Large-scale lattice structures, characterized by their high porosity and multifunctional properties such as impact resistance, vibration damping, and noise reduction, hold great potential in key industrial sectors including national defense, marine engineering, and construction. However, limitations in current manufacturing technologies and methods remain a critical bottleneck for their broader application. Additive manufacturing (AM), by virtue of its layer-by-layer fabrication principle, overcomes the constraints of traditional techniques and enables the integrated 3D formation of spatially complex large-scale lattice structures. This study focuses on the latest developments in AM technologies and approaches tailored for large-scale lattice structures, and provides a comprehensive review from three perspectives: manufacturing processes, manufacturing equipment, and application prospects. In terms of manufacturing processes, we compare the state-of-the-art fabrication methods for large-scale multi-material metal lattice structures developed by domestic and international research teams, with a focus on truss-type and regular geometric lattice structures. Regarding manufacturing equipment, we summarize the structural configurations and control systems of current AM platforms, highlighting key differences and commonalities. Finally, we explore the future application potential of large-scale lattice structures in the context of AM. This review aims to systematically elucidate the recent progress and future directions of large-scale lattice structure fabrication via additive manufacturing, and to promote the industrial application of AM technologies for the efficient and high-quality production of lightweight structures.

Advanced materials are new materials with excellent properties, which are characterized by high strength, extreme temperature resistance, high biocompatibility, or special functions such as self-healing, shape memory and environmental response. Advanced materials have become the key foundation to support the development of high-end manufacturing. However, due to the high hardness, high melting point, high brittleness and other characteristics of advanced materials, the disadvantages of traditional processing methods are gradually revealed. The additive manufacturing technology based on material layer by layer cumulative forming is especially suitable for advanced materials to form complex three-dimensional structures, and has made significant progress in product development and industrial application. Therefore, a review of the research and development in additive manufacturing of advanced materials is provided. Firstly, the related concepts of advanced materials and additive manufacturing are elaborated, and the development prospect of their synergy is analyzed; Secondly, based on different forming principles, the development status and technical advantages of various advanced material additive manufacturing are introduced; Thirdly, the advanced material system is systematically reviewed, and its application status in additive manufacturing is summarized; Then the application status of the technology in different fields is shown, and the actual cases are listed; Finally, the existing problems of this technology are discussed, and the future development direction is prospected.

Projection-based 3D printing is an additive manufacturing technology grounded in the principle of photopolymerization. It employs a spatial light modulator to generate a dynamic mask and projects a bitmap image onto the surface of photosensitive materials to achieve curing and forming. Projection techniques can be categorized into two types: surface projection and volumetric projection. Among the various 3D printing technologies, surface projection offers the highest resolution/time to manufacturing ratio, while volumetric projection boasts printing speeds that far surpass those of traditional printing methods. Consequently, projection-enabled 3D printing is regarded as a highly promising technological approach. However, when applied to bioprinting—specifically with the use of cell-laden bioinks—its printability, resolution, and ink requirements undergo significant changes, presenting a range of challenges. This review systematically summarizes technical principles and primary challenges of projection-enabled 3D bioprinting, analyzes recent advancements in techniques and applications, and proposes practical optimization strategies tailored to the demands of biomedical applications. It aims to provide valuable insights and references for research and development in this field.

As an advanced biomanufacturing strategy based on additive manufacturing principles, bioprinting enables the precise deposition of cells and biomaterials, providing a powerful tool for constructing complex three-dimensional biological structures. This review systematically summarizes the fundamental principles and limitations of conventional bioprinting techniques, including droplet-based, extrusion-based, and light-assisted approaches, and highlights recent advances in high-throughput bioprinting aimed at improving printing speed, parallel capacity, and automation. Furthermore, we discuss the critical applications of high-throughput bioprinting in organoid construction, such as enabling standardized and scalable production, recapitulating complex multicellular architectures, and dynamically regulating microenvironments, thereby significantly enhancing the biomimicry and reproducibility of organoids. Finally, we outline the major challenges—such as multimodal detection, the lack of standardized protocols, and the development of bioinks—and provide a forward-looking perspective on future directions, offering important insights for the clinical translation and industrialization of organoid technologies.

Addressing the drag and heat reduction requirements of hypersonic vehicles under "long-endurance, high-Mach-number, high-overload, reusable" operating conditions, this review focuses on active mass injection structures. It systematically surveys research advances in two types of porous structures – discrete injection holes and micro-permeable porous configurations – and thoroughly analyzes their fluid-thermal coupling mechanisms and adaptability to extreme environments. The study critically evaluates advanced manufacturing processes, including metal/ceramic porous material systems and additively manufactured porous structures, while summarizing their engineering applications in critical components such as internal high-temperature engine parts and windward-facing vehicle surfaces. Furthermore, it synthesizes lightweight design strategies like self-pumping, zoned regulation, and active-passive hybridization, and identifies cutting-edge development pathways: matrix material intelligence, design-process intelligence, and verification-system intelligence. This work provides valuable insights for overcoming extreme thermal barriers and regulating frictional drag in hypersonic vehicles.

