Template-free assembly of three-dimensional (3D) graphene foams from two-dimensional (2D) sheets offers a scalable bottom-up strategy, but the resulting structures often suffer from poor stiffness and strength due to limited inter-sheet covalent bonding, while exhibiting enhanced tensile ductility compared to template-based chemical vapor deposition (CVD) foams with continuous graphene layers. Here, we present an innovative computational approach to construct closed-cell and open-cell (gyroid) graphene foams assembled from either random graphene sheets or continuous layers, simulating the synthesis process through advanced algorithms. The stacking configuration of graphene bubbles critically governs mechanical performance: face-centered cubic (FCC) and body-centered cubic (BCC) closed-cell foams exhibit higher strength, stiffness, and energy absorption than randomly stacked foams due to reduced pore size and lower gap density. Scaling laws fitted for both closedcell and gyroid foams reveal the relationship between mechanical properties and relative density, and these predictions are validated against experimental data. In gyroid foams, assembled sheets display lower stiffness and strength but markedly enhanced tensile ductility compared with continuous layers, as inter-sheet gaps dissipate energy during crack propagation. The self-stiffening effect arising from sheet folding and wrinkling under tension is quantitatively analyzed using theoretical formulas, showing excellent agreement with predictions. Furthermore, the ductile tensile behavior of assembled gyroid graphene is elucidated through detailed quantitative analysis of the underlying microstructural mechanisms. These findings establish clear structureproperty relationships and provide design principles for engineering robust, energy-dissipative 3D graphene architectures.

Additive manufacturing (AM) offers new opportunities for developing biodegradable bone substitutes with personalized structures and tunable properties. Zn-Mg alloys have shown great potential in bone repair due to their suitable degradation rate, good biocompatibility, and favorable mechanical properties. However, most existing studies focus on uniform structures, and systematic research on the mechanical compatibility and permeability of Zn-3Mg alloys with gradient triply periodic minimal surface (TPMS) structures is still lacking. In this study, Zn-3Mg scaffolds with different gradient designs (gyroid, primitive, and diamond) were fabricated using selective laser melting (SLM). Microstructural analysis revealed that rapid solidification significantly refined the grains and promoted a uniform distribution of alpha-Zn/Mg2Zn11 eutectic and MgZn2 intermetallic phases, while stronger lattice distortion and higher brittleness were observed along the vertical direction. The gradient design notably optimized pore distribution and improved mechanical behavior, resulting in a progressive layer-by-layer collapse mode under compression while avoiding stress shielding effects. Permeability analysis showed that gyroid scaffolds exhibited nearly isotropic permeability, whereas primitive and diamond scaffolds had higher axial permeability, with overall permeability decreasing as the unit cell size decreased. Cell experiments further confirmed the good biocompatibility of the scaffolds. This work highlights the potential of periodic gradient structures in Zn-3Mg alloys and provides a valuable reference for the functional design of biodegradable metal scaffolds for clinical bone defect repair.

We report the friction behavior of graphene edges within a carbon film, which encompasses structures ranging from amorphous carbon (a-C) to graphene nanocrystalline carbon (GNC). Structural characterization revealed that vertically growing graphene nanocrystallites were implanted into the a-C structure, exposing high-density layer edges on the film surface. Atomic force microscopy (AFM) nanofriction tests highlighted the nature of graphene edge friction. Firstly, the edge friction of GNC films was tested in a critical-contact state, and the results showed that graphene edges exhibited lower friction forces than did a-C edges. Secondly, the surface friction of GNC films was investigated in a full-contact state, revealing that the edge friction of graphene nanocrystallites regulated the surface friction of GNC films. As the edge density of graphene nanocrystallites increased, the nanofriction force of GNC films decreased. Finally, the mechanism of the regulated friction behavior was attributed to the number of edges of the graphene nanocrystallites, which provided plentiful sp2 C dangling bonds with weak bonding interactions and edge quantum wells with low surface potentials for lowering friction. These findings shed light on the importance of graphene-related materials and their high-density edges in the structural design and nanofriction application of carbon films.

