Given the limited operating ability of a single robotic arm, dual-arm collaborative operations have become increasingly prominent. Compared with the electrically driven dual-arm manipulator, due to the unknown heavy load, difficulty in measuring contact forces, and control complexity during the closed-chain object transportation task, the hydraulic dual-arm manipulator (HDM) faces more difficulty in accurately tracking the desired motion trajectory, which may cause object deformation or even breakage. To overcome this problem, a compliance motion control method is proposed in this paper for the HDM. The mass parameter of the unknown object is obtained by using an adaptive method based on velocity error. Due to the difficulty in obtaining the actual internal force of the object, the pressure signal from the pressure sensor of the hydraulic system is used to estimate the contact force at the end-effector (EE) of two hydraulic manipulators (HMs). Further, the estimated contact force is used to calculate the actual internal force on the object. Then, a compliance motion controller is designed for HDM closed-chain collaboration. The position and internal force errors of the object are reduced by the feedback of the position, velocity, and internal force errors of the object to achieve the effect of the compliance motion of the HDM, i.e., to reduce the motion error and internal force of the object. The required velocity and force at the EE of the two HMs, including the position and internal force errors of the object, are inputted into separate position controllers. In addition, the position controllers of the two individual HMs are designed to enable precise motion control by using the virtual decomposition control method. Finally, comparative experiments are carried out on a hydraulic dual-arm test bench. The proposed method is validated by the experimental results, which demonstrate improved object position accuracy and reduced internal force.

Passive vibration isolation systems have been widely applied due to their low power consumption and high reliability. Nevertheless, the design of vibration isolators is usually limited by the narrow space of installation, and the requirement of heavy loads needs the high supporting stiffness that leads to the narrow isolation frequency band. To improve the vibration isolation performance of passive isolation systems for dynamic loaded equipment, a novel modular quasi-zero stiffness vibration isolator (MQZS-VI) with high linearity and integrated fluid damping is proposed. The MQZS-VI can achieve high-performance vibration isolation under a constraint mounted space, which is realized by highly integrating a novel combined magnetic negative stiffness mechanism into a damping structure: The stator magnets are integrated into the cylinder block, and the moving magnets providing negative-stiffness force also function as the piston supplying damping force simultaneously. An analytical model of the novel MQZS-VI is established and verified first. The effects of geometric parameters on the characteristics of negative stiffness and damping are then elucidated in detail based on the analytical model, and the design procedure is proposed to provide guidelines for the performance optimization of the MQZS-VI. Finally, static and dynamic experiments are conducted on the prototype. The experimental results demonstrate the proposed analytical model can be effectively utilized in the optimal design of the MQZS-VI, and the optimized MQZS-VI broadened greatly the isolation frequency band and suppressed the resonance peak simultaneously, which presented a substantial potential for application in vibration isolation for dynamic loaded equipment.

Piezoelectric actuators are a class of actuators that precisely transfer input electric energy into displacement, force, or movement outputs efficiently via inverse piezoelectric effect-based electromechanical coupling. Various types of piezoelectric actuators have sprung up and gained widespread use in various applications in terms of compelling attributes, such as high precision, flexibility of stoke, immunity to electromagnetic interference, and structural scalability. This paper systematically reviews the piezoelectric materials, operating principles, representative schemes, characteristics, and potential applications of each mainstream type of piezoelectric actuator. Herein, we intend to provide a more scientific and nuanced perspective to classify piezoelectric actuators into direct and indirect categories with several subcategories. In addition, this review outlines the pros and cons and the future development trends for all kinds of piezoelectric actuators by exploring the relations and mechanisms behind them. The rich content and detailed comparison can help build an in-depth and holistic understanding of piezoelectric actuators and pave the way for future research and the selection of practical applications.

3D printing is a versatile technology capable of rapidly fabricating intricate geometric structures and enhancing the performance of flexible devices in comparison to conventional fabrication methods. However, 3D-printed devices are susceptible to failure as a result of minuscule structural impairments, thereby impacting their overall durability. The utilization of self-healing, biodegradable materials in 3D printing holds immense potential for increasing the longevity and safety of devices, thereby expanding the application prospects for such devices. Nevertheless, enhancing the self-repairing capability of devices and refining the 3D printing performance of self-healing materials are still considerable challenges that need to be addressed to achieve optimal outcomes. This paper reviews recent developments in the field of advancements in 3D printing using self-healing and biodegradable materials. First, it investigates self-healing and biodegradable materials that are compatible with 3D printing techniques, discussing their printability, material properties, and factors that influence print quality. Then, it explores practical applications of self-healing and biodegradable 3D printing technology in depth. Finally, it critically offers practical perspectives on this topic.