High-temperature ceramic microchannel heat exchangers, which combines excellent thermal resistance with structural compactness, represent a critical technology for next-generation high-efficiency thermal systems. However, the intrinsic high hardness and brittleness of ceramic materials pose significant challenges to the integrated fabrication of complex microchannel architectures. Conventional approaches typically adopt a two-dimensional stacked assembly of prefabricated cold/hot microchannel plates along the height direction. This leads to low spatial utilisation and mismatches between fluid flow and heat transfer fields, thereby limiting both structural compactness and heat transfer performance. Additive manufacturing (AM), with its unique capability for layer-by-layer integrated construction of intricate structures, breaks through the design constraints of the conventional approach. It enables a paradigm shift in microchannel design from a “manufacturing-driven” to a “performance-driven” approach, offering significant potential for maximizing spatial efficiency and enhancing field synergy between flow and heat transfer. This review systematically summarizes recent status in the additive manufacturing of high-temperature ceramic microchannel heat exchangers, with a focus on structural design strategies, fabrication processes, technical challenges, and representative application scenarios. Furthermore, development trends are discussed in the context of practical demands, aiming to provide technical guidance for the innovative design and engineering application of high-performance microchannel heat exchangers.

To address the issues of high internal stress and porosity defects in thin-walled high-strength Al-Zn-Mg alloy components fabricated by wire arc directed energy deposition (WA-DED), this study investigates the effect and mechanism of laser shock peening (LSP) as a post-treatment process. The influence of LSP on the mechanical properties, residual stress, microstructure evolution, and porosity of as-deposited Al-Zn-Mg alloys is systematically studied. Experimental results show that LSP introduces significant residual compressive stress inside the specimens, with an affected depth of approximately 1 mm. Compared to the as-deposited condition (yield stress: 266.6 MPa±0.7 MPa, ultimate tensile strength: 406.5 MPa±2.0 MPa), the yield strength and ultimate tensile strength of the Al-Zn-Mg alloy after LSP increased by 38.1% and 16.1%, reaching 368.1 MPa±5.1 MPa and 471.9 MPa±9.5 MPa, respectively. The remarkable improvement in mechanical properties is attributed to the generation of high-density dislocations within the bulk and the formation of numerous nanograins on the LSP-affected surface. The synergistic effects of dislocation strengthening and grain refinement are responsible for the enhanced mechanical performance of the LSP-treated samples.

Focusing on the problems of non-uniform temperature fields and thickness variations along the build direction in thin-walled laser directed energy deposition (LDED) samples, this research investigates the influence of interlayer idle time on the temperature field and quality of GH3536 samples fabricated via DED. The thermal field during the deposition process is monitored in real time using an off-axis infrared thermal imaging camera. Five temperature field features are extracted: length of melt pool, peak temperature of melt pool, average temperature of the central melt pool, heat affected layers, and average cooling rate of layers. Additionally, the surface morphology, microstructure, microhardness, and tensile strength of the samples are analyzed. The results indicate that extending the interlayer idle time can reduce the melt pool length and heat-affected zone, increase the average layer cooling rate, decrease thermal accumulation effect, improve dimensional accuracy, and reduce surface roughness. The side surface roughness Ra of the experimental samples decreased by 36.28%. Meanwhile, an increased interlayer idle time results in a finer and more uniform grain structure, which in turn enhances both the microhardness and tensile strength. The ultimate tensile strength of the experimental samples increased by 9.45%. The increases in melt pool length and heat-affected zone are negatively correlated with the appearance quality and mechanical properties, whereas an increase in the average layer cooling rate shows a positive correlation with both appearance quality and mechanical properties. This study provides a basis for the optimization of process parameters and performance control in the laser directed energy deposition of GH3536 alloy.

Laser coaxial wire additive manufacturing, with its advantages of high forming flexibility and uniform material melting, offers a novel and effective solution for the efficient forming of high-performance heterogeneous material integral structures based on 2xxx and 7xxx series aluminum alloys. To address the metallurgical porosity problem during laser coaxial wire additive manufacturing of aluminum alloys, this study combines experimental analysis with numerical simulation to investigate the differential pore distribution characteristics across different grain types and locations. It further elucidates the influence mechanisms of initial pore precipitation features and grain nucleation conditions on the competitive and cooperative evolution of microstructure and porosity. The results demonstrate that in the 205C aluminum alloy transition layer C1, the porosity at equiaxed grain boundaries (0.03%) is significantly higher than that within grains (0.01%). In the 7075 aluminum alloy transition layer C2, the porosity (1.01%) and average pore diameter (48.07 μm) in the columnar grain zone are 10.1 times and 1.68 times those in the equiaxed grain zone, respectively. During the final solidification stage, pores in the upper liquid channels of columnar grains merge with underlying pores, forming double-grain-boundary pores, while pores distant from primary dendrite tips become encapsulated by adjacent columnar grains, resulting in triple-grain-boundary interactive pores. Pores between multiple equiaxed grains exhibit near-spherical morphology due to uniform grain boundary constraints, whereas those between columnar grains adopt an elongated, intergranular distribution due to crystallographic orientation constraints. As the columnar grain growth mode transitions from convergent to parallel and finally divergent, the length, width, and roundness of intergranular pores progressively increase.

