A novel integrated microfluidic chip for on-demand electrostatic droplet charging and sorting

On-demand droplet sorting is extensively applied for the efficient manipulation and genome-wide analysis of individual cells.However,state-of-the-art microfluidic chips for droplet sorting still suffer from low sorting speeds,sample loss,and labor-intensive preparation procedures.Here,we demonstrate the development of a novel microfluidic chip that integrates droplet generation,on-demand electrostatic droplet charging,and high-throughput sorting.The charging electrode is a copper wire buried above the nozzle of the microchannel,and the deflecting electrode is the phosphate buffered saline in the microchannel,which greatly simplifies the structure and fabrication process of the chip.Moreover,this chip is capable of high-frequency droplet generation and sorting,with a frequency of 11.757 kHz in the drop state.The chip completes the selective charging process via electrostatic induction during droplet generation.On-demand charged microdroplets can arbitrarilymove to specific exit channels in a three-dimensional(3D)-deflected electric field,which can be controlled according to user requirements,and the flux of droplet deflection is thereby significantly enhanced.Furthermore,a lossless modification strategy is presented to improve the accuracy of droplet deflection or harvest rate from 97.49% to 99.38% by monitoring the frequency of droplet generation in real time and feeding it back to the charging signal.This chip has great potential for quantitative processing and analysis of single cells for elucidating cell-to-cell variations.

Nonlinear dynamics of a circular curved cantilevered pipe conveying pulsating fluid based on the geometrically exact model

Due to the novel applications of flexible pipes conveying fluid in the field of soft robotics and biomedicine,the investigations on the mechanical responses of the pipes have attracted considerable attention.The fluid-structure interaction(FSI)between the pipe with a curved shape and the time-varying internal fluid flow brings a great challenge to the revelation of the dynamical behaviors of flexible pipes,especially when the pipe is highly flexible and usually undergoes large deformations.In this work,the geometrically exact model(GEM)for a curved cantilevered pipe conveying pulsating fluid is developed based on the extended Hamilton's principle.The stability of the curved pipe with three different subtended angles is examined with the consideration of steady fluid flow.Specific attention is concentrated on the large-deformation resonance of circular pipes conveying pulsating fluid,which is often encountered in practical engineering.By constructing bifurcation diagrams,oscillating shapes,phase portraits,time traces,and Poincarémaps,the dynamic responses of the curved pipe under various system parameters are revealed.The mean flow velocity of the pulsating fluid is chosen to be either subcritical or supercritical.The numerical results show that the curved pipe conveying pulsating fluid can exhibit rich dynamical behaviors,including periodic and quasi-periodic motions.It is also found that the preferred instability type of a cantilevered curved pipe conveying steady fluid is mainly in the flutter of the second mode.For a moderate value of the mass ratio,however,a third-mode flutter may occur,which is quite different from that of a straight pipe system.

Atomic-scale engineering of advanced catalytic and energy materials via atomic layer deposition for eco-friendly vehicles

Zero-emission eco-friendly vehicles with partly or fully electric powertrains have exhibited rapidly increased demand for reducing the emissions of air pollutants and improving the energy efficiency. Advanced catalytic and energy materials are essential as the significant portions in the key technologies of eco-friendly vehicles, such as the exhaust emission control system,power lithium ion battery and hydrogen fuel cell. Precise synthesis and surface modification of the functional materials and electrodes are required to satisfy the efficient surface and interface catalysis, as well as rapid electron/ion transport. Atomic layer deposition(ALD), an atomic and close-to-atomic scale manufacturing method, shows unique characteristics of precise thickness control, uniformity and conformality for film deposition, which has emerged as an important technique to design and engineer advanced catalytic and energy materials. This review has summarized recent process of ALD on the controllable preparation and modification of metal and oxide catalysts, as well as lithium ion battery and fuel cell electrodes. The enhanced catalytic and electrochemical performances are discussed with the unique nanostructures prepared by ALD. Recent works on ALD reactors for mass production are highlighted. The challenges involved in the research and development of ALD on the future practical applications are presented, including precursor and deposition process investigation, practical device performance evaluation, large-scale and efficient production, etc.

