The fine cohesive abrasive mixing is a critical step in the fine-grained grinding wheel production process. However, the traditional mechanical mixing is facing great challenges due to the agglomeration and adhesion of fine abrasive caused by cohesive forces between powders. In this work, a novel method of vibration mixing for fine abrasive is developed. The coarse graining method is introduced to create the engineering scale of the discrete element model for fine diamond/CuSn composite powders mixing. The dynamic mechanism of blade vibration and particle surface energy parameters on the mixing performance is revealed. The results show that weak contact force networks are formed by the majority of particles with low velocities. The blade vibration creates strong contact force chains with a loose packing particles system. It promotes the movement, diffusion and mixing of particles in the chaotic state. The high powder surface energy can lead to the agglomeration of particles. The blade vibration exerts more energy on the particle system, which weakens clusters of particles and strengthens the mixing performance. Therefore, it is beneficial to achieve good fine cohesive abrasive mixing uniformity as the vibration amplitude and frequency increase, and the surface energy decreases. The findings provide technical support to improve the performance of fine-grained grinding wheels.

Traditional experimentally derived constitutive models for granular materials often fall short in meeting the computational efficiency requirements demanded by industrial block-forming processes. To overcome these limitations, we present a deep learning-based constitutive framework for granular materials incorporating matrix Long Short-Term Memory units. This approach establishes robust correlations between macroscopic mechanical properties and microstructural features of particle assemblies, while effectively capturing the history-dependent behavior of materials. A comprehensive database was developed using DEM simulations to capture porosity-time and stress-strain responses during uniaxial compaction of block-shaped granular materials under varied gradation and adhesion conditions. This database served as the foundation for constructing a data-driven constitutive model tailored to block-forming applications. Our results show that the mLSTM-based model achieves high predictive accuracy and strong discriminative capability. Mechanistic analysis further reveals that greater adhesion forces promote particle agglomeration, increasing porosity during loading, reducing loading stiffness, and producing rightward shifts and flattening in stress-strain curves. Similar trends emerge with increasing fine particle content across all gradation types, primarily due to enhanced interparticle adhesion. However, post-compaction porosity demonstrates a non-monotonic dependence on fine particle content, reaching minima at specific gradations - for example, 50% fines in binary PSD, 40-30% fines in ternary PSD, and n = 0.4 in Dinger-Funk PSD - coinciding with peak values of the dispersion index. Deep learning-based stress-strain constitutive models provide the theoretical foundation for finite element simulations. Gradation optimization results based on porosity offer a theoretical formulation guidance for block production processes.

Carbon fiber reinforced polyetheretherketone (CF/PEEK) composites possess excellent mechanical properties and thermal stability. However, during the processing of PEEK with large-tow carbon fibers, there are challenges such as dense fiber arrangement and high viscosity penetration of the resin, which usually require complex fiber spreading or surface treatment. In this work, a novel aqueous suspension-based impregnation process is developed to rapidly and continuously impregnate epoxy-sized large-tow carbon fibers with PEEK without any prior desizing or tow spreading. The suspension utilizes a multicomponent gradient-evaporation solvent system (deionized water with ethanol, ethylene glycol, and NMP) combined with synergistic surfactants (PVP K30, PEG-400, and Tween 80) to dramatically improve resin powder dispersion stability and lower interfacial tension. The addition of nano-SiO2 and a silane coupling agent (KH560) further enhances fiber-matrix interfacial bonding. Zeta potential analysis confirmed that the optimized suspension (pH 9, 1.5 wt% surfactants) achieved high stability with no observable sedimentation for 1 h, and contact angle tests showed effective wetting on sized fibers (only 2 degrees difference from desized). Using a custom continuous impregnation line, 48K tows were uniformly coated and consolidated at 1 m/min line speed. The resulting prepregs exhibited uniform resin distribution with fiber volume fractions of approximately 35% and porosity below 1%. A three-hour continuous production run demonstrated consistent prepreg quality over time. These results highlight that the proposed multicomponent suspension and process enable fast, continuous manufacturing of high-quality CF/PEEK prepregs from large-tow fibers without additional fiber treatment, representing a significant advancement in scalable thermoplastic composite fabrication.