There are significant challenges in balancing the strength and plasticity in traditional alloy triply periodic minimal surface (TPMS) lattice structures fabricated by laser powder bed fusion (LPBF). In this work, a systematic study on the LPBF process of AlCoCrFeNi_2.1 eutectic high entropy alloy and its TPMS lattice structures' mechanical properties has been conducted. The optimal parameter combination resulted in the elastic modulus of 255 GPa, the yield stress of 1348 MPa, the compressive strength of 2520 MPa, and the compressive strain exceeding 25%. Microstructure characterization revealed a dual-phase nanolamellar structure of FCC (130-250 nm) and BCC (20-30 nm) with element segregation forming heterogeneous interfaces for synergistic strengthening. Diamond, Gyroid, Primitive TPMS structures and BCC truss structures are fabricated to reveal the influence of lattice configuration, relative density, and unit cell size on quasi-static compression properties. The elastic modulus, yield stress, and energy absorption are positively correlated with the relative density. The maximum energy absorption of Diamond, Gyroid, and Primitive structures reached 2369 J, 2062 J, and 1096 J, respectively. The elastic modulus and yield stress increased linearly with unit cell size, and the plateau stress and energy absorption are enhanced simultaneously. At a relative density of 40%, the specific elastic modulus of Gyroid and Primitive structures reached 47.8 GPa/kg and 46.9 GPa/kg respectively. The Diamond structure had the best comprehensive properties with a specific elastic modulus of 72.6 GPa/kg and a specific energy absorption of 38.7 J/g. Compared with TPMS lattices of 316L stainless steel and Ti-6Al-4V titanium alloy, the AlCoCrFeNi_2.1 lattice structure has superior strength-plasticity matching and great application prospects for high load-bearing and energy absorption under extreme loading conditions.

To address the high-precision and mass-transfer of high-strength aluminum alloy capillary wick structures, this study investigates the printability and capillary performance of micro-featured structures fabricated via conventional laser powder bed fusion (c-LPBF) versus micro laser powder bed fusion (μ-LPBF). The μ-LPBF process achieved a structural resolution limit of ~86 μm, with defect equivalent diameter ranging from 25-40 μm, average defect volume of 9.99×10^-6 mm³, and sphericity of 0.76. These results significantly surpass c-LPBF performance (defect equivalent diameters: 50-100 μm; sphericity: 0.48), demonstrating superior dimensional accuracy and defect suppression capability for sub-200 μm features. Numerical simulation revealed the evolution mechanisms of particle splashing and denudation behavior: Strong metallic vapor plumes of c-LPBF induced powder splashing velocities up to 10 m/s and denudation zone widths of 821-932 μm. In contrast, μ-LPBF’s attenuated vapor disturbance reduced splashing velocities below 5 m/s and narrowed denudation zones to 159-239 μm, markedly enhancing process stability. The μ-LPBF-fabricated structures exhibited enhanced capillary metrics, including a higher capillary pressure-permeability product (ΔP_capK=16.08×10^-8 N) and capillary factor (K/R_eff=1.16 μm), indicating balanced comprehensive mass transfer performance. It provides a theoretical foundation for optimized design and integrated manufacturing of thermal management structures.

Ni-Ti shape memory alloys (SMAs) are fabricated by selective laser melting (SLM) technology. The effects of laser power, scanning velocity, and volumetric energy density on the forming quality, microstructure, martensitic transformation behavior, mechanical properties, and superelasticity of SLM-fabricated Ni-Ti SMAs are systematically investigated. The results indicate that to achieve a relative density above 99%, a high laser power should be combined with a high scanning velocity, while a low laser power should be paired with a low scanning velocity. Additionally, a minimum volumetric energy density of 45 J/mm³ is required. Regardless of the processing parameters used, columnar grains aligned parallel to the build direction formed in all SLM-fabricated Ni-Ti SMAs when an x/y alternating scanning strategy is applied. And both the length and width of columnar grains increased as the volumetric energy density increased, which corresponds to higher laser power and lower scanning velocity. Moreover, with increasing the volumetric energy density, the characteristic temperatures of martensitic transformation of SLM-fabricated Ni-Ti SMAs increased, and the critical stress for stress-induced martensitic transformation consequently decreased. Samples fabricated with a low energy density of volumetric 57.1 J/mm³ exhibited a nominal yield strength of 1 208 MPa and a superelastic recovery strain of 6.9% under room-temperature compression. As the volumetric energy density further increased, the nominal yield strength first increased and then decreased, while the superelastic recovery strain consistently declined.