The gas film thickness in aerostatic bearings is on the micrometer scale, under which the gas flow within the film no longer follows conventional macroscopic behavior but instead falls within the micro-scale flow regime. Under microscale conditions, gas rarefaction effects cause the conventional no-slip boundary condition to break down, resulting in velocity slip at the gas-solid interface. This velocity slip alters the pressure distribution within the gas film, thereby affecting the performance of the bearing. To investigate the influence of velocity slip on the static and dynamic performance of aerostatic spindles, a gas film flow model incorporating the velocity-slip effect is established. The results indicate that velocity slip reduces the static load-carrying capacity of the bearing while increasing its static stiffness. In addition, velocity slip leads to a reduction in the dynamic coefficients and the natural frequencies of the spindle. Therefore, the effects induced by velocity slip cannot be neglected during the practical operation of aerostatic spindles. The present study reveals the variation of spindle bearing performance and provides a theoretical basis for the optimized design of aerostatic spindle bearings.

Reaction-bonded silicon carbide (RB-SiC) ceramics are highly hard and brittle materials with an inherently heterogeneous microstructure comprising SiC matrix, free silicon, and interfacial phases. Conventional finite element models based on homogeneous material assumptions are inadequate for capturing the complex deformation and removal mechanisms in RB-SiC machining. This study develops a two-dimensional single-grit cutting model incorporating zero-thickness cohesive elements to explicitly represent the multiphase structure (SiC matrix, free silicon and phase boundary) of the RB-SiC workpiece, which is validated through nano-scratch tests. Subsequently, the model is employed to investigate material removal mechanisms and cutting force characteristics of RB-SiC ceramics in elliptical ultrasonic vibration-assisted cutting (EUVAC). Simulation results identify three primary material removal modes: friction-induced plastic deformation, pulverization via pore–crack interaction, and brittle fracture dominated by interfacial debonding and crack propagation-with brittle fracture being the predominant mechanism. Cracks initiate preferentially within the low-toughness SiC matrix and propagate along phase boundaries. Furthermore, cutting forces are effectively suppressed around 40 kHz, with no substantial further reduction beyond this frequency. Increased cutting depth elevates cutting forces and accelerates the occurrence of peak forces due to enhanced material deformation resistance. Therefore, high-frequency and low-amplitude machining is recommended for RB-SiC ceramics. These findings provide a theoretical basis for high-quality processing of RB-SiC ceramics.

Five-axis machine tools are extensively employed in the manufacturing of precise and complex components. Their machining accuracy is significantly constrained by geometric errors. The variations in geometric errors are intricate and challenging to quantify precisely. To address these challenges, a geometric error identification method based on single-axis and multi-axis measurements is presented. First, a motion error model is developed, and separate identification methods are proposed for the linear and rotary axes. For the linear axes, a combination of single-axis motion and multi-axis linkage error identification schemes is designed, utilizing measurements of positioning and straightness errors. For the rotary axes, a multi-point identification strategy is introduced, incorporating double ball bar measurements taken at various positions. Using this approach, all geometric errors are successfully identified. Finally, machining tests with standard workpieces are conducted. The numerical control instruction is compensated based on identification results and the developed motion error model. Experimental results indicate that the average machining accuracy of the standard workpieces is improved by 33.98%, demonstrating the feasibility of the proposed method.

Although Zn3Mg has been widely reported as a promising biodegradable Zn-based alloy with favourable mechanical performance, its role in regulating degradation behaviour, particularly under the unique microstructural conditions introduced by laser powder bed fusion (LPBF), remains highly controversial. In this study, the long-term in vitro degradation behaviour of laser powder bed fusion (LPBF) fabricated Zn3Mg alloy was systematically investigated in simulated body fluid over a period of up to 28 days and compared with that of pure Zn. The results reveal a pronounced time-dependent dual role of Mg during degradation. In the early (0–3 days) and intermediate–late (14–21 days) stages, the release of Mg²⁺ contributes to interfacial buffering and stabilises protective corrosion products, whereas in the intermediate stage (3–14 days), densification of the degradation layer inhibits Mg²⁺ transport, thereby diminishing its regulatory effect. In the final stage (21–28 days), local pH elevation and Cl⁻ enrichment weaken the protective effect of Mg, leading to a stabilised degradation rate of approximately 0.09 mm·year⁻¹. This study elucidates the dynamic competition between micro-galvanic corrosion and Mg²⁺-mediated interfacial regulation in LPBF-fabricated Zn3Mg alloy, providing mechanistic insights for the composition and microstructure design of biodegradable Zn-based implants.

