Hollow Nanoboxes Cu2-x S@ZnIn2 S4 Core-Shell S-Scheme Heterojunction with Broad-Spectrum Response and Enhanced Photothermal-Photocatalytic Performance.

Major issues in photocatalysis include improving charge carrier separation efficiency at the interface of semiconductor photocatalysts and rationally developing efficient hierarchical heterostructures. Surface continuous growth deposition is used to make hollow Cu2-x S nanoboxes, and then simple hydrothermal reaction is used to make core-shell Cu2-x S@ZnIn2 S4 S-scheme heterojunctions. The photothermal and photocatalytic performance of Cu2-x S@ZnIn2 S4 is improved. In an experimental hydrogen production test, the Cu2-x S@ZnIn2 S4 photocatalyst produces 4653.43 µmol h-1 g-1 of hydrogen, which is 137.6 and 13.8 times higher than pure Cu2-x S and ZnIn2 S4 , respectively. Furthermore, the photocatalyst exhibits a high tetracycline degradation efficiency in the water of up to 98.8%. For photocatalytic reactions, the hollow core-shell configuration gives a large specific surface area and more reactive sites. The photocatalytic response range is broadened, infrared light absorption enhanced, the photothermal effect is outstanding, and the photocatalytic process is promoted. Meanwhile, characterizations, degradation studies, active species trapping investigations, energy band structure analysis, and theoretical calculations all reveal that the S-scheme heterojunction can efficiently increase photogenerated carrier separation. This research opens up new possibilities for future S-scheme heterojunction catalyst design and development.

Online Extraction of Pose Information of 3D Zigzag-Line Welding Seams for Welding Seam Tracking.

Three-dimensional (3D) zigzag-line welding seams are found extensively in the manufacturing of marine engineering equipment, heavy lifting equipment, and logistics transportation equipment. Currently, due to the large amount of calculation and poor real-time performance of 3D welding seam detection algorithms, real-time tracking of 3D zigzag-line welding seams is still a challenge especially in high-speed welding. For the abovementioned problems, we proposed a method for the extraction of the pose information of 3D zigzag-line welding seams based on laser displacement sensing and density-based clustering point cloud segmentation during robotic welding. after thee point cloud data of the 3D zigzag-line welding seams was obtained online by the laser displacement sensor, it was segmented using theρ-Approximate DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm. In the experiment, high-speed welding was performed on typical low-carbon steel 3D zigzag-line welding seams using gas metal arc welding. The results showed that when the welding velocity was 1000 mm/min, the proposed method obtained a welding seam position detection error of less than 0.35 mm, a welding seam attitude estimation error of less than two degrees, and the running time of the main algorithm was within 120 ms. Thus, the online extraction of the pose information of 3D zigzag-line welding seams was achieved and the requirements of welding seam tracking were met.

Welding Seam Trajectory Recognition for Automated Skip Welding Guidance of a Spatially Intermittent Welding Seam Based on Laser Vision Sensor.

To solve the problems of low teaching programming efficiency and poor flexibility in robot welding of complex box girder structures, a method of seam trajectory recognition based on laser scanning displacement sensing was proposed for automated guidance of a welding torch in the skip welding of a spatially intermittent welding seam. Firstly, a laser scanning displacement sensing system for measuring angles adaptively is developed to detect corner features of complex structures. Secondly, a weld trajectory recognition algorithm based on Euclidean distance discrimination is proposed. The algorithm extracts the shape features by constructing the characteristic triangle of the weld trajectory, and then processes the set of shape features by discrete Fourier analysis to solve the feature vector used to describe the shape. Finally, based on the Euclidean distance between the feature vector of the test sample and the class matching library, the class to which the sample belongs is identified to distinguish the weld trajectory. The experimental results show that the classification accuracy rate of four typical spatial discontinuous welds in complex box girder structure is 100%. The overall processing time for weld trajectory detection and classification does not exceed 65 ms. Based on this method, the field test was completed in the folding special container production line. The results show that the system proposed in this paper can accurately identify discontinuous welds during high-speed metal active gas arc welding (MAG) welding with a welding speed of 1.2 m/min, and guide the welding torch to automatically complete the skip welding, which greatly improves the welding manufacturing efficiency and quality stability in the processing of complex box girder components. This method does not require a time-consuming pre-welding teaching programming and visual inspection system calibration, and provides a new technical approach for highly efficient and flexible welding manufacturing of discontinuous welding seams of complex structures, which is expected to be applied to the welding manufacturing of core components in heavy and large industries such as port cranes, large logistics transportation equipment, and rail transit.