Laser powder bed fusion (LPBF) enables the high-precision fabrication of complex metal components; quality fluctuations during the process and the lack of reliable in-situ defect monitoring is one of the key research directions. Focusing on the LPBF fabrication of Ti-6Al-4V alloys, this study develops an in-situ vision-based method for online monitoring and classification of layer-wise build quality, which enables the prediction of forming quality. First, single-track experiments are conducted to investigate melt-pool behavior and optical morphology under different combinations of laser power and scanning velocity. Based on the resulting energy-density variations, the layer morphology is categorized into low-energy, optimal-energy, and high-energy regimes, establishing ground-truth criteria for subsequent classification. Nine groups of multi-parameter LPBF experiments are then performed to acquire layer-wise images and characterize the corresponding build quality, enabling the construction of a quantitative relationship among processing parameters, surface morphology, and final part quality. A multimodal augmented dataset (including geometric transformations, noise injection, and illumination adjustment) is built using the collected images. The YOLOv5s network is employed to learn the mapping between optical features of the layer morphology and the energy-input state, achieving real-time online recognition and prediction of quality categories. Experimental results show that after 100 training epochs, the model achieves over 97% classification accuracy (mAP > 0.90) for distinguishing high, medium, and low energy-density morphologies. This work elucidates the correspondence between LPBF processing parameters, optical layer morphology, and resultant build quality, providing an engineering-feasible pathway for online monitoring and real-time control of LPBF processes.

Heat treatment phase transition is a key factor affecting the magnetic and mechanical properties of high-entropy alloys (HEAs). AlCoCrCuFeNi HEAs were prepared by a laser powder bed fusion (LPBF) method and the effects of annealing at different temperatures (600-1 100 ℃) on the microstructures, magnetic and micromechanical properties of AlCoCrCuFeNi HEAs were studied. The results show that the printed alloy is randomly oriented columnar crystals with ordered BCC matrix phase and a small amount of FCC precipitated phase, which epitaxially growth along the molten pool. With the increase of annealing temperature, the alloy underwent recovery and recrystallization process accompanied by the FCC phase gradually separated from the BCC phase matrix and occupied the dominant position. Both the printed and annealed alloys exhibit excellent mechanical properties, while the nanohardness and vickers hardness increase first and then decrease with the increase of annealing temperature. When the annealing temperature is 600 ℃, the nanohardness and vickers hardness of the sample are the highest, which are 9.57 GPa and 692.6 HV, respectively.The samples showed typical semi-hard magnetic properties with the saturation magnetization (M_s) and coercivity (H_c) first increased and then decreased with the increase of annealing temperature, but the magnetic crystal anisotropy constant (k₁) showed a trend of increasing first, then decreasing and increasing again. When the annealing temperature is 600 ℃, both M_s and H_c have the maximum values, which are 60.12 A·m²/kg and 7.16 kA/m respectively. This work can provide certain research ideas for the subsequent adjustment of the microstructure and comprehensive magnetic properties of HEAs through annealing processes.

4D printing offers electromagnetic metamaterials enhanced manufacturing capabilities for multi-material systems and multi-dimensional structures. Leveraging the stimulus-responsive behavior of materials, it unlocks significant advantages in dynamic tunability and multifunctional integration. The screw structure from mechanical engineering as a bio-inspired prototype is taked. Using CB/PLA composite filament as the EM-loss matrix and CB/TPU-PLA composite filament as the 4D smart material substrate, a functionally graded element-sequenced, 4D printed screw-like electromagnetic metamaterial is designed and fabricated via fused deposition modeling (FDM). The influence of multi-material combinations and structural geometric parameters on the microwave absorption performance of the metamaterial is investigated, and its broadband absorption mechanisms are elucidated. Both simulation and experimental results demonstrate that the metamaterial exhibits an exceptionally wide effective absorption bandwidth (EAB) of 36.95 GHz and a minimum reflection loss of -33.26 dB. It also possesses excellent wide-angle absorption characteristics (EAB ≥ 34.66 GHz) across an incidence angle range of θ = 0-60°. Furthermore, the metamaterial exhibits outstanding shape memory properties, achieving a shape recovery ratio exceeding 90% within 30 seconds. Combining a broad effective absorption bandwidth with favorable shape memory characteristics, the screw-like electromagnetic metamaterial provides a novel solution for applications such as intelligent electromagnetic protection and adaptive stealth. This work contributes to the advancement of electromagnetic metamaterials towards multifunctional integration.

With the rapid application of additive manufacturing technology in the field of ceramic material fabrication, the development of light cured ceramic slurries with high solid content and low viscosity has become a key content in the complex structure additive manufacturing of various ceramic materials. This article focuses on Si₃N₄ based ceramic composite materials and studies high solid content/low viscosity multiphase ceramic slurries that meet the requirements of photopolymerization additive manufacturing, providing theoretical and technical support for the additive manufacturing of high-performance ceramic parts. The design concept of the slurry system is outlined, including the resin matrix formulation, particle grading strategy, and additive optimization. A composite resin matrix is designed and prepared by mixing the monomer resins HDDA, TMPTA, ACMO, and EA in a mass ratio of 1:1:1:1. A ceramic particle size grading strategy is adopted (particle mass ratio of 1 μm : 0.5 μm : 50 nm = 0.17 : 0.67 : 0.16). The contents of the silane coupling agent KH560 (5% of the total ceramic particle mass), dispersant BYK110 (4% of the total ceramic particle mass), and diluent NMP (20% of the resin mass) are optimized. This ultimately achieved comprehensive improvement in the slurry's rheological properties and printability. At a solid loading of 55.56%, the slurry exhibited a viscosity of 0.79 Pa·s, thixotropy of 553.1 Pa/s, and yield stress of 28.9 Pa. The addition of KH560, BYK110, and NMP reduced the slurry viscosity to 3.87 Pa·s even when the solid loading reached 74 wt%. This study provides theoretical and technical support for the preparation of applicable slurries used in additive manufacturing of high-performance ceramic components.