Linear die filling is currently widely employed in industries. However, there is no comprehensive and systematic model to describe the powder die filling process. This paper utilizes dimensional analysis to extract and analyze various factors that affect the flow characteristics of powder based on DEM-CFD simulations. Several dimensionless parameters including the ratio of particle size to die depth (dphD−1), solid density number (ρpρg−1), shoe speed number (vρgLDμ−1), and force number (GpFDrag−1) were proposed based on the Pi theorem. The results showed that the filling ratio δ increased with the increase in dphD−1 and ρpρg−1 due to GpFDrag−1 rising. But it decreased with the increase in vρgLDμ−1 due to the shortening of effective filling time. Finally, a semi-empirical modeling of linear die filling was developed, taking the critical value (dphD−1)90 as the dependent variable and the solid density number (ρpρg−1) and shoe speed number (vρgLDμ−1) as independent variables. Hence, this model provides a new approach to computing the smallest shoe speed and designing the sizes of dies based on measurable material properties under complete die filling.

ObjectiveSelective laser melting (SLM)technology provides a new approach for the integratedmanufacture of metal-matrix diamond tools with structural and functional integration, which has drawn alot of interest from the academic and technicalcommunities. The powder spreading process is the keyprocess of SLM technology, which is very important toobtain a dense, flat and uniform powder bed. However,there are defects such as pits, scratches, loose packing ofpowder bed, uneven distribution of powder layer, andparticles segregation in the powder spreading process.Further research is required since the powder spreadingprocess of metal-based diamond composite powdermaterials entails intricate scientific and engineeringissues such as non-spherical particles and multicomponentpowders. In this work, three blades of linear,circular, and parabolic as well as roller spreaderstructures are selected to explore the influencemechanism of spreader structures on the powderspreading quality and particle dynamic behavior.Research results have guiding significance for theoptimization of powder spreading processes of metalmatrixdiamond tools in SLM.MethodsIn order to achieve the aforementionedobjectives, the diamond/CuSn powders were utilized asthe research object to build the three-dimensionalgeometry of two types of powders. In this work, theadhesion force was introduced into the particle contactdynamics model, which was based on the Hertz-Mindlinmodel and Johnson-Kendall-Roberts (JKR) theory. Adiscrete element model (DEM) describing the microforceof two kinds of powder particles was established.The DEM of powder spreading process was constructed,and three blades of linear, circular, and parabolic as wellas roller spreader structures were selected. Parametricequations were used to alter the spreader's geometricshape. It has been investigated how the spreaderstructural factors affect the powder bed's density and thediamond distribution's homogeneity. The particledynamic behavior and the mechanism of powder beddensification in the powder spreading process wereexplored. Furthermore, the physical mechanism ofparticles segregation and jamming in the process ofpowder spreading were revealed.Results and DiscussionsFirst, the influence ofspreader structures on the powder bed quality wasexamined. When the structural coefficient angle θ of thelinear blade increased from 0° to 90° , the powder spreading quality changed slightly. As the angle θincreased from 90° to 150° , the powder spreadingquality was significantly improved. The powderspreading quality was significantly improved as thestructural coefficient c of the circular blade increasedfrom 0.25 mm to 1.25 mm. When the structuralcoefficient p value of the parabolic structure increasedfrom 0.1 to 2, the relative bulk density decreased from0.36 to 0.29, and the standard deviation increased from0.031 to 0.041. Increasing the diameter of the roller canimprove the powder bed quality. Under the condition ofthe structural parameter optimization given in this work,the influence of spreader structures on the powder bedquality was comprehensively considered. The resultsshowed that the powder spreading quality of parabolicblade and roller spreaders was relatively good, thecircular blade was the second, and the linear blade wasrelatively poor. Second, the flow behavior of particleswas analyzed. With the translational motion of thespreader, the upper part of the powder pile was shearedand moved forward under the action of the spreader. Theparticles in the lower part of the powder pile passingthrough the gap between the spreader and the substratewere similar to particles flowing through the orifice ofthe conical hopper. In addition, the particles underwentcomplex diffusion and cyclic movement inside thepowder pile due to the complex movement of the roller.While the diffusion movement of particles inside thepowder pile was relatively weak during the blade'spowder spreading process. The structure of the bladespreader had a slight effect on the trajectory of particles.The trajectories of diamond and CuSn particles showedsimilar flow patterns. The particles driven by thespreader moved horizontally and rose, fluctuating adistance at a high position. Particles then avalancheddown the powder heap's slope as a result of gravity.Ultimately, the particles through the gap between thespreader and the substrate were deposited on thesubstrate. Then, the particle contact force chains wereexamined. With the increase of θ value and c value, andthe decrease of p value, the blade exerted an obliquedownward pressure on particles, increasing their normalcontact force and lessening the blade's shear effect onthem. This would improve the powder bed quality. Forthe roller spreader, increasing the diameter of the roller would increase the area of interaction between the rollerand the powder pile, which would increase the normalcontact force of particles, strengthen the compactioneffect of the roller and improve the powder bed quality.Finally, the volume fraction of diamond particles wasanalyzed in terms of its spatial distribution. There wasno significant difference in the effect of spreaderstructures on the volume fraction of diamond particles inthe X direction, but the volume fraction of diamondparticles first increased exponentially along the Xdirection before fluctuating about the predeterminedvalue. This demonstrated that there was particlessegregation due to the low concentration of diamondparticles close to the front of the powder bed. Theprimary cause was that the fine CuSn particles weremore likely to pass through the gap between thespreader and the substrate, and deposited on the front ofthe powder bed. While the coarse diamond particleswith irregular shapes created strong force chains that caused particle jamming.ConclusionsWith the increase of the linearstructure angle θ value and the circular structurecoefficient c value, the decrease of the parabolicstructure coefficient p value and the increase of theroller diameter d, the oblique downward pressure of thespreader on particles is enhanced which will increase thenormal contact force of particles. And the shear effect ofthe spreader on particles is weakened, therebyimproving the powder bed quality. The results show thatthe powder spreading quality of parabolic blade androller spreaders is relatively good, the circular blade isthe second, and the linear blade is relatively poor. Thevolume fraction of diamond particles first increasedexponentially along the X direction before fluctuatingabout the predetermined value, resulting in the diamondparticles segregation during the powder spreadingprocess.