Owing to their excellent performance and large design space, curvilinear fiber-reinforced composite structures have gained considerable attention in engineering fields such as aerospace and automobile. In addition to the stiffness and strength of such structures, their stability also needs to be taken into account in the design. This study proposes a level-set-based optimization framework for maximizing the buckling load of curvilinear fiber-reinforced composite structures. In the proposed method, the contours of the level set function are used to represent fiber paths. For a composite laminate with a certain number of layers, one level set function is defined by radial basis functions and expansion coefficients for each layer. Furthermore, the fiber angle at an arbitrary point is the tangent orientation of the contour through this point. In the finite element of buckling, the stiffness and geometry matrices of an element are related to the fiber angle at the element centroid. This study considers the parallelism constraint for fiber paths. With the sensitivity calculation of the objective and constraint functions, the method of moving asymptotes is utilized to iteratively update all the expansion coefficients regarded as design variables. Two numerical examples under different boundary conditions are given to validate the proposed approach. Results show that the optimized curved fiber paths tend to be parallel and equidistant regardless of whether the composite laminates contain holes or not. Meanwhile, the buckling resistance of the final design is significantly improved.

The planetary roller screw mechanism (PRSM) is a novel precision transmission mechanism that realizes the conversion between linear and rotary motions. The contact characteristics of helical surfaces directly determine PRSM’s performance in load-carrying capacity and transmission accuracy. Therefore, studying the contact characteristics of PRSM forms the fundamental basis for enhancing its transmission performance. In this study, a three-dimensional parametric analysis method of contact characteristics is proposed based on the PRSM meshing principle and PyVista (a high-level API to the Visualization Toolkit). The proposed method considers the influence of machining errors among various thread teeth. The effects of key machining errors on contact positions and axial clearance, as well as their sensitivities, are analyzed. With excellent solution accuracy, this method exhibits higher calculation efficiency and stronger robustness than the analytical and numerical meshing models. The influence of nominal diameter and pitch errors of the screw, roller, and nut on the axial clearance follows a linear relationship, whereas flank angle errors have negligible effects on the axial clearance. The corresponding influence coefficients for these three machining errors on the axial clearance are 0.623, 0.341, and 0.036. The variations in contact positions caused by individual errors are axisymmetric. Flank angle errors and roller diameter errors result in linear displacements of the contact points, whereas pitch errors cause the contact points to move along the arc of the roller diameter. Based on the proposed three-dimensional parametric contact characteristics analysis method, the Fuzzy C-Means clustering algorithm considering error sensitivity is utilized to establish a component grouping technique in the selective assembly of critical PRSM components, ensuring the rational and consistent clearances based on the given component’s machining errors. This study provides effective guidance for analyzing contact characteristics and grouping in selective assembly for PRSM components. It also presents the proposed method’s potential applicability to similar calculation problems for contact positions and clearances in other transmission systems.

Achieving dynamic compliance for energy-efficient legged robot motion is a longstanding challenge. Although recent predictive control methods based on single-rigid-body models can generate dynamic motion, they all assume infinite energy, making them unsuitable for prolonged robot operation. Addressing this issue necessitates a mechanical structure with energy storage and a dynamic control strategy that incorporates feedback to ensure stability. This work draws inspiration from the efficiency of bio-inspired muscle–tendon networks and proposes a controllable torsion spring leg structure. The design integrates a spring-loaded inverted pendulum model and adopts feedback delays and yield springs to enhance the delay effects. A leg control model that incorporates motor loads is developed to validate the response and dynamic performance of a leg with elastic joints. This model provides torque to the knee joint, effectively reducing the robot’s energy consumption through active or passive control strategies. The benefits of the proposed approach in agile maneuvering of quadruped robot legs in a realistic scenario are demonstrated to validate the dynamic motion performance of the leg with elastic joints with the advantage of energy-efficient legs.