Polyether ether ketone and its composites exhibit excellent adaptability to space environments, demonstrating significant potential for in-space 3D printing applications. The key to conducting in-space 3D printing lies in addressing the challenges posed by space extreme environment conditions, particularly the high-vacuum environment. This study investigated vacuum 3D printing of polyether ether ketone (PEEK) and its short carbon fiber-reinforced composite (SCF/PEEK), revealing the influence of vacuum-induced heat and mass transfer mechanisms including heat dissipation suppression and micro pore thermal expansion on mechanical properties. Dominated by radiative heat dissipation in vacuum, the reduced melt solidification rate enhanced molecular orientation motion and interlayer diffusion, increasing the crystallinity of vacuum-printed PEEK and SCF/PEEK from 14.9% and 25.2% for ambient pressure to 27.8% and 30.5%, respectively. Consequently, the Z-direction tensile strength improved by 212.5% and 295.9% compared to ambient conditions. However, the SCF/PEEK filament contained many inherent micro pores that expanded under the drive of vacuum pressure difference, increasing porosity and reducing longitudinal and transverse tensile performance. In contrast, PEEK filament, with fewer initial voids, benefitted from enhanced melt flow under vacuum’s slower heat dissipation, reducing porosity and improving both longitudinal and transverse tensile properties. This research provided theoretical guidance for on-orbit validation of in-space 3D printing, contributing significantly to the in-situ manufacturing of space structures.

Conformal electronics on curved surfaces offer unique advantages in achieving multifunctionality and high integration of electronic devices by directly adhering to target substrates, demonstrating significant potential value in fields such as wearable electronics, biomedical devices, and aerospace engineering. To systematically address the challenges of poor printing flexibility, low printing accuracy, and post-processing limitations in the fabrication of conformal microscale circuits on complex curved surfaces, this study proposes an integrated manufacturing method combining multi-degree-of-freedom aerosol jet printing and in-situ laser sintering based on a six-axis robotic arm. The robotic arm is equipped with an aerosol jet printing module and an infrared laser sintering unit, and a multi-threaded control architecture is developed to enable flexible path planning and synchronous control of printing parameters. To achieve uniform sintering of aerosol jet printed conformal microscale circuits on curved surfaces, a multi-degree-of-freedom conformal in-situ laser sintering methodology is proposed, yielding optimized laser sintering process parameters. This enables high-precision printing and high-conductivity sintering of conformal circuits on surfaces with curvature variations of 25~100 m^-1 and a large area of 400 mm×190 mm. The circuit line width is less than 50 μm, and the electrical resistivity is as low as 6.53×10^-8 Ω·m. Furthermore, the proposed integrated process is validated to be compatible with polymer substrates with heat deflection temperatures ranging from 60 ℃ to 360 ℃. The study has successfully achieved direct manufacturing of conformal conductive circuits on a spatial double-helix surface across a wide inclination angle range of -20° to +30°, and also realized 8-channel conformal thermal sensor circuits on a curved blade model surface. This study overcomes key technical bottlenecks in the flexibility and functionality of conformal microcircuit manufacturing on complex curved surfaces, providing an efficient and reliable solution for the rapid fabrication of conformal electronic systems.

High-precision curved conformal films/coatings are an important part of 3D curved conformal electronics, structural health monitoring, intelligent skins, conformal sensors and other products, which have extensive applications in aerospace, national defense and military industries, and intelligent electronics field. However, the efficient, low-cost, normal temperature/pressure manufacturing of high-precision conformal films is a major problem in current research. A new method for manufacturing high-precision conformal films is proposed by three-axis linked pneumatic/electricity/heat synergistically driven jetting micro-3D printing: through the pneumatic pressure to drive material into the nozzle, piezoelectric impact needle synergistic nozzle heating to achieve stable jetting of high viscosity material microdroplets, substrate heating regulates the deposition and curing behavior of microdroplets on curved surfaces, and ultimately realizes the preparation of high-precision conformal films using high-viscosity materials; Taking the industrially widespread polyimide (PI) material as a case study, we investigated the rheological behavior and viscosity characteristics of the material suitable for printing via the proposed method; Through experiments, the influences of key process parameters on stability of conformal film preparation, thickness uniformity, and surface quality are revealed;Combined with the optimized process parameters, high-precision PI conformal films with an average thickness of 22 μm and thickness deviation <2 μm were successfully fabricated on semi-cylindrical glass substrates, This method is suitable for materials with different viscosities (such as PI, zirconia ceramics, PDMS, etc.), and can fabricate high-precision conformal films on various substrate materials (glass, resin, metal, etc.) and on multiple complex curved substrate surfaces (e.g., spherical surfaces, stepped surfaces, wavy surfaces, etc.), exhibiting good universality. The prepared curved-film heater achieves a maximum temperature of 144.3 ℃ at 14 V, with a temperature deviation of <2% in the heating area, showing a highly uniform heating effect. This proposed method provides a new solution with industrialized application prospects for efficient and low-cost fabrication of high-precision conformal films/coatings under normal temperature and pressure conditions.