Wet and sticky bulk materials exhibit poor flowability during the mixing process, which prevents adequate contact between dry and wet particles. This results in uneven moisture distribution and deterioration in the mixing system. To address these issues, the mixing process of viscous concrete was focused on a vertical blender. A comprehensive investigation into mixing mechanisms and particles flow patterns were conducted using the discrete element method (DEM). The accuracy of the contact parameters in DEM was calibrated through repose angle and validated by torques tested in a custom-built mixing platform. And then, the effects of moisture content, filling level, rotational speed, and inclined angle were systematically investigated with respect to key mixing metrics: the relative standard deviation (RSD), coordination number (CN), segregation index (SI) of wet particles, as well as liquid mass. The results indicated that when the moisture content is 8 %, filling level is 50 %, and rotational speed is more than 60 rpm, the CN and mixing efficiency are acceptable, and the RSD and SI are low, thereby improving the mixing quality. The convective motion was revealed as the dominant flow regime through statistical quantification of diffusion coefficients and Peclet numbers. Finally, Box-Behnken Design was employed to develop quadratic polynomial models for RSD, CN, and SI, which demonstrated strong accuracy in predicting mixing performance and enabled systematic optimization of critical process parameters.

Blockages in a transfer system are a crucial problem for the wet coals conveying process in thermal power plants. Improving the viscous material flow is a fundamental solution to prevent blockages. A discrete element simulation was employed to investigate the flow characteristics of viscous materials in transfer systems with different structures under vibration-assisted conditions. The results indicate that, near the structure wall, the adhesive force increased, which was the root cause of material blockages. Introducing vibration motions into the chute could break the adhesive forces between the wet particles and the structure wall. Compared with a linear chute, a curved chute was more sensitive to vibration movement and had less leftover viscous materials and a lower output velocity. Compared with a deflector hood, an impact plate had less residual material and a higher particle velocity because of its longer ejection distance and lower adhesive force. Based on the above simulation results, a transfer system with an impact plate and curved chute is proposed. By introducing the critical vibration intensity for the transfer system, the vibration parameters and transfer system structures are optimized. The aforementioned research findings provide guidance for intervention measures aimed at preventing material blockages in industrial bulk material conveying processes.