基于CFD的具有首翼的新型飞翔形式AUV升力和阻力估计:对阻力极曲线和推力估计的见解

To achieve hydrodynamic design excellence in Autonomous Underwater Vehicles(AUVs)largely depends on the accurate prediction of lift and drag forces.The study presents Computational Fluid Dynamics(CFD)-based lift and drag estimations of a novel torpedo-shaped flight-style AUV with bow-wings.The horizontal bow-wings are provided to accommodate the electromagnetic arrays used to perform the cable detection and tracking operations near the seabed.The hydrodynamic performance of the AUV due to addition of these horizontal bow-wings is required to be investigated,particularly at the initial design stage.Hence,CFD techniques are employed to compute the lift and drag forces observed by the flight-style AUV,maneuvering underwater at different angles of attack and varying speeds.The Reynolds-Averaged Navier-Stokes Equations(RANSE)closure is achieved by employing the modified k-ϵ model and Two-Scale Wall Function(2-SWF)approach is used for boundary layer treatment.Further,the study also highlights the unique mesh refinement and solution-adaptive meshing techniques to perform the CFD simulations in Solidworks Flow Simulation(SWFS)environment.The drag polar curve for flight-style AUV with and without bow-wings is generated using the computed lift and drag coefficients.The curve provided essential insights for achieving hydrodynamically efficient and optimized AUV design.From the drag polar curve,it is revealed that due to horizontal bow-wings,the flight-style AUV is capable to generate higher lift with less drag and thus,it gives better lift-to-drag ratio compared to the AUV without bow-wings.Moreover,simulated results of axial drag observed by the AUV have also been compared with free-running experimental results and are found in good agreement.

飞秒激光-化学混合制备多基底超疏水表面

超疏水表面因具有多种功能和广泛的应用引起了人们极大的兴趣。目前制备超疏水表面的方法大多只适用于一种或几种特定的基底材料,具有依赖基底的缺点。本文提出了一种基于飞秒激光-化学混合加工制备与基底无关的超疏水表面的方法。通过飞秒激光直接写入技术在基底上构建出微/纳米结构,然后用硬脂酸改性。硬脂酸涂覆激光处理后的样品(LTx-SA,x表示不同的样品)表面具有优异的超疏水和自清洁性能。此外,值得注意的是,将基底从20℃加热到100℃,或清洗基板10次,或将基板暴露在空气中60 d后,LTx-SA表面仍然保持稳定的超疏水特性。这项工作为制备与基底无关的超疏水表面提供了一种有效而简单的策略。

Atomic layer deposition in advanced display technologies:from photoluminescence to encapsulation

Driven by the growing demand for next-generation displays,the development of advanced luminescent materials with exceptional photoelectric properties is rapidly accelerating,with such materials including quantum dots and phosphors,etc.Nevertheless,the primary challenge preventing the practical application of these luminescent materials lies in meeting the required durability standards.Atomic layer deposition(ALD)has,therefore,been employed to stabilize luminescent materials,and as a result,flexible display devices have been fabricated through material modification,surface and interface engineering,encapsulation,cross-scale manufacturing,and simulations.In addition,the appropriate equipment has been developed for both spatial ALD and fluidized ALD to satisfy the low-cost,high-efficiency,and high-reliability manufacturing requirements.This strategic approach establishes the groundwork for the development of ultra-stable luminescent materials,highly efficient light-emitting diodes(LEDs),and thin-film packaging.Ultimately,this significantly enhances their potential applicability in LED illumination and backlighted displays,marking a notable advancement in the display industry.

The welding application of high strength steels used in engineering machinery

With the rapid development of low alloy steel strength level,more problems caused by welding are exposed day by day.Recently,the efforts have been paid to improve or enchance the low toughness of heated affected zone and welded metal which can enchance the comprehensive mechanical properties that is the core scientific problems of its safe operation by researching crack initiation and crack propragation attracted a rapidly growing interest.This article focuses on the research status and progress of welding technology and joint microstructure and properties of advanced steel materials.The influence of shielding gas on the microstructure evolution of deposited metals,the effect heat input of welded joint performance,interpass temperature and alloy elements on welded joints microstructure and M-A constituent evolution and properties are reviewed in detail.And for the heat affected zone,the grain size and microstructure as well as the shape,size,and distribution of M-A constituent,have a significant impact on the impact toughness.This paper is an attempt to review the effect of different welding process parameters on welded metal and HAZ of HSLA steels.

