An improved YOLO v4 used for grape detection in unstructured environment

Visual recognition is the most critical function of a harvesting robot, and the accuracy of the harvesting action is based on the performance of visual recognition. However, unstructured environment, such as severe occlusion, fruits overlap, illumination changes, complex backgrounds, and even heavy fog weather, pose series of serious challenges to the detection accuracy of the recognition algorithm. Hence, this paper proposes an improved YOLO v4 model, called YOLO v4+, to cope with the challenges brought by unstructured environment. The output of each Resblock_body in the backbone is processed using a simple, parameterless attention mechanism for full dimensional refinement of extracted features. Further, in order to alleviate the problem of feature information loss, a multi scale feature fusion module with fusion weight and jump connection structure was pro-posed. In addition, the focal loss function is adopted and the hyperparameters α, γ are adjusted to 0.75 and 2. The experimental results show that the average precision of the YOLO v4+ model is 94.25% and the F1 score is 93%, which is 3.35% and 3% higher than the original YOLO v4 respectively. Compared with several state-of-the-art detection models, YOLO v4+ not only has the highest comprehensive ability, but also has better generalization ability. Selecting the corresponding augmentation method for specific working condition can greatly improve the model detection accuracy. Applying the proposed method to harvesting robots may enhance the applicability and robustness of the robotic system

Flexible Actuators Based on Conductive Polymer Ionogels and Their Electromechanical Modeling

High-performance flexible actuators, integral components of soft robotics, hold promise for advancing applications in safe human–robot interactions, healthcare, and various other fields. Notable among these actuators are flexible electrochemical systems, recognized for their merits in low-voltage manipulation, rapid response speed, and cost-effectiveness. However, the optimization of output strain, response speed, and stability presents a significant challenge in this domain. Despite the application of diverse electrochemically active materials to enhance actuation performance, a critical need persists for corresponding electrical-mechanical models to comprehensively grasp actuation mechanisms. In this study, we introduce a novel electrochemical actuator that utilizes conductive polymer ionogel as active electrodes. This ionogel exhibits exceptional properties, including high conductivity, flexibility, and electrochemical activity. Our electrochemical actuators exhibit noteworthy bending strain capabilities and rapid response rates, achieving frequencies up to 10 Hz at a modest voltage of 1 V. An analytical model integrating ion migration and dynamic processes has been established to elucidate actuator behavior. Simulation results highlight that electrodes characterized by low resistance and high capacitance are optimal for simultaneous enhancement of bending strain and blocking force. However, the augmentation of Young’s modulus, while increasing blocking force, compromises bending strain. Furthermore, a larger aspect ratio proves beneficial for unidirectional stress output, leading to increased bending strain, while actuator blocking force diminishes with greater length. These findings underscore the intricate interplay between material properties and dimensions in optimizing the performance of flexible electrochemical actuators. This work provides important practical and theoretical guidance for the manufacture of high-performance flexible actuators and the search for new smart materials

An Investigation of the Wear on Silicon Surface at High Humidity

Using an atomic force microscope (AFM), the wear of monocrystalline silicon (covered by a native oxide layer) at high humidity was investigated. The experimental results indicated that tribochemistry played an important role in the wear of the silicon at different relative humidity levels (RH = 60%, 90%). Since the tribochemical reactions were facilitated at 60% RH, the wear of silicon was serious and the friction force was around 1.58 μN under the given conditions. However, the tribochemical reactions were restrained when the wear pair was conducted at high humidity. As a result, the wear of silicon was very slight and the friction force decreased to 0.85 μN at 90% RH. The slight wear of silicon at high humidity was characterized by etching tests. It was demonstrated that the silicon sample surface was partly damaged and the native oxide layer on silicon sample surface had not been totally removed during the wear process. These results may help us optimize the tribological design of dynamic microelectromechanical systems working in humid conditions

Molecular Dynamics Study on the Reverse Osmosis Using Multilayer Porous Graphene Membranes

