape shoots at a forward speed, clamping belt speed and clamping gap of 0.42 m/s, 0.89 m/s and 11.43 mm, respectively (missed cut rate, 2.63%; missed clamp rate, 4.84%; and plant damage rate, 5.22%). This study provides a reference for the research and optimization of the flexible harvesting device for rape shoots. [ABSTRACT FROM AUTHOR]

Existing calibration methods for contact parameters of soil discrete elements are primarily based on a single physical property of soil (e.g., natural accumulation angle and shear characteristics). To solve this limitation, a calibration method based on the area difference method was proposed in accordance with the actual operation effect of ridge and furrow opener. The typical clay loam in the middle and lower reaches of the Yangtze River (moisture content of 20.66% ± 1%) was used as the research object. The Hertz–Mindlin with JKR Cohesion contact model was selected, and the static friction factor and rolling friction factor between soil and 65Mn steel were determined by inclined plane mechanics method. Soil tank ridge and furrow opening experiments and quadratic orthogonal rotation combined tests were carried out. MATLAB software was used to carry out polynomial fitting and the constant integral solution to the ridge and the cross-sectional contour data of the furrow obtained from the measured and simulated ridge and furrow opening experiments to establish the regression model of area difference. The optimization function in Design-Expert software was adopted. The optimal parameter combination was obtained by optimizing the regression model with the minimum area difference as the target. Based on the above parameter combination, the relative error of cross-sectional area of the furrow that was obtained by simulation test and soil tank test was 9.15%. Finally, the comparison of the traction resistance of the simulation and the soil tank test at the stable working stage indicated that the relative error between the simulated value and the measured value was 10.4%, which is less than the acceptable error of 15% in general statistics and within a reasonable range. The results showed that the particle movement and mechanical properties of the soil simulation model were basically consistent with the actual soil after parameter optimization and calibration. In this study, a precise discrete element simulation model of the typical clay loam in the middle and lower reaches of the Yangtze River based on the area difference method was constructed, which lays a theoretical basis for later exploration of the interaction mechanism between the typical clay loam and the soil contact components in the middle and lower reaches of the Yangtze River. [ABSTRACT FROM AUTHOR]

Carbon-coated SnO2 nanocomposites were synthesized successfully by the hydrothermal method and carbonization at 500 °C with glucose and SnCl2·2H2O as precursor materials. The SnO2/C nanocomposites were characterized by various techniques such as X-ray powder diffraction (XRD), scanning electron microscopy (SEM), high-resolution transmission electron microscopy (HR-TEM), Raman spectra, and electrochemical analyses. It was demonstrated that SnO2/C-0, SnO2/C-5, SnO2/C-15, SnO2/C-30, and SnO2/C-50 had initial discharge capacities of 1359.2, 1626.8, 2124.9, 1525.8, and 1349.4 mAhg−1, respectively. In particular, the SnO2/C-15 sample exhibited excellent high reversible lithium storage capacity, good rate capability, and cycling stability. The electrodes show a long cycling ability and high charge/discharge capacity due to the presence of carbon. [ABSTRACT FROM AUTHOR]

Camellia oleifera fruits are randomly distributed in an orchard, and the fruits are easily blocked or covered by leaves. In addition, the colors of leaves and fruits are alike, and flowers and fruits grow at the same time, presenting many ambiguities. The large shock force will cause flowers to fall and affect the yield. As a result, accurate positioning becomes a difficult problem for robot picking. Therefore, studying target recognition and localization of Camellia oleifera fruits in complex environments has many difficulties. In this paper, a fusion method of deep learning based on visual perception and image processing is proposed to adaptively and actively locate fruit recognition and picking points for Camellia oleifera fruits. First, to adapt to the target classification and recognition of complex scenes in the field, the parameters of the You Only Live Once v7 (YOLOv7) model were optimized and selected to achieve Camellia oleifera fruits' detection and determine the center point of the fruit recognition frame. Then, image processing and a geometric algorithm are used to process the image, segment, and determine the morphology of the fruit, extract the centroid of the outline of Camellia oleifera fruit, and then analyze the position deviation of its centroid point and the center point in the YOLO recognition frame. The frontlighting, backlight, partial occlusion, and other test conditions for the perceptual recognition processing were validated with several experiments. The results demonstrate that the precision of YOLOv7 is close to that of YOLOv5s, and the mean average precision of YOLOv7 is higher than that of YOLOv5s. For some occluded Camellia oleifera fruits, the YOLOv7 algorithm is better than the YOLOv5s algorithm, which improves the detection accuracy of Camellia oleifera fruits. The contour of Camellia oleifera fruits can be extracted entirely via image processing. The average position deviation between the centroid point of the image extraction and the center point of the YOLO recognition frame is 2.86 pixels; thus, the center point of the YOLO recognition frame is approximately considered to be consistent with the centroid point of the image extraction. [ABSTRACT FROM AUTHOR]