Revealing the inherent running mechanism of quadruped mammals based on a novel bionic stiffness model.

In this paper, the limb of a goat is chosen as the research object, and according to mammalian anatomy, a bionic model called the quasi inverted pendulum with "J" curve spring (QIPJCS) model with nonlinear stiffness is built, and the equations of motion are derived. Based on these equations, the advantages of the QIPJCS model are illustrated from the aspect of the stable motion region by the SFA (step-to-fall analysis) numerical simulation method. These results are compared with the traditional SLIP model. Furthermore, the ARM (Apex-Return-Map) of this model is built, and the fixed points are analyzed. Finally, according to the locomotion law of goats running with gallop gaits and the analysis of the dead-point support effect, the dynamic motion mechanism of goat limbs is elucidated, and the equivalent mechanism model is built. Based on the mechanism, the dynamic mechanical analysis indicates that the joint driving torque can be minimized to conserve energy by optimizing the landing angle. The running mechanism research of quadruped mammals, which is based on the novel bionic stiffness model, provides theoretical support for the design of high-performance mechanical legs and the motion control of bionic robots.

Uncertainties in Pollution and Risk Assessments of Heavy Metals in Lake Sediments Using Regional Background Soils in China.

Background soils are frequently utilized as a surrogate to assess pollution levels and environmental risks of heavy metals in Chinese lakes. However, there remains a lack of understanding regarding the reliability and uncertainty of such assessments. Here, we determined heavy metals (As, Cd, Co, Cr, Cu, Hg, Ni, Pb, and Zn) in sediment cores from five rural lakes in North China to evaluate the reliability and uncertainty of the assessments using background soils by comparing them with assessments based on background sediments. Comparative studies reveal large uncertainties in the assessments using background soils. Among these metals, uncertainties for Hg and Cd are relatively large, whereas those for the other metals are minor. This discrepancy is due to the considerably higher natural variability of Hg and Cd in soils and sediments in comparison to the other metals. Generally, assessments utilizing background soils underestimate pollution levels and risks of Hg but overestimate those of Cd in these lakes. Despite limited human activities around the lakes, they still received a considerable influx of heavy metals via regional atmospheric transport. Assessments of the nine metals indicate moderate to considerable ecological risks in these lakes. The risks are contributed primarily (78-89%) by Hg and Cd. This study underscores the substantial uncertainties in assessing heavy metal pollution and risks using regional background soils and emphasizes the importance of controlling atmospheric emissions of Hg and Cd to mitigate pollution in rural and remote water bodies in China.

Na-doped g-C3N4/NiO 2D/2D laminated p-n heterojunction nanosheets toward optimized photocatalytic performance.

Na-doped g-C3N4/NiO 2D/2D laminated p-n heterojunction nanosheets are fabricated by facile calcination and hydrothermal methods. The average thickness of g-C3N4 nanosheets is ∼1.388 nm, and the ultrathin structure allows for a high specific surface area and enough surface active sites, increasing the surface reactivity. The flower ball like structure of NiO increases the light utilization rate. Na doping accelerates charge separation and transport by increasing the electrical conductivity. The g-C3N4 and NiO nanosheets form 2D/2D laminated structures, and the spherical structure can suppress the agglomeration of 2D nanosheets, which could realize adequate interface contact and form efficient p-n heterojunctions. The p-n heterostructure builds an internal electric field to accelerate spatial charge separation. Under visible light irradiation, the photocatalytic degradation efficiency for ciprofloxacin and the hydrogen production rate of Na-doped g-C3N4/NiO are up to 99.0%, and 2299.32 µmol h-1 g-1, respectively, which are several times higher than those of the pristine one. The fabrication strategy for 2D/2D laminated heterojunctions may provide new insights for the preparation of novel laminated photocatalysts with high performance.