In the five-axis stable milling of thin-walled blades, significant variations in surface micro-ripple morphology have been observed under different tool rake and tilt angle combinations, even when cutting parameters are within the chatter-free zone. This phenomenon suggests that tool attitude regulates the formation of residual ripples through a dynamic mechanism rather than simple geometric projection. To reveal the physical nature of this process, this paper proposes a surface topography modeling method that couples the forced vibration response with tool attitude. First, a two-dimensional dynamic model considering periodic cutting force excitation is established to solve for the forced vibration responses in the feed and normal directions. These vibration perturbations are then superimposed onto the ideal tool path. Subsequently, a three-dimensional surface topography simulation model is constructed, incorporating coordinate transformations to predict the microscopic residual ripple structure under various attitude combinations. Simulation results based on two typical experimental attitudes (30 degrees/-45 degrees and 15 degrees/-15 degrees) show strong agreement with measured data in terms of residual height and corrugation patterns. The study reveals that the 30 degrees/-45 degrees attitude effectively suppresses normal vibration and improves surface quality. This work provides a theoretical basis and a predictive tool for tool attitude optimization and micro-quality control in complex multi-axis machining processes.

Abstract This paper takes CNC coordinate grinding machines as the research object, aiming to solve the problem of accurately quantifying the overall spatial error of the machine from the bottom tolerance and identifying the weak links of key motion axes in the design stage. Firstly, by analysing the intrinsic relationship between the microsurface topography of key machine components and motion errors, an analytical mathematical model was constructed using the Fourier series to map tolerance parameters to geometric errors. Secondly, based on multi-body system (MBS) theory, a prediction model for the spatial motion errors of the entire machine was established, incorporating two motion chains: the tool and the workpiece. Finally, a global sensitivity analysis was performed on each motion axis using a method combining individual perturbation with comprehensive influence factors. The results indicate that, under the coupled action of multiple error sources, the contributions of each motion axis to the machine’s spatial error vary significantly. The W-axis has the highest influence weight, reaching 40.02%; the Z-axis is second, accounting for 29.92%; whilst the U-axis has the weakest influence, at only 2.11%. This study provides a scientific and quantitative basis for the optimal allocation of initial tolerances and targeted error compensation for key axes in CNC coordinate grinding machines.

Abstract The vertical straightness error of a rectangular closed hydrostatic guideway is a critical indicator of motion accuracy. To model this error without complete supporting-surface measurement data, a low-parameter method based on the error averaging mechanism and component characterisation is proposed. The vertical straightness error is formulated as an equivalent response jointly determined by the upper and lower supporting systems. Accordingly, a model comprising a global trend term and a local response term is established to represent the long-wavelength variation and localised deviation, respectively. Vertical straightness experiments are conducted on a rectangular closed hydrostatic guideway test rig for parameter identification and model validation. The results demonstrate that the proposed model can effectively capture both the overall trend and local features of the vertical straightness error without relying on complex oil-film analytical solutions or complete profile measurements of the supporting surfaces. The proposed method provides a practical basis for error analysis, accuracy evaluation, and structural optimisation of rectangular closed hydrostatic guideways.

Laser powder bed fusion (LPBF) paves a new way for fabricating zinc alloy implants with personalized and complex geometries, drawing significant attention in the biomedical field. However, Zn alloys fabricated from blended elemental (BP) and pre-alloyed (AP) powders with the same nominal composition exhibit markedly different microstructures and mechanical properties, whose underlying mechanisms remain unclear. In this study, Zn-3Mg alloys were successfully prepared via LPBF using both BP and AP feedstocks, and the melt-pool dynamics governing the microstructure and properties were revealed. The pronounced compositional heterogeneity in BP triggers intense solutal Marangoni convection, which promotes Zn-Mg mixing but also causes large thermal gradients and strong vapor recoil pressure, resulting in pore formation, localized grain refinement, and consequently lower density and strength. The BP sample, dominated by coarse alpha-Zn phase, exhibits significantly better ductility. In contrast, the chemically uniform AP promotes stable thermal flow, facilitating the formation of fine equiaxed grains, which contributes to superior strength and hardness. However, the uniformly dispersed brittle Mg2Zn11 phase severely compromises ductility. Furthermore, a subsequent laser remelting process was applied to the blended powder, which effectively reduced porosity by lowering thermal gradients and suppressing spattering, leading to a more uniform grain structure and improved density and strength. This work elucidates the interrelationships among powder characteristics, remelting strategy, melt-pool behavior, and final properties, establishing a universal framework for the microstructural design of high-performance biodegradable Zn-based and other LPBF-fabricated alloy systems.