Transition metal oxides Fe2O3 as lithium‐ion battery anode has aroused intense interest as a result of its high capacity (1007 mA h g−1). Nevertheless, the significant volume expansion during the cycling procession causes its capacity to decay sharply as the anode of lithium‐ion battery. The size and morphology of materials are important factors improving the stability of electrode materials. However, most of the excellent morphology design needs complex processes. The single‐crystalline erythrocyte‐like α‐Fe2O3 nanoparticles are synthesized by one‐step hydrothermal method to improve the electrochemical properties of the α‐Fe2O3 anode, and the Li+ storage kinetics of the erythrocyte‐like α‐Fe2O3 anode are investigated. As a lithium‐ion battery anode material, the erythrocyte‐like α‐Fe2O3 anode exhibits an eminent reversible capacity of 1200.2 mA h g−1 at 0.1 C after 100 cycles. In comparison to raw α‐Fe2O3, the erythrocyte‐like α‐Fe2O3 performs with a better rate property. The special morphological design can effectively improve the stability of α‐Fe2O3 electrode materials. [ABSTRACT FROM AUTHOR]

In order to solve the problems of high labor intensity and low production efficiency in the cultivation of hemp in hilly areas, the seed arrangement performance of self-propelled hemp seeders was studied. According to the cultivation mode of hemp for the fiber industry in Yunnan, Sichuan, and other hilly areas, the seed metering device for the hemp industry was designed, the seed metering mechanism of hemp was analyzed, and the theoretical value range of design parameters of its key components was determined. The row of kind of wheel speed is obtained by single factor experiment, hole diameter and hole depth and uniformity of the seed, the seed of change rule, on the basis of the quadratic regression orthogonal rotation combination test, two indexes of the regression model, using the regression model of the design parameter optimization, and seeder row of kind of verification test, the results show that: when the rotation speed of the metering wheel was 90.0 r/min, the diameter of the hole was 10.4 mm, and the depth of the hole was 6.4 mm, the coefficient of variation of seeding uniformity of seeding machine was less than 45%, and the coefficient of variation for consistency of seed quantity in each row was less than 8%. The operation of the self-walking industrial hemp seeder met the requirements of fiber industrial hemp planting in hilly areas. [ABSTRACT FROM AUTHOR]

In order to reduce the chopping power consumption of a flat hob chopper (referred to herein as chopper) on the premise of ensuring the chopping effect of the chopper, the mathematical model of optimal design of chopper is established in this paper with the minimum chopping power as the objective. With the help of MATLAB software, the mathematical model is solved. The chopping power curves of each point on the chopper blade edge line before and after the optimization of structural parameters are generated. The results indicate that when the coordinate value of point A on the blade edge line on the Z axis is 0.7 m; the included angle between the bottom surface of the blade and the axis of the cutter roll is 6°. When the radius of the chopper is 0.11 m, the chopper can obtain the theoretical minimum chopping power. The analysis result of chopping power curve is the chopping power after structural parameter optimization is reduced by about 25.50% compared with that before optimization. The choppers before and after the optimization of structural parameters was trial manufactured and sequentially mounted on the performance test bench of the chopping system of the forage ramie harvester. The test results show the standard-length rate of ramie stalk chopped by the choppers before and after the optimization of structural parameters were 92.96% and 92.84%, respectively, which were extremely close to each other, indicating that the optimization of structural parameters has no influence on the chopping effect of the chopper. The chopping power of the chopper is reduced by 22.25% after optimization, which is close to the software analysis value (25.50%), indicating that the optimization result is accurate and reliable. This study can provide parameter foundation and an optimization method for lowering chopping power consumption of the chopper. [ABSTRACT FROM AUTHOR]