Ultrafast laser-chemical modification hybrid fabrication of hydrostatic bearings with a superhydrophobicity solid-liquid interface

Oil film vortex severely reduces the stability of hydrostatic bearings. A solid-liquid interface with drag and slip properties can weaken the oil film vortex of the bearing. Here, a combined picosecond laser ablation and chemical modification method is proposed to prepare surfaces with microbulge array structure on 6061 aluminum alloy substrates. Because of the low surface energy of the perfluorododecyltriethoxysilane modification and the bulge geometry of the microbulge array structure, the surface shows excellent superhydrophobicity. The optimum contact angle in air for water is 164°, and that for oil is 139°. Two surfaces with “lotus-leaf effect” and “rose-petal effect” were obtained by controlling the processing parameters. The drag reduction properties of superhydrophobic surfaces were systematically investigated with slip lengths of 22.26 and 36.25 μm for deionized water and VG5 lubricant, respectively. In addition, the superhydrophobic surface exhibits excellent mechanical durability and thermal stability. The proposed method provides a new idea for vortex suppression in hydrostatic bearings and improves the stability of bearings in high-speed operation.

Planning method of droplet fusion scheduling based on mixedinteger programming

The emergence of new display devices,such as organic light-emitting diodes,has brought about numerous advantages,including high material utilization,low cost,and high adaptability.These devices are manufactured using inkjet printing and possess the potential to become a key technology for display transformations.However,a challenge in achieving this is the display effect that reveals uneven brightness and darkness,which can be avoided by controlling the volume of ink solution in a pixel to within 5%.Currently,the volume difference among the nozzles of commercial printheads does not meet the requirements for volume uniformity,thus challenging the printing process.Therefore,designing a suitable printing method that allows for the fusion of different volumes of ink droplets,ultimately reducing the error of the post fusion process,is necessary.In this study,we propose a print display droplet fusion scheduling method comprising two main steps.First,we use a dichotomous trust domain algorithm to obtain a feasible range of printhead docking point spacings for different nozzle and pixel panel resolutions.Second,we model the printing process as a droplet fusion scheduling model based on mixed integer programming,with the optimization objective of achieving intra pixel volume uniformity via ensuring the volume uniformity of ink droplets within all pixels.We verified this method through numerical simulations and printing experiments using 394 pixels per inch(ppi)pixel panels and successfully reduced the volume uniformity error among pixels to within 5%.

Buckling optimization of curvilinear fiber-reinforced composite structures using a parametric level set method

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

High-Order Two-Scale Asymptotic Paradigm for the Elastodynamic Homogenization of Periodic Composites

The classical two-scale asymptotic paradigm provides macroscopic and microscopic analyses for the elastodynamic homogenization of periodic composites based on the spatial or/and temporal variable,which offers an approximate framework for the asymptotic homogenization analysis of the motion equation.However,in this framework,the growing complexity of the homogenization formulation gradually becomes an obstacle as the asymptotic order increases.In such a context,a compact,fast,and accurate asymptotic paradigm is developed.This work reviews the high-order spatial two-scale asymptotic paradigm with the effective displacement field representation and optimizes the implementation by symmetrizing the tensor to be determined.Remarkably,the modified implementation gets rid of the excessive memory consumption required for computing the high-order tensor,which is demonstrated by representative one-and two-dimensional cases.The numerical results show that(1)the contrast of the material parameters between media in composites directly affects the convergence rate of the asymptotic results for the homogenization of periodic composites,(2)the convergence error of the asymptotic results mainly comes from the truncation error of the modified asymptotic homogenized motion equation,and(3)the excessive norm of the normalized wavenumber vector in the two-dimensional inclusion case may lead to a non-convergence of the asymptotic results.

Electrohydrodynamic printing for high resolution patterning of flexible electronics toward industrial applications

Electrohydrodynamic(EHD)printing technique,which deposits micro/nanostructures through high electric force,has recently attracted significant research interest owing to their fascinating characteristics in high resolution(<1μm),wide material applicability(ink viscosity 1–10000 cps),tunable printing modes(electrospray,electrospinning,and EHD jet printing),and compatibility with flexible/wearable applications.Since the laboratory level of the EHD printed electronics'resolution and efficiency is gradually approaching the commercial application level,an urgent need for developing EHD technique from laboratory into industrialization have been put forward.Herein,we first discuss the EHD printing technique,including the ink design,droplet formation,and key technologies for promoting printing efficiency/accuracy.Then we summarize the recent progress of EHD printing in fabrication of displays,organic field-effect transistors(OFETs),transparent electrodes,and sensors and actuators.Finally,a brief summary and the outlook for future research effort are presented.