The dynamic motion of quadrupedal robots on challenging terrain generally requires elaborate spatial–temporal kinodynamic motion planning and accurate control at higher refresh rate in comparison with regular terrain. However, conventional quadrupedal robots usually generate relatively coarse planning and employ motion replanning or reactive strategies to handle terrain irregularities. The resultant complex and computation-intensive controller may lead to nonoptimal motions or the breaking of locomotion rhythm. In this paper, a kinodynamic optimization approach is presented. To generate long-horizon optimal predictions of the kinematic and dynamic behavior of the quadruped robot on challenging terrain, we formulate motion planning as an optimization problem; jointly treat the foot’s locations, contact forces, and torso motions as decision variables; combine smooth motion and minimal energy consumption as the objective function; and explicitly represent feasible foothold region and friction constraints based on terrain information. To track the generated motions accurately and stably, we employ a whole-body controller to compute reference position and velocity commands, which are fed forward to joint controllers of the robot’s legs. We verify the effectiveness of the developed approach through simulation and on a physical quadruped robot testbed. Results show that the quadruped robot can successfully traverse a 30° slope and 43% of nominal leg length high step while maintaining the rhythm of dynamic trot gait.

Robots are playing an increasingly important role in engineering applications. Soft robots have promising applications in several fields due to their inherent advantages of compliance, low density, and soft interactions. A soft gripper based on bio-inspiration is proposed in this study. We analyze the cushioning and energy absorption mechanism of human fingertips in detail and provide insights for designing a soft gripper with a variable stiffness structure. We investigate the grasping modes through a large deformation modeling approach, which is verified through experiments. The characteristics of the three grasping modes are quantified through testing and can provide guidance for robotics manipulation. First, the adaptability of the soft gripper is verified by grasping multi-scale and extremely soft objects. Second, a cushioning model of the soft gripper is proposed, and the effectiveness of cushioning is verified by grasping extremely sharp objects and living organisms. Notably, we validate the advantages of the variable stiffness of the soft gripper, and the results show that the soft robot can robustly complete assemblies with a gap of only 0.1 mm. Owing to the unstructured nature of the engineering environment, the soft gripper can be applied in complex environments based on the abovementioned experimental analysis. Finally, we design the soft robotics system with feedback capture based on the inspiration of human catching behavior. The feasibility of engineering applications is initially verified through fast capture experiments on moving objects. The design concept of this robot can provide new insights for bionic machinery.

Additive manufacturing, particularly 3D printing, has revolutionized the manufacturing industry by allowing the production of complex and intricate parts at a lower cost and with greater efficiency. However, 3D-printed parts frequently require post-processing or integration with other machining technologies to achieve the desired surface finish, accuracy, and mechanical properties. Ultra-precision machining (UPM) is a potential machining technology that addresses these challenges by enabling high surface quality, accuracy, and repeatability in 3D-printed components. This study provides an overview of the current state of UPM for 3D printing, including the current UPM and 3D printing stages, and the application of UPM to 3D printing. Following the presentation of current stage perspectives, this study presents a detailed discussion of the benefits of combining UPM with 3D printing and the opportunities for leveraging UPM on 3D printing or supporting each other. In particular, future opportunities focus on cutting tools manufactured via 3D printing for UPM, UPM of 3D-printed components for real-world applications, and post-machining of 3D-printed components. Finally, future prospects for integrating the two advanced manufacturing technologies into potential industries are discussed. This study concludes that UPM is a promising technology for 3D-printed components, exhibiting the potential to improve the functionality and performance of 3D-printed products in various applications. It also discusses how UPM and 3D printing can complement each other.

Robots with transformable tracked mechanisms are widely used in complex terrains because of their high adaptability, and many studies on novel locomotion mechanisms have been conducted to make them able to climb higher obstacles. Developing underactuated transformable mechanisms for tracked robots could decrease the number of actuators used while maintaining the flexibility and obstacle-crossing capability of these robots, and increasing their cost performance. Therefore, the underactuated tracked robots have appreciable research potential. In this paper, a novel tracked robot with a newly proposed underactuated revolute‒revolute‒prismatic (RRP) transformable mechanism, which is inspired by the sit-up actions of humans, was developed. The newly proposed tracked robot has only two actuators installed on the track pulleys for moving and does not need extra actuators for transformations. Instead, it could concentrate the track belt’s tension toward one side, and the unbalanced tension would drive the linkage mechanisms to change its configuration. Through this method, the proposed underactuated design could change its external shape to create support points with the terrain and move its center of mass actively at the same time while climbing obstacles or crossing other kinds of terrains, thus greatly improving the climbing capability of the robot. The geometry and kinematic relationships of the robot and the crossing strategies for three kinds of typical obstacles are discussed. On the basis of such crossing motions, the parameters of links in the robot are designed to make sure the robot has sufficient stability while climbing obstacles. Terrain-crossing dynamic simulations were run and analyzed to prove the feasibility of the robot. A prototype was built and tested. Experiments show that the proposed robot could climb platforms with heights up to 33.3% of the robot’s length or cross gaps with widths up to 43.5% of the robot’s length.