Flexible robots with multiple degrees of freedom can be driven to adapt to various shapes and complex environments with lower risks for their inherent flexibility. Robotics development has become one of the hot spots since its broad applications in many fields, such as biomedicine, pipeline maintenance, and rescue, are prospected. However, the low stiffness brought by flexibility makes it difficult to support and manipulate objects under high load conditions. Inspired by natural creatures, researchers introduced adjustable stiffness elements and materials into flexible robots to switch between rigid and flexible states alternately, which provides an effective method to solve the potential contradiction between compliance and high stiffness. This paper presents a systematic review of the latest advances in research on stiffness modulation for flexible robots, including the methods used for stiffness modulation and program configurations. The stiffness modulation principles are classified as intelligent material-based stiffness modulation, structure-based stiffness modulation, and interference-based stiffness modulation. At the same time, the combination of various stiffness modulation methods, especially the variable stiffness strategy combining interference structure and origami technology, is introduced. With the development of material science and mechanical structure technology, adjustable stiffness flexible robots with high load-carrying capacity, high flexibility, and lightweight will become an important research direction in future robotics.

The free gait planning of hexapod robots for uneven terrain greatly influences the motion and operation performance exploring complex scenarios. This research mainly focuses on the local terrain representation, dynamic and static stability evaluation, and free gait planning. Referencing the smooth motion mechanism of hexapods, inspiring by the discrete interaction between the foot and terrain, a description for the foot locations and an iterative integration strategy of terrain feature points are proposed, and then a local terrain representation method depending on footholds is established. By exploring the influences of support-footed polygons and single-footed workspace on robot stability, spatially static and temporally dynamic stability margins are proposed, which further establishes the stability evaluation method. Following the gait generation paradigm with feature plane switching, series of adjustment rules involving foothold locations and action sequences are formulated with referencing to feature planes, stability margins, and virtual queues, which is dedicated to establishing free gait planning method for uneven terrain. The experimental results show that a hexapod robot adopting proposed free gait planning method can generate suitable gaits to stably move on uneven test terrain.

The stable gripping of the end-effector is one of the key technologies for the precise and reliable operation of the picking robot. However, in the agricultural unstructured growth environment, the fruit varies in size and shape, which is a major challenge for the stable gripping of the end-effector. Aiming at the stable gripping problem of spherical fruit, a three-finger two-knuckle end-effector driven by linkage is optimized. Firstly, the basic structure and parameters of the end-effector are designed, and then the forward kinematics model of the two-knuckle finger mechanism is established. Based on the stability of the fruit envelope, the multi-objective optimization objective function and constraint conditions for stable clamping are established, and the NSGA-II algorithm is used to optimize the parameters. The correctness of the motion law of the designed end-effector is verified by ADAMS simulation platform. Finally, the stable gripping test of tomato fruits with different sizes and postures is carried out. The experimental results show that when tomato fruits with different sizes and shapes are clamped, the average centroid offset of the fruit relative to the end-effector is 4.30 mm. The average position change of each knucklegrip contact point was 6.23 mm. The designed end-effector has good adaptability to different sizes and postures of tomatoes, and can effectively improve the gripping stability of the end-effector, which has important theoretical and technical support for the development and application of the picking robot.

To address the issues of external force estimation for industrial robots—namely, its dependence on accurate dynamic models, poor disturbance rejection, low estimation accuracy, and insufficient interpretability—an external force estimation method for force sensorless industrial robots with high anti-interference is proposed. Firstly, a dynamic model of a 5-degree-of-freedom industrial robot with a 3T2R configuration is established, considering the effects of joint friction torque and external forces. The nonlinear characteristics of joint friction are modeled using the Stribeck friction–velocity model. Secondly, an adaptive super-twisting sliding mode generalized momentum observer, with an adaptively tuned rate gain parameter, is then employed to estimate joint external torques. This approach improved estimation accuracy, reduced reliance on precise dynamic models, and enhanced interpretability. Thirdly, a mapping relationship between joint external torques and external forces is constructed using the Jacobian matrix, enabling external force estimation. Fourthly, comparative experiments are conducted against the adaptive super-twisting sliding mode observer, the super-twisting sliding mode observer, and the first-order generalized momentum observer. Taking Joint 1 as an example, the proposed method reduced the mean absolute error of joint external torque estimation by 12.9%, 39.9%, and 57.9%, respectively. Based on the established mapping, external forces are further estimated, demonstrating higher accuracy and validating the effectiveness of the proposed method. Finally, under the application of the same random disturbance, the proposed method is compared with the first-order generalized momentum observer. The root mean square error of the estimated joint external torque increased by only 1.5% for the proposed method, whereas it increased by 43.3% for the first-order method, verifying the superior disturbance rejection capability of the proposed method.