Experimental study of solid-liquid origami composite structures with improved impact resistance

In this paper,a liquid-solid origami composite design is proposed for the improvement of impact resistance.Employing this design strategy,Kresling origami composite structures with different fillings were designed and fabricated,namely air,water,and shear thickening fluid(STF).Quasi-static compression and drop-weight impact experiments were carried out to compare and reveal the static and dynamic mechanical behavior of these structures.The results from drop-weight impact experiments demonstrated that the solid-liquid Kresling origami composite structures exhibited superior yield strength and reduced peak force when compared to their empty counterparts.Notably,the Kresling origami structures filled with STF exhibited significantly heightened yield strength and reduced peak force.For example,at an impact velocity of 3 m/s,the yield strength of single-layer STF-filled Kresling origami structures increased by 772.7%and the peak force decreased by 68.6%.This liquid-solid origami composite design holds the potential to advance the application of origami structures in critical areas such as aerospace,intelligent protection and other important fields.The demonstrated improvements in impact resistance underscore the practical viability of this approach in enhancing structural performance for a range of applications.

Data-driven Product Functional Confguration:Patent Data and Hypergraph

The product functional confguration(PFC)is typically used by frms to satisfy the individual requirements of customers and is realized based on market analysis.This study aims to help frms analyze functions and realize functional confgurations using patent data.This study frst proposes a patent-data-driven PFC method based on a hypergraph network.It then constructs a weighted network model to optimize the combination of product function quantity and object from the perspective of big data,as follows:(1)The functional knowledge contained in the patent is extracted.(2)The functional hypergraph is constructed based on the co-occurrence relationship between patents and applicants.(3)The function and patent weight are calculated from the patent applicant’s perspective and patent value.(4)A weight calculation model of the PFC is developed.(5)The weighted frequent subgraph algorithm is used to obtain the optimal function combination list.This method is applied to an innovative design process of a bathroom shower.The results indicate that this method can help frms detach optimal function candidates and develop a multifunctional product.

基于多模态融合的激光除漆检测方法

激光清洗是一种高度非线性物理过程,为解决激光清洗单模态(例如声学或视觉)检测性能不高,信息间利用率较低的问题,本文提出了基于激光除漆实验构建多模态特征融合网络模型。通过结合分段聚合近似以及格拉米角场解决不同模态间异构数据转换与对齐问题。并通过引入注意力机制优化双路径网络和密集连接网络增强对视觉图像和声波的特征提取与融合,从而实现激光除漆的多模态最优判别检测。实验结果表明,所构建模型在实验数据集上的验证准确率为99.17%,相比激光除漆单模态检测最优准确率提高5.77%。通过注意力机制优化特征提取网络,模型准确率提升3.3%。结果验证了本文所构建的多模态特征融合模型在检测激光除漆检测中具有更好的分类性能,模型能有效融合声波数据和视觉图像数据,实现激光除漆的准确检测。

Lattice Boltzmann study on the effects of surface nanostructure on wettability with application in laser scanning fabrication of superhydrophobic surfaces

Nanostructured surfaces with dimensions on a scale of a few millimeters exhibit remarkable hydrophobicity.The geometry of these nanostructures considerably affects their wettability.However,determining the optimal geometry is challenging due to the abundance of geometry parameters and the difficulty in numerically describing their effects on wettability at the mesoscopic scale.In addition,the fabrication of nanostructured surfaces with precise geometries is challenging.We establish a lattice Boltzmann method(LBM)model to address these challenges.We use the model to gain mesoscopic insights into the interaction between droplets and nanostructures.Our model can accurately reproduce contact angles(CAs)on various nanostructured surfaces and enables investigation of the effects of nanostructure geometry on wettability.We optimize the geometry of the nanostructures using the insights provided by the LBM model on the wettability mechanisms.Our analysis indicates that cones with dimensions of 40μm in width and 33μm in height exhibit the highest hydrophobicity.We successfully fabricate a superhydrophobic surface with the desired geometry via laser scanning,achieving a CA of 163°.We believe that this approach,which combines the LBM model and laser manufacturing,will enable a better understanding of the wettability mechanism and provide a high-performance approach for fabricating superhydrophobic surfaces.