The volumetric error of five-axis machine tools (FAMTs) is significantly influenced by geometric errors arising during multi-axis interpolation. These errors are primarily determined by manufacturing and assembly tolerances. The large number of tolerance parameters poses significant challenges to accurately identifying the key error contributors. This study proposes a method to identify critical tolerances for volumetric error in FAMTs using multi-body system modeling and sensitivity analysis. The model accounts for all geometric errors, and establishes a mapping between tolerance parameters and geometric errors. Furthermore, the machining workspace is discretized into a grid to quantify the influence of each tolerance parameter. Simulation results show the key tolerances influencing volumetric error are relatively concentrated. It is validated by machining a standard inspection workpiece on a FAMT. The average improvement in critical precision indicators for the workpiece was measured at 22.93

Accurate volumetric error model is the basis for accuracy design. In this paper, a universal model for volumetric error prediction considering tolerance is proposed. Firstly, geometric error parameters are obtained by analysing the motion forms of key components. Secondly, the map between geometric error and tolerance is developed using Fourier function. Subsequently, the volumetric error prediction model (VEPM) is established based on key component tolerance. The model was applied to guide the development of machine tools. Finally, model validation experiments are carried out with two configurations of machine tools. The results show that, for the horizontal grinder, the predicted values for ±45° diagonal errors are 0–2.7 μm and 0–4.5 μm, which are consistent with the measured average values of 0.03–2.33 μm and −0.10–5.46 μm, respectively. Moreover, the predicted and measured values for +45° diagonal error of the vertical grinder are −15.0–0 μm and −15.07–0 μm, respectively. The experimental results illustrate the VEPM is effective and universal. The model has the potential to be applied to the design and development of machine tools.

We reported the effect of doping on current-carrying friction behaviour of amorphous carbon (a-C) film. Si-doped, Ti-doped and pure a-C films were fabricated using a divergent electron cyclotron resonance plasma system. Structural analysis revealed that Si-doped and pure a-C films showed fully amorphous structures, while Ti-doped a-C films contained an amorphous matrix with embedded tiny sp(2) nanocrystallites. Current-carrying friction tests demonstrated Si-doped a-C films achieved low friction coefficients (mu = 0.02 similar to 0.04) within a short run-in period of 0 similar to 2 cycles. Similarly, Ti-doped a-C films reached low friction (mu = 0.03 similar to 0.05) within 2 similar to 3 cycles. In contrast, pure a-C films required longer run-in periods (10 similar to 15 cycles) to achieve low friction (mu = 0.05 similar to 0.06). Transfer film analysis identified Si-O/Si-OH bonds induced by Si-doping and sp(2) nanocrystallites facilitated by Ti-doping were critical factors to the rapid low-friction performance. Specifically, Si atoms contributed to terminal passivation of contact surfaces by reacting with oxygen to form Si-O/Si-OH bonds. While Ti atoms played a dual role in both inducing sp(2) nanocrystallites and promoting their formation under current-carrying conditions. The presence of terminal passivation and sp(2) nanocrystallites at contact interface enhanced the current-carrying friction performance of doped a-C films. These findings highlight the potential of Si- and Ti-doped a-C films in current-carrying friction applications.

Aerostatic spindle utilizes gas as the lubricating and supporting medium, enabling it to exhibit outstanding characteristics such as high precision, low temperature rise, and environmental friendliness during operation, thereby fulfilling the requirements of high-speed machining applications. However, during the operation of the aerostatic spindle, the increase in spindle speed induces velocity effects such as centrifugal force and gyroscopic effect, which jointly act on the spindle, resulting in vibration characteristics and rotational accuracy that differ from traditional conditions. Currently, there is relatively limited research on the influence of velocity effects on the motion behavior of aerostatic spindles. Therefore, in order to investigate the impact of velocity effects on the vibration characteristics and rotational accuracy of aerostatic spindles, a bearing-rotor system dynamics model based on velocity effects was established. The study found that velocity effects can increase the vibration amplitude and rotational errors of the spindle, and this influence intensifies as the spindle speed increases. Therefore, in the actual operation of the aerostatic spindle, the impact of the velocity effect cannot be neglected. This study provides an important theoretical basis for the dynamic prediction of the performance of the aerostatic spindle system and the optimal design of the spindle system.