The global dynamics of the passive walking robot are primarily focused on the exploration of the shape change of the basin of attraction, while the dynamic evolution of the state points inside the basin is relatively scant. To this end, the round-footed passive walking robot is taken as the research object, and the cell mapping and point mapping algorithms are adopted to systematically analyze the number of convergence steps for each point in the basin of attraction. The complex topological structure within the basin is revealed, and the state regions that trigger the robot to fall forward or backward are clearly distinguished. In addition, dynamics simulations of the stable walking and falling behaviors of the robot prototype are conducted in ADAMS to verify the accuracy of the numerical calculations. Subsequently, nonlinear numerical tools such as bifurcation diagrams, Floquet multiplier diagrams and Lyapunov exponential diagrams are utilized to deeply analyze the evolution of the topology inside the basin of the robot under different parameter conditions. The results show that the robot's basin of attraction is surrounded by the state region that triggers the forward fall, and the passive walking gait is continuously converged to a stable state in a surrounding manner. The robot with an excessively high support leg angle and an overly low angular velocity of the support leg is highly susceptible to backward falls, while forward falls are more likely under the opposite conditions. The internal topology of the basin of attraction becomes more complicated with the increase of the angle of the ramp, and the average number of convergence steps of the state points inside the basin is related to the maximum modulus of the point. The above analysis results help to understand the internal evolution mechanism of the robot’s basin of attraction, which can provide a reference for the selection of the initial value of the robot’s walking and dynamic control.

While significant progress has been made in autonomous navigation of mobile robots in 2D structured terrains, many challenges remain in navigating 3D unstructured environments, such as accurately reflecting terrain features and planning paths that can traverse obstacles. Therefore, a navigation framework for wheeled robots in unstructured terrains is proposed. Firstly, local plane fitting is applied to the surface points of the 3D grid map to capture terrain detail features, enabling evaluation and passability analysis of the surrounding terrain to provide quantitative support for navigation decisions. Secondly, an informed RRT* sampling planning method is employed to design a cost function that considers terrain passability, proposing a 2D sampling and 3D optimization global planning method, IRRT*-TFP, which effectively utilizes terrain information to accurately plan while reducing computational complexity. Finally, an improved dynamic window approach (DWA) is used for local planning, DWA-KPS, which solves the problem of deviating from the global plan and entering dangerous terrains by densifying the global trajectory and adding a trajectory similarity evaluation function, thereby improving navigation quality and safety. Comparative experiments between IRRT-TFP and the A* algorithm, as well as DWA-KPS and the original DWA algorithm, verify the effectiveness of the proposed algorithms for autonomous navigation in rugged and complex unstructured environments.

Gear transmission system is an important component of aero-engines, operating under long-term thermal-mechanical load conditions. Its fatigue reliability has become a key limit on the service performance of machines. However, current reliability assessment methods of gear transmission systems do not consider the combined effect of thermal-mechanical loads, making them difficult to assess fatigue reliability. A fatigue reliability analysis method based on the "fatigue life-operation history" interference theory for aircraft gear transmission systems is proposed, considering fatigue strength degradation caused by temperature rise and the load spectrum effect. It is found that the fatigue damage of key components of the transmission system under the thermal-mechanical loading condition is significantly different compared with that under merely mechanical loading. The fatigue reliability of the transmission system under thermal-mechanical loading is improved by 21.5% through the selection of gear materials with high strength and heat resistance.

This paper introduces the structure of a hydraulic drifter. Integrated with a nonlinear rock model, the process of drilling the rock is established as a four-degree-of-freedom mechanical model and a mathematical model. Both stick and non-stick modes are studied, explaining the differences between these two types of motion. Taking the angular frequency, amplitude and vertical offset of the hydraulic force as control parameters, the single-parameter continuation analysis is carried out, and the period-doubling bifurcation, saddle-node bifurcation and torus bifurcation are found. A comparison is made between the piston displacement and velocity data obtained from the model and experimental results. The results indicate that to make the drifter work on the period-1 trajectory, the range of angular frequency should be 2.09 < ω < 5.327. The range of amplitude should be 0.012 < a < 0.746, 0.005 < a < 1. The range of vertical offset should be 0.093 < b < 0.25. The hydraulic forces of the experiment and the model have the same performance trend, and the piston displacement and velocity of the model are roughly within the range of "experimental mean ±standard deviation", which indicates that the model well simulates the experimental results.

With the large-scale and lightweight trend of aerospace equipment, low-frequency vibrations induced by complex excitations have become a critical factor affecting accuracy, stability, and reliability. Inspired by the biomechanical principle of seahorse exoskeleton has the ability of protecting its vertebrae from injury under strong external impacts, a hexagonal vibration isolation structure mimicking the seahorse exoskeleton is proposed. The dynamic theoretical model is established, and the effects of structural parameters on the static stiffness and loading capacity of the seahorse exoskeleton inspired hexagonal structure are investigated. The dynamic equations are established based on the Lagrange formulation, the approximate transmissibility is obtained with the harmonic balance method. The effects of the structural parameters on the low-frequency vibration isolation performance are evaluated. An experimental system was built to validate the dynamic model of the seahorse exoskeleton hexagonal vibration isolation structure and its low-frequency vibration isolation performance. The results show that the seahorse exoskeleton hexagonal vibration isolation structure has a large quasi-zero stiffness working range, and the peak frequency of 1.9 Hz can be obtained by adjusting the structural parameters, and it has a better vibration isolation effect in the low-frequency band. This research offers theoretical and experimental guidance for the design and development of seahorse-inspired vibration isolation structures.