Nanofibers prepared by electrospinning have developed into a mature and effective method for sensor preparation due to the advantages of large specific surface area, high porosity, and controllable structure. Despite the abundance of research on electrospun fiber-based sensors in recent years, there remains a notable gap in the literature concerning the comprehensive electrospun fiber preparation process, unimodal sensor applications, and the design and fabrication of multifunctional sensors. This article systematically reviews the progress of electrospinning in multifunctional sensing, exploring various facets of this technology. Starting from the development history of electrospinning, technical principles, material selection, and influence parameters are introduced. The latest research advances in electrospinning on pressure sensing, strain sensing, temperature and humidity sensing, and gas sensing are presented in detail around the performance parameters of highperformance sensors. Importantly, this paper reviews the latest progress in structural design, fabrication methods, and performance optimization. Then, this paper summarizes current technical challenges and offers insights into future research trends in electrospun sensors. This comprehensive review aims to provide practical and theoretical references for the design and fabrication of high-performance fiber-based multifunctional sensors.

A novel method for the integrated production of structural and functional metal-matrix diamond composites is provided by selective laser melting (SLM) in the field of diamond tools. However, the uneven distribution of diamond particles and loose packing density in the powder bed can easily result in poor performance of diamond tools. In this work, a discrete element method model of diamond/CuSn composite powders is developed to simulate blade-spreading processes. It investigates how powder bed quality and particle dynamics are affected by diamond powder physical properties and powder spreading process parameters. The findings reveal that coarse diamond particles exhibit strong force chains at low velocities, whereas contact force chains are weak for fine CuSn particles at high velocities. It shows that diamond particles with irregular shapes have poor diffusivity and spreadability due to the large friction and mechanical locking forces, which causes diamond particles segregation. Therefore, the packing density and uniformity of the powder bed are both improved by reducing the volume fraction and particle size of diamond particles. In addition, the powder bed quality is improved by increasing the powder layer thickness and decreasing the translational speed of the blade, which weakens the shear expansion and jamming of diamond particles. The results have some significance for optimizing powder spreading processes toward the production of metal-matrix diamond composites in SLM.

Nanofibers prepared by electrospinning have developed into a mature and effective method for sensor preparation due to the advantages of large specific surface area, high porosity, and controllable structure. Despite the abundance of research on electrospun fiber-based sensors in recent years, there remains a notable gap in the literature concerning the comprehensive electrospun fiber preparation process, unimodal sensor applications, and the design and fabrication of multifunctional sensors. This article systematically reviews the progress of electrospinning in multifunctional sensing, exploring various facets of this technology. Starting from the development history of electrospinning, technical principles, material selection, and influence parameters are introduced. The latest research advances in electrospinning on pressure sensing, strain sensing, temperature and humidity sensing, and gas sensing are presented in detail around the performance parameters of high-performance sensors. Importantly, this paper reviews the latest progress in structural design, fabrication methods, and performance optimization. Then, this paper summarizes current technical challenges and offers insights into future research trends in electrospun sensors. This comprehensive review aims to provide practical and theoretical references for the design and fabrication of high-performance fiber-based multifunctional sensors.

Optimizing particle gradations to improve the powder bed quality is of practical engineering interest for powder spreading in additive manufacturing (AM). The discrete element model of ceramic powder is introduced to simulate blade-spreading and roller-spreading processes. Based on the packing theory, the effect of particle gradations on the powder bed quality and particle microscopic behavior is analyzed. The results show that fine particle gradations weaken the wall effect. The powder shear dilation in blade-spreading strengthens the loosening effect, however, the compaction effect of roller-spreading weakens the loosening effect. As coarse particle gradations increase, contact force chains become loose, however, strong force arches lead to particle jamming, uneven distribution, and voids in the powder bed. Particle segregation occurs because fine particle gradations pass through the gap between the substrate and spreader, and are deposited at the front part of the powder bed, while coarse particle gradations due to jamming are deposited at the end part of the powder bed. When the particle gradation coefficient is in the range of 0.1 to 0.5, the powder bed quality and particle segregation phenomenon are significantly improved compared to Gaussian distribution. The results can provide valuable references for the selection of particle gradations in AM.