This study investigates the wear behavior of Vascomax 300 rocket sled shoe material under high-speed friction and heavy-load conditions through integrated experimental and numerical approaches. A customized high-speed pin-on-disc apparatus was developed to characterize wear parameters, which were incorporated into a three-dimensional finite element model in ABAQUS® using the Archard wear model and UMESHMOTION subroutine with adaptive Lagrangian-Eulerian (ALE) meshing. The model accurately predicted wear depth distribution based on local contact pressure and sliding distance, while thermal effects were captured by introducing a convective heat transfer coefficient. Results revealed strong agreement between simulations and experiments, with an average wear depth error below 20 % and pronounced wear localization at the slider front and center under increased speeds. The findings provide valuable insights into friction-induced temperature rise, oxidation behavior, and wear mechanisms, offering a robust framework for predicting wear in rocket sled applications and optimizing material performance under extreme operating conditions.

The overall spatial accuracy of a precision machine tool directly influences its machining quality. As a representative form of spatial motion realized through multiaxis linkage, the diagonal error of the spatial body effectively reflects the linkage error characteristics. To improve the prediction of machine tool accuracy, this paper presents a modeling and prediction approach centered on the spatial body diagonal error. First, the structure of a five-axis machine tool is analyzed, and the mathematical relationship between tolerance and geometric errors is established using the Fourier series. Subsequently, an error transmission model grounded in multi-body system theory is developed to quantitatively predict diagonal errors. The proposed model is validated through both simulation and experimental analysis. Results indicate that the maximum deviation between predicted and measured values is 2.4 μm, demonstrating the accuracy and practical applicability. This method offers valuable insights into the evolution of tolerance and diagonal error, providing theoretical support for precision design and optimization of machine tools.

In the engineering application of porous aerostatic radial bearings, the gas supplied is generally not absolutely clean, and the micropores in porous materials are usually very small. As the aerostatic bearing continues to operate, impurities in the gas gradually accumulate and form blockages at certain points in the porous medium, affecting the bearing performance. Therefore, a systematic study of the impact of blockages in porous media on aerostatic bearings is essential. This paper establishes lubrication models for porous aerostatic radial bearings under both blockage-free and blocked conditions. Through Fluent simulation analysis, the effects of the number, location, and size of blockages on the static characteristics of the bearing are examined. An analysis of the extent of impact of blockages on bearing performance is also conducted, providing a reference basis for judging the operating condition of the bearing and optimizing bearing design in practical applications.

The high hardness and low fracture toughness of reaction-bonded silicon carbide (RB-SiC) ceramics result in brittle fracture-dominated material removal during conventional grinding, inevitably inducing surface/subsurface damage that compromises component performance and longevity. To elucidate the nanoscale deformation behavior and material removal mechanisms of RB-SiC ceramics, this study employs nanoindentation and nano-scratch techniques with a Berkovich indenter, coupled with scanning electron microscopy (SEM), to systematically investigate its micromechanical properties and deformation characteristics. Nanoindentation results reveal average hardness (H) and elastic modulus (E) values of 35.03 GPa and 471.8 GPa, respectively. A pronounced indentation size effect is observed at depths < 500 nm, indicating that intrinsic material properties dominate machining outcomes at shallow machining depths, while their influence diminishes at greater depths. Nano-scratch analyses revealed the indenter's progressive penetration process and the transition in material removal mechanisms. Furthermore, the correlation between applied load and deformation mechanisms (plastic-to-brittle transition and crack nucleation/propagation from phase boundaries) and frictional responses (residual depth, tangential force) was systematically investigated. These findings provide mechanistic insights into the interplay between nanoscale mechanical behavior and machining-induced damage, establishing a theoretical framework for optimizing precision machining parameters to suppress brittle fracture and enhance surface integrity. The results bridge microscale mechanical responses to macroscale machining outcomes, offering foundational guidance for advancing the high-precision manufacturing of RB-SiC ceramic components.

Monocrystalline silicon, as a typical hard and brittle material, is prone to subsurface damage during nanomachining, which affects the subsequent performance of processed workpieces. By adjusting cutting parameters, subsurface damage and surface quality during the machining process can be controlled and improved. Therefore, this article explored the formation mechanism of sub-surface damage in monocrystalline silicon during nanocutting process through molecular dynamics(MD) simulation, and systematically studied the effects of four processing parameters, namely cutting crystal plane, cutting speed, tool rake angle, and relative tool sharpness, on the depth of sub-surface damage and surface roughness. The results indicated that high hydrostatic stress and high temperature during the cutting process promote the amorphous phase transition of the workpiece atoms, resulting in subsurface damage. Changes in cutting parameters can significantly affect subsurface damage and surface roughness. By optimizing cutting parameters, subsurface damage and surface roughness can be effectively controlled and improved.