In this study, the reverse osmosis (RO) of a salt solution was investigated using a molecular dynamics method to explore the performance of a multilayer porous graphene membrane. The effects of the salt solution concentration, pressure, layer separation and pore offset on the RO performance of the membrane were investigated and the influences of the number of layers and the gradient structure were determined. The results show that as the salt solution concentration increases, the energy barrier of the water molecules passing through the bilayer porous graphene membranes changes slightly, indicating that the effect of the water flux on the membrane can be ignored. The salt rejection performance of the membrane improves with an increase in the concentration of the salt solution. When the pressure is increased, the energy barrier decreases, the water flux increases and the salt rejection decreases. When the layer separation of the bilayer porous graphene membrane is the same as the equilibrium spacing of the graphene membrane, the energy barrier is the lowest and the membrane water flux is the largest. The energy barrier of the bilayer porous graphene membrane increases with increasing layer separation, resulting in a decrease in the water flux of the membrane. The salt rejection increases with increasing layer separation. The water flux of the membrane decreases as the energy barrier increases with increasing pore offset and the salt rejection increases. The energy barrier effect is more pronounced for a larger number of graphene layers and the water flux of the membrane decreases because it is more difficult for the water molecules to pass through the porous graphene membrane. However, the salt rejection performance improves with the increase in the number of layers. The gradient pore structure enhances the energy barrier effect of the water molecules permeating through the membrane and the water flux of the membrane decreases. The salt rejection performance is improved by the gradient pore structure. The research results provide theoretical guidance for research on the RO performance of porous graphene membranes and the design of porous graphene membranes

Flexible Wet-Spun PEDOT:PSS Microfibers Integrating Thermal-Sensing and Joule Heating Functions for Smart Textiles

Multifunctional fiber materials play a key role in the field of smart textiles. Temperature sensing and active thermal management are two important functions of smart fabrics, but few studies have combined both functions in a single fiber material. In this work, we demonstrate a temperature-sensing and in situ heating functionalized conductive polymer microfiber by exploiting its high electrical conductivity and thermoelectric properties. The conductive polymer microfibers were prepared by wet-spinning the PEDOT:PSS aqueous dispersion with ionic liquid additives, which was used to enhance the electrical and mechanical properties of the final microfibers. The thermoelectric properties of these microfibers were further studied. Due to their excellent flexibility and mechanical properties, these fibers can be easily integrated into commercial fabrics for the manufacture of smart textiles through knitting. We further demonstrated a smart glove with integrated temperature-sensing and in situ heating functions, and further explored thermoelectric fiber-based temperature-sensing array fabric. These works combine the thermoelectric properties and heating function of conductive polymer fibers, providing new insights that enable further development of high-performance, multifunctional wearable smart textiles

High-Sensitivity Pressure Sensors Based on a Low Elastic Modulus Adhesive

With the rapid development of intelligent applications, the demand for high-sensitivity pressure sensor is increasing. However, the simple and efficient preparation of an industrial high-sensitivity sensor is still a challenge. In this study, adhesives with different elastic moduli are used to bond pressure-sensitive elements of double-sided sensitive grids to prepare a highly sensitive and fatigue-resistant pressure sensor. It was observed that the low elastic modulus adhesive effectively produced tensile and compressive strains on both sides of the sensitive grids to induce greater strain transfer efficiency in the pressure sensor, thus improving its sensitivity. The sensitivity of the sensor was simulated by finite element analysis to verify that the low elastic modulus adhesive could enhance the sensitivity of the sensor up to 12%. The preparation of high-precision and fatigue-resistant pressure sensors based on low elastic modulus, double-sided sensitive grids makes their application more flexible and convenient, which is urgently needed in the miniaturization and integration electronics field

Temperature-responsive peristome-structured smart surface for the unidirectional controllable motion of large droplets

Abstract The manipulation of fast, unidirectional motion for large droplets shows important applications in the fields of fog collection and biochemical reactions. However, driving large droplets (>5 μL) to move directionally and quickly remains challenging due to the nonnegligible volume force. Herein, we fabricated a scalable, bionic peristome substrate with a microcavity width of 180 μm using a 3D printing method, which could unidirectionally drive a large water droplet (~8 μL) at a speed reaching 12.5 mm/s by temperature-responsive wettability. The substrate surface was grafted with PNIPAAm, which could reversibly change its wettability in response to temperature, thereby enabling a temperature-responsive smart surface that could regulate droplet movement in real-time by changing the temperature. A series of temperature-responsive smart patterns were designed to induce water transport along specific paths to further realize controllable droplet motion with the antibacterial treatment of predesignated areas. The ability to achieve temperature-responsive unidirectional motion and dynamic control of droplet movement could allow programmable fluidic biosensors and precision medical devices. A temperature-responsive smart surface was produced to control the unidirectional motion of large droplets between spreading and pinning movement by changing the surface wettability