With the continued shrinking of the critical dimensions (CDs) of wafer patterning, the requirements for modeling precision in optical proximity correction (OPC) increase accordingly. This requirement extends beyond CD controlling accuracy to include pattern alignment accuracy because misalignment can lead to considerable overlay and metal-via coverage issues at advanced nodes, affecting process window and yield. This paper proposes an efficient OPC modeling approach that prioritizes pattern-shift-related elements to tackle the issue accurately. Our method integrates careful measurement selection, the implementation of pattern-shift-aware structures in design, and the manipulation of the cost function during model tuning to establish a robust model. Confirmatory experiments are performed on a via layer fabricated using a negative tone development. Results demonstrate that pattern shifts can be constrained within a range of ±1 nm, remarkably better than the original range of ±3 nm. Furthermore, simulations reveal notable differences between post OPC and original masks when considering pattern shifts at locations sensitive to this phenomenon. Experimental validation confirms the accuracy of the proposed modeling approach, and a firm consistency is observed between the simulation results and experimental data obtained from actual design structures.

Small tracking error correction for electro-optical systems is essential to improve the tracking precision of future mechanical and defense technology. Aerial threats, such as “low, slow, and small (LSS)” moving targets, pose increasing challenges to society. The core goal of this work is to address the issues, such as small tracking error correction and aiming control, of electro-optical detection systems by using mechatronics drive modeling, composite velocity–image stability control, and improved interpolation filter design. A tracking controller delay prediction method for moving targets is proposed based on the Euler transformation model of a two-axis, two-gimbal cantilever beam coaxial configuration. Small tracking error formation is analyzed in detail to reveal the scientific mechanism of composite control between the tracking controller’s feedback and the motor’s velocity–stability loop. An improved segmental interpolation filtering algorithm is established by combining line of sight (LOS) position correction and multivariable typical tracking fault diagnosis. Then, a platform with 2 degrees of freedom is used to test the system. An LSS moving target shooting object with a tracking distance of S = 100 m, target board area of A = 1 m², and target linear velocity of v = 5 m/s is simulated. Results show that the optimal method’s distribution probability of the tracking error in a circle with a radius of 1 mrad is 66.7%, and that of the traditional method is 41.6%. Compared with the LOS shooting accuracy of the traditional method, the LOS shooting accuracy of the optimized method is improved by 37.6%.

A key challenge is using bionic mechanisms to enhance aerodynamic performance of hover-capable flapping wing micro air vehicle (FWMAV). This paper presented a new lift system with high lift and aerodynamic efficiency, which use a hummingbird as a bionic object. This new lift system is able to effectively utilize the high lift mechanism of hummingbirds, and this study innovatively utilizes elastic energy storage elements and installs them at the wing root to help improve aerodynamic performance. A flapping angle of 154° is achieved through the optimization of the flapping mechanism parameters. An optimized wing shape and parameters are obtained through experimental studies on the wings. Consequently, the max net lift generated is 17.6% of the flapping wing vehicle’s weight. Moreover, energy is stored and released periodically during the flapping cycle, by imitating the musculoskeletal system at the wing roots of hummingbirds, thereby improving the energy utilization rate of the FWMAV and reducing power consumption by 4.5% under the same lift. Moreover, strength verification and modal analyses are conducted on the flapping mechanism, and the weight of the flapping mechanism is reduced through the analysis and testing of different materials. The results show that the lift system can generate a stable lift of 31.98 g with a wingspan of 175 mm, while the lift system weighs only 10.5 g, providing aerodynamic conditions suitable for high maneuverability flight of FWMAVs.

The planned missions to explore the surfaces of the Moon and Mars require high exploration efficiency, thus imposing new demands on the mobility system of planetary rovers. In this paper, a design method for a high-speed planetary rover (HPR) is proposed, and the representative configurations are modeled and simulated. First, the influence of the planetary surface environment on the design of HPRs is analyzed, and the design factors for HPRs are determined by studying a single-wheel suspension. Second, a design methodology for HPRs is proposed. The adaptive suspension mechanisms of a four-wheeled rover are synthesized using the all-wheel-attachment condition and position and orientation characteristics theory, which are expressed in the form of a graph theory for the increase in elastic components and active joints. Finally, a dynamic model is built, and a simulation is carried out for the proposed rover. The validity of the proposed method and rover is verified, thus highlighting their potential application in future planetary exploration.