The powder spreading process is usually performed at preheating temperature in powder-bed-based additive manufacturing (AM). Thus, the powder flowability characterisation at preheating temperature is important for powder spreading processes. However, devices for traditional powder flowability characterising methods are mainly designed for specific conditions at room temperature and cannot consider the effect of temperature on powder flowability. In this work, an experimental platform with a heated rotating drum was set up and a high-speed camera was used to record powder avalanche processes in a heated rotating drum for the powder flowability characterisation at preheating temperature. Nylon and stainless steel powder flowability at different temperatures was assessed by the statistical analysis of avalanche angle, avalanche time, arithmetic mean deviation and surface linearity of powder surface profile. Four parameters provide a good characterisation of powder flowability. The results can provide guidance for the powder flowability characterisation method at preheating temperature in AM.

The roller-spreading and blade-spreading are main powder spreading methods in powder-bed addi-tive manufacturing.The discrete element method was introduced to simulate nylon powder spreading by both roller and blade spreaders.The two spreading processes were compared from several aspects including particle flow behavior,particle contact forces,forces exerted on spreaders,particle segrega-tion and powder layer density.It is found that powder spreading methods mainly affect the movement trajectory of particles,particle contact forces and forces exerted on spreaders.Complicated dispersion and circulation movement of particles occur inside the powder pile by roller-spreading,while particles have relatively weak dispersion by the blade-spreading.The normal force applied to the roller introduces a compacting effect on the powder pile and creates strong force chains that distribute uniformly in the powder pile.Therefore,the powder bed with higher density can be obtained by roller-spreading in thicker powder layer due to the compacting effect.The blade spreader sustains tangential force mainly,so the blade-spreading process limits its application to thicker powder layer.As the powder layer thickness increases,the roller-spreading is more sensitive to segregation index than that of the blade-spreading.The comprehensive comparison of two spreading processes provides criteria for selecting spreading methods.

The powder spreading process is one of the key processes in the powder-bed-based additive manufacturing (AM) technology. The roller-spreading parameters include the powder spreading layer thickness H, roller’s diameter D, roller’s rotational speed ω and translational velocity V, which have a major impact on the powder spreadability in AM processes. In this paper, the nylon powder was taken as the research object, and the discrete element method (DEM) was deployed to simulate the nylon powder spreading process by a roller. The three powder spreadability indicators including the deposition fraction, percent coverage and deposition rate were established. The central composite design (CCD) model was used to generate 30 groups of simulation cases. The regression models of three powder spreadability indicators were fitted by the response surface method (RSM). The analysis of variance was used to prove the accuracy and predicting effectiveness of regression models. In addition, the effect of process parameters on powder spreadability indicators was analyzed in detail. The results showed that the powder spreading layer thickness H was a leading influencing factor. The roller’s translational velocity V was a less important influencing factor. The roller’s diameter D and rotational speed ω had a slight influence on powder spreadability indicators. Both the H and D with V were determined as the main interactive factors on powder spreadability indicators. The three powder spreadability indicators were taken as the optimization goal, and the multi-objective optimization of roller-spreading parameters was carried out by the expectation method. The predicted optimal combination of powder spreading parameters and powder spreadability indicators were obtained. Moreover, the optimal results were verified through the experiments. The results showed that the predicted results of powder spreadability indicators were in good agreement with experimental results. The research results in this paper can provide guidance for the optimization of roller-spreading parameters in AM.

The suitable powder flowability is critical to the success of powder spreading processes in powder-bed additive manufacturing (AM). There are several methods to test powder flowability, but the powder flowing is more complex in spreading processes and cannot be fully characterized with any single test method. Twelve kinds of powders which are widely used in AM are considered, and their flowabilities are measured. Besides the size and shape features of powders are described, the compressibility, shear and dynamic flow energy indexes of powders are measured by a FT4 powder rheometer. A comprehensive evaluation index (CEI) for evaluating powder flowability is proposed based on the principal component analysis of the test results, and reveals the impacts of powder surface modification and gradation on powder flowability. The CEI has a stronger correlation with the avalanche angle during powder spreading processes than other indexes, which is suitable to evaluate powder flowability in AM.