Adaptive sampling for corrugated plate digitization using a laser displacement sensor

The surface quality of a corrugated plate directly determines the heat transfer property of the thermal power mechanical apparatus.Traditional detection methods are impractical for real-world production,being slow and destructive.In contrast,the point laser displacement sensor,employing the optical triangle method,emerges as a promising device for assessing parts with variable curvature and highly reflective surfaces.Despite its benefits,high-density sampling by an innate frequency introduces challenges such as data redundancy and a poor signal-to-noise ratio,potentially affecting the efficiency and precision of subsequent data processing.To address these challenges,adjustable frequency data sampling has been developed for this sensor,allowing adaptive sampling for corrugated plate digitization.The process begins with surface digitization to extract discrete points,which are transformed into intersection curves using the B-spline fitting technique.Subsequently,dominant points are identified,considering multigeometric constraints for curvature and arch height.Finally,the sampling signal is adjusted based on the distribution information of dominant points.Comparative results indicate that the proposed method effectively minimizes redundant sampling without compromising the accurate capture of essential geometric features.

WeldNet:A voxel-based deep learning network for point cloud annular weld seam detection

Weld seam detection is an important part of automated welding.At present,few studies have been conducted on annular weld seams,and a lot of defects exist in the point cloud model of the tube sheet obtained by RGB-D cameras and photography methods.Aiming at the above problems,this paper proposed an annular weld seam detection network named WeldNet where a voxel feature encoding layer was adaptively improved for annular weld seams,the sparse convolutional network and region proposal network(RPN)were used to detect annular weld seam position,and an annular weld seam detection loss function was designed.Further,an annular weld seam dataset was established to train the network.Compared with the random sampling consistency(RANSAC)method,WeldNet has a higher detection accuracy,as well as a higher detection success rate which has increased by 23%.Compared with U-Net,WeldNet has been proven to achieve a better detection result,and the intersection over the union of the weld seam detection is improved by 17.8%.

Surface roughness classification using light scattering matrix and deep learning

High-quality optical components have been widely used in various applications;thus,extremely high beam quality is required.Moreover,surface roughness is a key indicator of the surface quality.In this study,the angular distribution of light scattering field intensity was obtained for surfaces having different roughness profiles based on the finite difference time domain(FDTD)method,and the results were compared with those obtained using the generalized Harvey-Shack(GHS)theory.It was shown that the FDTD approach can be used for an accurate simulation of the scattered field of a rough surface,and the superposition of results obtained from many surfaces that have the same roughness level was in good agreement with the result given by the analytic GHS model.A light scattering matrix(LSM)method was proposed based on the FDTD simulation results that could obtain rich surface roughness information.The classification effect of LSM was compared with that of the single-incidence scattering distribution(SISD)based on a ResNet-50 deep learning network.The classification accuracy of the model trained with the LSM dataset was obtained as 95.74%,which was 23.40%higher than that trained using the SISD dataset.Moreover,the effects of different noise types and filtering methods on the classification performance were analyzed,and the LSM was also shown to improve the robustness and generalizability of the trained surface roughness classifier.Overall,the proposed LSM method has important implications for improving the data acquisition scheme of current light scattering measurement systems,and it also has the potential to be used for detection and characterization of surface defects of optical components.

Machine learning-assisted sparse observation assimilation for real-time aerodynamic field perception

Accurate aerodynamic distribution perception and real-time flight state evaluation are crucial for flight safety,e.g.,stall detection.However,the observations are usually sparse due to limitations in sensor mounting space and cost,and a reconstruction technology is urgently required.Herein,a machine learning-assisted assimilation method based on sparse observations has been proposed.Different from the traditional reconstruction methods focusing on boundary condition correction,the proposed method formulates the flow field pressure distribution as a linear superposition of flow field modes,thereby forming a real-time reconstruction pattern that combines offline modal extraction using computational fluid dynamics(CFD)with real-time determination of modal weights using a neural network.In this study,CFD simulations were conducted under 800different operating conditions for common modal extraction and model training.The weights of these modes were determined online based on merely five observations for reconstructing the full pressure field.A pressure reconstruction with a relative error of 6.1%and a mean square error of 0.003 was achieved within the prescribed condition range.The computational cost was just2 ms for each reconstruction run,significantly faster than the 20 min required by the classical reconstruction ensemble transform Kalman filter.It also showed that the method maintains almost the same accuracy amidst 1.5%measurement noise.As practical examples,shock waves and the change of lift coefficient were analyzed using the proposed method,providing remarkable evidence for the capability of the method in supporting stall detection.These validate the method’s effectiveness and explore its potential in real-time and accurate monitoring of an aircraft.