Planet pin position errors significantly affect the mechanical behavior of planetary transmissions at both the power-sharing level and the gear tooth meshing level, and its tolerance properties are one of the key design elements that determine the fatigue reliability of large aviation planetary systems. The dangerous stress response of planetary systems with error excitation is analyzed according to the hybrid finite element method, and the weakening mechanism of large-size carrier flexibility to this error excitation is also analyzed. In the simulation and analysis process, the Monte Carlo method was combined to take into account the randomness of planet pin position errors and the coupling mechanism among the error individuals, which provides effective load input information for the fatigue reliability evaluation model of planetary systems. In addition, a simulation test of gear teeth bending fatigue intensity was conducted using a power flow enclosed gear rotational tester, providing the corresponding intensity input information for the reliability model. Finally, under the framework of stress-intensity interference theory, the computational logic of total formula is extended to establish a fatigue reliability evaluation model of planetary systems that can simultaneously consider the failure correlation and load bearing time-sequence properties of potential failure units, and the mathematical mapping of planet pin positional tolerance to planetary systems fatigue reliability was developed based on this model. Accordingly, the upper limit of planet pin positional tolerance zone can be determined at the early design stage according to the specific reliability index requirements, thus maximizing the balance between reliability and economy.

The concept of remote center of motion (RCM) is pivotal in a myriad of robotic applications, encompassing areas such as medical robotics, orientation devices, and exoskeletal systems. The efficacy of RCM technology is a determining factor in the success of these robotic domains. This paper offers an exhaustive review of RCM technologies, elaborating on their various methodologies and practical implementations. It delves into the unique characteristics of RCM across different degrees of freedom (DOFs), aiming to distill their fundamental principles. In addition, this paper categorizes RCM approaches into two primary classifications: design based and control based. These are further organized according to their respective DOFs, providing a concise summary of their core methodologies. Building upon the understanding of RCM’s versatile capabilities, this paper then transitions to an in-depth exploration of its applications across diverse robotic fields. Concluding this review, we critically analyze the existing research challenges and issues that are inherently present in both RCM methodologies and their applications. This discussion is intended to serve as a guiding framework for future research endeavors and practical deployments in related areas.

The efficient dynamic modeling and vibration transfer analysis of a fluid-delivering branch pipeline (FDBP) are essential for analyzing vibration coupling effects and implementing vibration reduction optimization. Therefore, this study proposes a reduced-order dynamic modeling method suitable for FDBPs and then analyzes the vibration transfer characteristics. For the modeling method, the finite element method and absorbing transfer matrix method (ATMM) are integrated, considering the fluid–structure coupling effect and fluid disturbances. The dual-domain dynamic substructure method is developed to perform the reduced-order modeling of FDBP, and ATMM is adopted to reduce the matrix order when solving fluid disturbances. Furthermore, the modeling method is validated by experiments on an H-shaped branch pipeline. Finally, transient and steady-state vibration transfer analyses of FDBP are performed, and the effects of branch locations on natural characteristics and vibration transfer behavior are analyzed. Results show that transient vibration transfer represents the transfer and conversion of the kinematic, strain, and damping energies, while steady-state vibration transfer characteristics are related to the vibration mode. In addition, multiple-order mode exchanges are triggered when branch locations vary in frequency-shift regions, and the mode-exchange regions are also the transformation ones for vibration transfer patterns.

The deployable telescopic boom, whose mass and stiffness play crucial roles, is extensively used in the design of space-deployable structures. However, the most existing optimal design that neglects the influence of the locking mechanisms in boom joints cannot raise the whole stiffness while reducing the boom mass. To tackle this challenge, a novel optimization model, which utilizes the arrangement of the locking mechanisms to achieve synchronous improvement of the stiffness and mass, is proposed. The proposed optimization model incorporates a novel joint stiffness model developed based on an equivalent parallel mechanism that enables the consideration of multiple internal stiffness factors of the locking mechanisms and tubes, resulting in more accurate representations of the joint stiffness behavior. Comparative analysis shows that the proposed stiffness model achieves more than at least 11% improved accuracy compared with existing models. Furthermore, case verification shows that the proposed optimization model can improve stiffness while effectively reducing mass, and it is applied in boom optimization design.