以Al2 O3陶瓷粉末为研究对象,建立了Al2 O3陶瓷粉末流动的离散元方法模型.针对增材制造铺粉工艺中滚筒振动对粉床质量的影响问题,模拟滚筒振动方向、振幅和频率对粉床的密实性、均匀性和平整度的影响规律.仿真结果表明:滚筒轴向振动可提高粉床密实性和均匀性,却会导致粉床平整度变差;滚筒径向振动会导致较差的粉床平整度,当振幅大于8μm时,颗粒的压缩和回弹效应导致粉床质量显著降低;滚筒切向振动可以提高粉床的密实性和均匀性,对粉床平整度影响很小,但切向振动频率过高容易引起粉末飞溅.研究表明在切向方向对滚筒施加低频的振动可以有效提高增材制造粉床质量.

The powder-bed with uniform and high density that determined by the spreading process parameters is the key factor for fabricating high performance parts in Additive Manufacturing (AM) process. In this work, Discrete Element Method (DEM) was deployed in order to simulate Al2O3 ceramic powder roller-spreading. The effects of roller-spreading parameters include translational velocity Vs, roller's rotational speed ω, roller's diameter D, and powder layer thickness H on powder-bed density were analyzed. The results show that the increased translational velocity of roller leads to poor powder-bed density. However, the larger roller's diameter will improve powder-bed density. Moreover, the roller's rotational speed has little effect on powder-bed density. Layer thickness is the most significant influencing factor on powder-bed density. When layer thickness is 50 μm, most of particles are pushed out of the build platform forming a lot of voids. However, when the layer thickness is greater than 150 μm, the powder-bed becomes more uniform and denser. This work can provide a reliable basis for roller-spreading parameters optimization.

尼龙粉末是增材制造中常用的粉体材料,温度对其流动性有重要影响.探索尼龙粉末增材制造预热温度下的流动性是研究选择性激光烧结(selective laser sintering,SLS)工艺中粉体铺展成形的基础.选取SLS技术中的尼龙粉末为原材料,采用离散元数值方法,研究尼龙粉末的流动行为,是增材制造工艺数值模拟和铺粉工艺优化的研究热点.以Hertz-Mindlin模型为基础,基于Hamaker理论模型和库伦定律,在尼龙粉末的接触动力学模型中引入范德华力和静电力,建立预热温度下尼龙粉末流动的离散元模型(discrete element method,DEM),通过对比相应实验结果,标定了该模型的参数.对加热旋转圆筒中尼龙粉末流动过程进行了DEM数值模拟,校核了所建模型的正确性,并研究了粉体粒径分布对尼龙粉末流动特性的影响规律.研究表明,尼龙粉末黏附力是静电力与范德华力的共同作用结果;随着粉体粒径的增大,尼龙粉末崩塌角增大,流动性增强;相对于高斯粒径分布,粒径均匀分布的尼龙粉末颗粒流动性更强.研究结果可指导SLS中铺粉工艺的优化.

The most commonly used material for fused deposition molding FDM build parts is polylactic acid PLA.CHCL3 is used for spray polishing surface which can improve surface quality of FDM build parts.This paper investigates the effect of the polishing temperature,polishing time and polishing concentration on the FDM build parts.Experimental results show that the surface roughness of FDM build parts reduces with the increasing of temperature and time,but the surface roughness of FDM build parts increase slightly after the temperature and time reaching a certain value.With the increasing of concentration of polishing liquid,the surface roughness of FDM build parts reduces sharply.At a polishing temperature of 60 ℃,polishing time of 7 min and a concentration of polishing liquid of 100％,the surface roughness of FDM build parts after polishing decreases sharply;the surface topography has significantly improved;and the effect on the dimensional accuracy and quality of parts is small.

With the development of digital technology in the stomatology application and digital fabrication of dentures will be the trend in the future.During the process of digital fabrication of dentures ,3D printed dental casts will replace traditional plaster casts.Preparing standard cylinder and rectangular specimens by 3D printing and pour plaster impression and measuring the me-chanical properties and surface roughness of specimens are indirect comparison with 3D printed dental casts and traditional plaster casts.Besides the dimensional accuracy of them are analyzed in comparison .Compared with traditional plaster casts ,3D printed dental casts are less in hardness ,but better in compressive strength ,bending strength and surface roughness .The dimensional ac-curacy of 3D printed dental casts is similar to traditional plaster casts ,but the consistency of 3D printed dental casts is better . Comparative analysis between 3D printed dental casts and traditional plaster casts ,the study shows that 3D printed dental casts which are more superior to traditional plaster casts ,can fully replace traditional plaster casts for digital fabrication of dentures .