The electrochemical CO2 reduction reaction (CO2RR) is a promising method to decrease the CO2 concentration in the atmosphere and produce high value-added chemicals simultaneously. Catalysts play a central role in the CO2RR system, and can determine the conversion efficiency and product species. Single-atom catalysts (SACs), a new class of catalysts, have been extensively employed in the CO2RR due to their high activities, selectivity and maximum atom utilization efficiency. In this review, an overview of the recent progress of SACs for the CO2RR is provided with respect to two types of catalyst supports including graphene (Gr)-based nanomaterials and conjugated macrocycle (CM)-based complexes. Specifically, we focus on significant influencing factors on the activity and selectivity of the modeled catalysts, such as heteroatom doping, ligand effects and bimetals. Insights on the intrinsic connection between electronic structures and catalytic properties are summarized. Moreover, the stability and the dynamic structural change of SACs under operating conditions are also discussed. Finally, some challenges and perspectives are raised for the future development of efficient SACs based on Gr and CM supports. [ABSTRACT FROM AUTHOR]

Perylene diimide (PDI) is one of the most intensively studied building blocks for the construction of non‐fullerene acceptors (NFAs). In this contribution, based on combination of the direct and indirect linkage manners of PDI units at the bay position, a propeller‐shaped PDI hexamer T‐DPDI was designed and synthesized. The singly bonded PDI dimer DPDI and the benzene ring cored PDI trimer TPDI were synthesized for comparison. The photovoltaic performances of these three PDI derivatives were investigated using the commercially available PTB7‐Th as electron donor. A best power conversion efficiency (PCE) of 6.58% was obtained for T‐DPDI based organic solar cells (OSCs), which is higher than those of DPDI and TPDI based ones. The superior photovoltaic performance of T‐DPDI can be ascribed to its stronger absorption and more favorable morphology. This study presents an interesting example of improving the photovoltaic performances of PDI based NFAs by hybridizing the direct and indirect linkage manners. [ABSTRACT FROM AUTHOR]

In the simulation analysis of the lily harvesting process, the intrinsic parameters of the lily bulb and the contact parameters between the lily bulb and the lily mechanized harvesting equipment (Q235 steel) are deficient. Thus, the three-axis size, density, moisture content, Poisson's ratio, elastic modulus, and other parameters of lily bulbs are measured in this paper with lily bulbs as the research object. Moreover, the discrete element model of the lily bulb was established using 3D scanning technology. The contact parameters between the lily bulb and Q235 steel were calibrated through bench test and simulation parameter test. The relative error between the measured value of the lily bulb accumulation angle and the simulated value is taken as response value to calibrate three parameters (collision recovery coefficient, static friction coefficient, and dynamic friction coefficient between lily bulbs). A regression model of the relative error of the stacking angle and three parameters is established, and the response surface is optimized. The results demonstrate that collision recovery coefficient, static friction coefficient, and dynamic friction coefficient between lily bulb and Q235 steel are 0.301, 0.423, and 0.063, respectively; these coefficients between lily bulbs are 0.455, 0.425, and 0.158, respectively. Additionally, a better combination of parameters is adopted to perform the simulation stacking test. The measured stacking angle is 32.31°, which is 0.34% in error with the stacking angle obtained by the physical stacking test. The test results suggest that the discrete element model and contact parameters of the lily bulb can be used in the discrete element simulation test. Furthermore, these research results could provide references for simulation tests, such as mechanized harvesting and post-harvest processing, of lily. [ABSTRACT FROM AUTHOR]

Cu nanoparticles with different sizes, morphology, and surface structures exhibit distinct activity and selectivity toward CO2 reduction reaction, while the reactive sites and reaction mechanisms are very controversial in experiments. In this study, we demonstrate the dynamic structure change of Cu clusters on graphite‐like carbon supports plays an important role in the multicarbon production by combining static calculations and ab‐initio molecular dynamic simulations. The mobility of Cu clusters on graphite is attributed to the near‐degenerate energies of various adsorption configurations, as the interaction between Cu atoms and surface C atoms is weaker than that of CuCu bonds in the tight cluster form. Such structure change of Cu clusters leads to step‐like irregular surface structures and appropriate interparticle distances, increasing the selectivity of multicarbon products by reducing the energy barriers of CC coupling effectively. In contrast, the large ratio of edge and corner sites on Cu clusters is responsible for the increased catalytic activity and selectivity for CO and H2 compared with Cu(100) surface, instead of hydrocarbon products like methane and ethylene. The detailed study reveals that the dynamic structure change of the catalysts results in roughened surface morphologies during catalytic reactions and plays an essential role in the selectivity of CO2 electro‐reduction, which should be paid more attention for studies on the reaction mechanisms. [ABSTRACT FROM AUTHOR]