The failure types in gear systems vary, with typical ones mainly including pitting, cracking, wear, and broken teeth. Different modeling and stiffness calculation methods have been developed for various gear failure types. A unified method for typical gear failure modeling and stiffness calculation is introduced in this study by considering the deviations in the time-varying meshing stiffness (TVMS) of faulty gears resulting from the use of different methods. Specifically, a gear tooth is discretized into a large number of microelements expressed with a matrix, and unified models of typical gear failures are built by adjusting the values of the matrix microelements. The values and positions of the microelements in the tooth failure model matrix have the same physical meaning as the parameter variables in the potential energy method (PEM), so the matrix-based failure model can be perfectly matched with PEM. Afterward, a unified method for TVMS is established. Modeling of healthy and faulty gears with pitting, wear, crack, and broken tooth is performed with the matrix equation, and the corresponding TVMS values are calculated by incorporating the matrix models with PEM. On the basis of the results, the mechanism of typical fault types that affect TVMS is analyzed, and the conclusions are verified through the finite element method. The developed unified method is a promising technique for studying the dynamic response characteristics of gear systems with different failure types because of its superiority in eliminating stiffness deviations.

The quality of the exposed avionics solder joints has a significant impact on the stable operation of the in-orbit spacecrafts. Nevertheless, the previously reported inspection methods for multi-scale solder joint defects generally suffer low accuracy and slow detection speed. Herein, a novel real-time detector VMMAO-YOLO is demonstrated based on variable multi-scale concurrency and multi-depth aggregation network (VMMANet) backbone and “one-stop” global information gather-distribute (OS-GD) module. Combined with infrared thermography technology, it can achieve fast and high-precision detection of both internal and external solder joint defects. Specifically, VMMANet is designed for efficient multi-scale feature extraction, which mainly comprises variable multi-scale feature concurrency (VMC) and multi-depth feature aggregation-alignment (MAA) modules. VMC can extract multi-scale features via multiple fix-sized and deformable convolutions, while MAA can aggregate and align multi-depth features on the same order for feature inference. This allows the low-level features with more spatial details to be transmitted in depth-wise, enabling the deeper network to selectively utilize the preceding inference information. The VMMANet replaces inefficient high-density deep convolution by increasing the width of intermediate feature levels, leading to a salient decline in parameters. The OS-GD is developed for efficacious feature extraction, aggregation and distribution, further enhancing the global information gather and deployment capability of the network. On a self-made solder joint image data set, the VMMAO-YOLO achieves a mean average precision mAP@0.5 of 91.6%, surpassing all the mainstream YOLO-series models. Moreover, the VMMAO-YOLO has a body size of merely 19.3 MB and a detection speed up to 119 frame per second, far superior to the prevalent YOLO-series detectors.

Manufacturing flexible magnetic-driven actuators with complex structures and magnetic arrangements to achieve diverse functionalities is becoming a popular trend. Among various manufacturing technologies, magnetic-assisted digital light processing (DLP) stands out because it enables precise manufacturing of macro-scale structures and micro-scale distributions with the assistance of an external magnetic field. Current research on manufacturing magnetic flexible actuators mostly employs single materials, which limits the magnetic driving performance to some extent. Based on these characterizations, we propose a multi-material magnetic field-assisted DLP technology to produce flexible actuators with an accuracy of 200 μm. The flexible actuators are printed using two materials with different mechanical and magnetic properties. Considering the interface connectivity of multi-material printing, the effect of interfaces on mechanical properties is also explored. Experimental results indicate good chemical affinity between the two materials we selected. The overlap or connection length of the interface moderately improves the tensile strength of multi-material structures. In addition, we investigate the influence of the volume fraction of the magnetic part on deformation. Simulation and experimental results indicate that increasing the volume ratio (20% to 50%) of the magnetic structure can enhance the responsiveness of the actuator (more than 50%). Finally, we successfully manufacture two multi-material flexible actuators with specific magnetic arrangements: a multi-legged crawling robot and a flexible gripper capable of crawling and grasping actions. These results confirm that this method will pave the way for further research on the precise fabrication of magnetic flexible actuators with diverse functionalities.