In practical applications, the lack of fault samples and the imbalance of fault sample categories often limit the effectiveness of diagnosis. In order to solve the problem of unbalanced bearing fault samples, a digital twin system based on dynamic fault injection is designed, which can not only reflect the normal operation state, but also generate samples of different faults. The system is divided into an agent model part and a parameter identification part: the agent model part adopts a two-freedom bearing dynamics model of the impact response at the fault point, and uses the fourth-order variable-step-length Lunger-Kutta method to perform simulation calculations and generate the simulated vibration data; the parameter identification part combines the original algorithm with the Chebyshev chaotic mapping, the golden sinusoidal strategy, and the adaptive weighting factor method and improves its fitness function to propose an improved dung beetle optimisation algorithm, which can identify the dynamic parameters through the measured vibration data, construct a digital twin system, and realise dynamic fault injection. It is proved through experiments that the fault data generated by this system has a higher accuracy rate compared with the data generated using inverse physical information neural network, CycleGAN and GAN. In addition, after expanding the outer ring fault data by this system, the overall diagnostic accuracy of the diagnostic model is increased by 8.9%, and the diagnostic accuracy of the outer ring fault is increased by 26.7% to 99.8% and 99.5%, respectively, which provides a certain reference for the problem of unbalanced fault samples in the fault diagnosis of rolling bearings.

As the requirements for battery custom design, intelligent manufacturing, and green recycling continue to increase in the manufacturing industry, how to adapt to customer personalized needs, multi-disciplinary collaborative design, intelligent and flexible production, and green recycling requirements in the production process has become a key issue to be solved in the transformation and upgrading of lead-acid battery factories. Therefore, the role of data and models in the transformation and upgrading of factories is analyzed, and a future factory adaptability data model system for lead-acid batteries is proposed. Four key technologies involved in the system are expounded, including customized design to meet the individual needs of customers, virtual and real interaction to adapt to multi-disciplinary collaborative design, control and traceability to adapt to the whole process of intelligent production, and process upgrade to adapt to green recycling. Taking the whole process production information traceability of lead-acid batteries as an example, the application of computer vision and other technologies in production control and traceability is analyzed to prove the effectiveness of the proposed method. The future factory development of new energy enterprises represented by lead-acid batteries is prospected, providing a reference for the transformation and upgrading of the domestic new energy industry.

Digital twin is the key technology for enabling intelligent operations at longwall mining face, with the shearer serving as the central equipment. The cutting of a longwall shearer drum is the primary part during the dynamic coupling process between the longwall shearer and coal/rock environment. Building an accurate cutting load of longwall shearer drum is important for a high-filed digital twins model of longwall shearer. A kinematic trajectory equation of cutting pick is built which includes the traction motion of longwall shearer, adjusting of range arm, and rotation of drum. With this equation, the necessary parameters, including cutting depth and angle of coal/rock cut range, for calculating cutting load of one cutting pick are obtained. The cutting load model of longwall shearer drum is built based on cutting load of one cutting pick. It realized that real-time cutting load is calculated under different conditions including rotating speed of drum, traction speed of longwall shearer, relative location between drum and coal/rock interface. The digital twin system of longwall shearer is built with the proposed real-time cutting load model of longwall shearer drum. The cutting load is simulated and analyzed under different conditions. The results shows that the cutting torque and cutting force F_x are greatly affected by working condition parameters, while the cutting force F_y is little affected by working condition parameters. Based on the historical operating data of 18201l longwall face, the shearer drum cutting load model is verified and tested. It is found that the average error between the simulation value and the measured value of cutting torque under constant and variable traction conditions is 6.85 kN·m and 6.36 kN·m, respectively. Both the simulation value and measured value of cutting torque include 7 IMF components and one residual term. Moreover, the frequency range and amplitude changes of each IMF are very similar, indicating that the established cutting load model can simulate the cutting load of shearer more accurately in the frequency domain.

To address the challenges of insufficient knowledge mining and low efficiency of knowledge reuse in the innovative design of complex industrial products, a complex product patent knowledge mining and recommendation method based on few-shot feature extraction and cross-citation network is proposed. Firstly, patent knowledge model is constructed by extracting three types of featured entities including domain(D), function(F), and technology(T), which is represented as a three-aspect model <D, F, T>. Meanwhile, the annotation rule of few-shot patent dataset is proposed for manual feature annotation. Secondly, a fine-tuned BERT model is constructed based on a few-shot annotated patent dataset to achieve automatic patent feature extraction. A graph neural network is employed to learn the representation of the patent co-citation network. Thirdly, the fine-tuned BERT model is subsequently used to extract feature entities in the input design problem or task description, which are vectorized and their cosine similarities computed to generate a recommendation list. Finally, a prototype based on Django framework is also developed, which realizes the two functions of feature extraction and knowledge push, and illustrates the use scenarios of this method based on a case of automobile windshield wiper strip design.