Simulation model optimization plays a crucial role in the accurate prediction of material removal function in bonnet polishing processes, but model complexity often poses challenges to the practical implementation and efficiency of these processes. This paper presents an innovative method for optimizing simulation model parameters, focusing on achieving consistent contact area and the accurate prediction of the material removal function while preventing increase in model complexity. First, controllable and uncontrollable factors in bonnet simulations are analyzed, and then a simplified contact model is developed and applied under constant force conditions. To characterize the bonnet’s contact performance, a contact area response curve is introduced, which can be obtained through a series of single spot contact experiments. Furthermore, a rubber hyperelastic parameter optimization model based on a neural network is proposed to achieve optimal matching of the contact area between simulation and experiment. The average deviation of the contact area under different conditions was reduced from 22.78% before optimization to 3.43% after optimization, preliminarily proving the effectiveness of the proposed simulation optimization model. Additionally, orthogonal experiments are further conducted to validate the proposed approach. The comparison between the experimental and predicted material removal functions reveals a high consistency, validating the accuracy and effectiveness of the proposed optimization method based on consistent contact response. This research provides valuable insights into enhancing the reliability and effectiveness of bonnet polishing simulations with a simple and practical approach while mitigating the complexity of the model.

Natural mechanical materials, such as bamboo and bone, often exhibit superior specific mechanical properties due to their hierarchical porous architectures. Using the principle of hierarchy as inspiration can facilitate the development of hierarchical mechanical metamaterials (HMMs) across multiple length scales via 3D printing. In this work, we propose self-similar HMMs that combine octet-truss (OCT) architecture as the first and second orders, with cubic architecture as the third or more orders. These HMMs were fabricated using stereolithography 3D printing, with the length sizes ranging from approximately 200 µm to the centimeter scale. The compressive stress–strain behaviors of HMMs exhibit a zigzag characteristic, and the toughness and energy absorption can be significantly enhanced by the hierarchical architecture. The compressive moduli are comparable to that of natural materials, and the strengths are superior to that of most polymer/metal foams, alumina hollow/carbon lattices, and other natural materials. Furthermore, the flexural stress–strain curves exhibit a nonlinear behavior, which can be attributed to the hierarchical architecture and local damage propagation. The relatively high mechanical properties can be attributed to the synergistic effect of the stretch-dominated OCT architecture and the bending-dominated cube architecture. Lastly, an ultralight HMM-integrated unmanned aerial vehicle (HMM-UAV) was successfully designed and printed. The HMM-UAV is ~85% lighter than its bulk counterpart, remarkably extending the flight duration time (~53%). This work not only provides an effective design strategy for HMMs but also further expands the application benchmark of HMMs.

The optimization of two-scale structures can adapt to the different needs of materials in various regions by reasonably arranging different microstructures at the macro scale, thereby considerably improving structural performance. Here, a multiple variable cutting (M-VCUT) level set-based data-driven model of microstructures is presented, and a method based on this model is proposed for the optimal design of two-scale structures. The geometry of the microstructure is described using the M-VCUT level set method, and the effective mechanical properties of microstructures are computed by the homogenization method. Then, a database of microstructures containing their geometric and mechanical parameters is constructed. The two sets of parameters are adopted as input and output datasets, and a mapping relationship between the two datasets is established to build the data-driven model of microstructures. During the optimization of two-scale structures, the data-driven model is used for macroscale finite element and sensitivity analyses. The efficiency of the analysis and optimization of two-scale structures is improved because the computational costs of invoking such a data-driven model are much smaller than those of homogenization.

Printed circuit boards (PCBs) are representative composite materials, and their high-quality drilling machining remains a persistent challenge in the industry. The finishing of the cutting edge of a microdrill is crucial to drill performance in machining fine-quality holes with a prolonged tool life. The miniature size involving submicron scale geometric dimensions, a complex flute shape, and low fracture toughness makes the cutting edge of microdrills susceptible to breakage and has been the primary limiting factor in edge preparation for microdrills. In this study, a newly developed cutting edge preparation method for microdrills was tested experimentally on electronic printed circuit boards. The proposed method, namely, shear thickening polishing, limited the cutting edge burrs and chipping on the cutting edge, and this in turn transformed the cutting edge’s radius from being sharp to smooth. Moreover, the edge–edge radius could be regulated by adjusting the processing time. PCB drilling experiments were conducted to investigate the influence of different cutting edge radii on wear, hole position accuracy, nail head value, and hole wall roughness. The proposed approach showed 20% enhancement in hole position accuracy, 33% reduction in the nail head value, and 19% reduction in hole wall roughness compared with the original microdrill. However, a threshold is needed; without it, excessive shear thickening polishing will result in a blunt edge, which may accelerate the wear of the microdrill. Wear was identified as the primary factor that reduced hole quality. The study indicates that in printed circuit board machining, microdrills should effectively eliminate grinding defects and maintain the sharpness of the cutting edge as much as possible to obtain excellent drilling quality. Overall, shear thickening polishing is a promising method for cutting edge preparation of microdrills. Further research and optimization can lead to additional improvements in microdrill performance and contribute to the continued advancement of printed circuit board manufacturing.

High-performance carbon fiber-reinforced polyether-ether-ketone (CF/PEEK) has been gradually applied in aerospace and automobile applications because of its high strength-to-weight ratio and impact resistance. The dry-machining requirement tends to cause the cutting temperature to surpass the glass transition temperature (T_g), leading to poor surface quality, which is the bottleneck for dry milling of CF/PEEK. Temperature suppression has become an important breakthrough in the feasibility of high-speed dry (HSD) milling of CF/PEEK. However, heat partitioning and jet heat transfer mechanisms pose strong challenges for temperature suppression analytical modeling. To address this gap, an innovative temperature suppression analytical model based on heat partitioning and jet heat transfer mechanisms is first developed for suppressing workpiece temperature via the first-time implementation of an air jet cooling process in the HSD milling of UD-CF/PEEK. Then, verification experiments of the HSD milling of UD-CF/PEEK with four fiber orientations are performed for dry and air jet cooling conditions. The chip morphologies are characterized to reveal the formation mechanism and heat-carrying capacity of the chip. The milling force model can obtain the force coefficients and the total cutting heat. The workpiece temperature increase model is validated to elucidate the machined surface temperature evolution and heat partition characteristics. On this basis, an analytical model is verified to predict the workpiece temperature of air jet cooling HSD milled with UD-CF/PEEK with a prediction accuracy greater than 90%. Compared with those under dry conditions, the machined surface temperatures for the four fiber orientations decreased by 30%–50% and were suppressed within the T_g range under air jet cooling conditions, resulting in better surface quality. This work describes a feasible process for the HSD milling of CF/PEEK.

The nickel-based high-temperature alloy GH4169 is the material of choice for manufacturing critical components in aeroengines, and electrostatic atomization minimum quantity lubrication (EMQL) milling represents a fundamental machining process for GH4169. However, the effects of electric field parameters, jet parameters, nozzle position, and milling parameters on milling performance remain unclear, which constrains the broad application of EMQL in aerospace manufacturing. This study evaluated the milling performance of EMQL on nickel-based alloys using soybean oil as the lubrication medium. Results revealed that compared with conventional pneumatic atomization MQL milling, EMQL reduced the milling force by 15.2%–15.9%, lowered the surface roughness by 30.9%–54.2%, decreased the average roughness spacing by 47.4%–58.3%, and decreased the coefficient of friction and the specific energy of cutting by 55% and 19.6%, respectively. Subsequent optimization experiments using orthogonal arrays demonstrated that air pressure most significantly affected the milling force and specific energy of cutting, with a contribution rate of 22%, whereas voltage had the greatest effect on workpiece surface roughness, contributing 36.71%. Considering the workpiece surface morphology and the potential impact of droplet drift on environmental and health safety, the optimal parameter combination identified were a flow rate of 80 mL/h, an air pressure of 0.1 MPa, a voltage of 30 kV, a nozzle incidence angle of 35°, an elevation angle of 30°, and a target distance of 40 mm. This research aimed to provide technical insights for improving the surface integrity of aerospace materials that are difficult to machine during cutting operations.

The plastic gear is widely used in agricultural equipment, electronic products, aircraft, and other fields because of its light weight, corrosion resistance, and self-lubrication ability. However, it has a limited range of working conditions due to the low modulus and thermal deformation of the material, especially in high-speed and heavy-duty situations. A compensation modification method (CMM) is proposed in this paper to restrain the heat production of the plastic gear tooth surface by considering the meshing deformation, and the corresponding modification formulas are derived. Improving the position of the maximum contact pressure (CP) and the relative sliding velocity (RSV) of the tooth surface resulted in a 30% lower steady-state temperature rise of the modified plastic gear tooth surface than that of the unmodified plastic gear. Meanwhile, the temperature rise of plastic gear with CMM is reduced by 19% compared with the traditional modification of removal material. Then, the influences of modification index and the segment number of modification on the meshing characteristics of plastic gear with CMM are discussed, such as maximum CP and steady-state temperature rise, RSV, transmission error, meshing angle, and contact ratio. A smaller segment number and modification index are beneficial to reduce the temperature rise of plastic gear with CMM. Finally, an experiment is carried out to verify the theoretical analysis model.