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.

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.

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.

Pixelated non-volatile programmable photonic integrated circuits with 20-level intermediate states

Multi-level programmable photonic integrated circuits(PICs)and optical metasurfaces have gained widespread attention in many fields,such as neuromorphic photonics,opticalcommunications,and quantum information.In this paper,we propose pixelated programmable Si_(3)N_(4)PICs with record-high 20-level intermediate states at 785 nm wavelength.Such flexibility in phase or amplitude modulation is achieved by a programmable Sb_(2)S_(3)matrix,the footprint of whose elements can be as small as 1.2μm,limited only by the optical diffraction limit of anin-house developed pulsed laser writing system.We believe our work lays the foundation for laser-writing ultra-high-level(20 levels and even more)programmable photonic systems and metasurfaces based on phase change materials,which could catalyze diverse applications such as programmable neuromorphic photonics,biosensing,optical computing,photonic quantum computing,and reconfigurable metasurfaces.

Field-assisted machining of difficult-to-machine materials

Difficult-to-machine materials (DMMs) are extensively applied in critical fields such as aviation,semiconductor,biomedicine,and other key fields due to their excellent material properties.However,traditional machining technologies often struggle to achieve ultra-precision with DMMs resulting from poor surface quality and low processing efficiency.In recent years,field-assisted machining (FAM) technology has emerged as a new generation of machining technology based on innovative principles such as laser heating,tool vibration,magnetic magnetization,and plasma modification,providing a new solution for improving the machinability of DMMs.This technology not only addresses these limitations of traditional machining methods,but also has become a hot topic of research in the domain of ultra-precision machining of DMMs.Many new methods and principles have been introduced and investigated one after another,yet few studies have presented a comprehensive analysis and summarization.To fill this gap and understand the development trend of FAM,this study provides an important overview of FAM,covering different assisted machining methods,application effects,mechanism analysis,and equipment design.The current deficiencies and future challenges of FAM are summarized to lay the foundation for the further development of multi-field hybrid assisted and intelligent FAM technologies.

The Immense Impact of Reverse Edges on Large Hierarchical Networks

Hierarchical networks are frequently encountered in animal groups,gene networks,and artificial engineering systems such as multiple robots,unmanned vehicle systems,smart grids,wind farm networks,and so forth.The structure of a large directed hierarchical network is often strongly influenced by reverse edges from lower-to higher-level nodes,such as lagging birds’howl in a flock or the opinions of lowerlevel individuals feeding back to higher-level ones in a social group.This study reveals that,for most large-scale real hierarchical networks,the majority of the reverse edges do not affect the synchronization process of the entire network;the synchronization process is influenced only by a small part of these reverse edges along specific paths.More surprisingly,a single effective reverse edge can slow down the synchronization of a huge hierarchical network by over 60%.The effect of such edges depends not on the network size but only on the average in-degree of the involved subnetwork.The overwhelming majority of active reverse edges turn out to have some kind of“bunching”effect on the information flows of hierarchical networks,which slows down synchronization processes.This finding refines the current understanding of the role of reverse edges in many natural,social,and engineering hierarchical networks,which might be beneficial for precisely tuning the synchronization rhythms of these networks.Our study also proposes an effective way to attack a hierarchical network by adding a malicious reverse edge to it and provides some guidance for protecting a network by screening out the specific small proportion of vulnerable nodes.

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.

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.

使用深度学习在CTA扫描卷下实现主动脉夹层分类和直径测量的双功能系统

Acute aortic dissection is one of the most life-threatening cardiovascular diseases,with a high mortality rate.Its prevalence ranges from 0.2%to 0.8%in humans,resulting in a significant number of deaths due to being missed in manual examinations.More importantly,the aortic diameter—a critical indicator for surgical selection—significantly influences the outcomes of surgeries post-diagnosis.Therefore,it is an urgent yet challenging mission to develop an automatic aortic dissection diagnostic system that can recognize and classify the aortic dissection type and measure the aortic diameter.This paper offers a dual-functional deep learning system called aortic dissections diagnosis-aiding system(DDAsys)that enables both accurate classification of aortic dissection and precise diameter measurement of the aorta.To this end,we created a dataset containing 61190 computed tomography angiography(CTA)images from 279 patients from the Division of Cardiovascular Surgery at Tongji Hospital,Wuhan,China.The dataset provides a slice-level summary of difficult-to-identify features,which helps to improve the accuracy of both recognition and classification.Our system achieves a recognition F1 score of 0.984,an average classification F1 score of 0.935,and the respective measurement precisions for ascending and descending aortic diameters are 0.994 mm and 0.767 mm root mean square error(RMSE).The high consistency(88.6%)between the recommended surgical treatments and the actual corresponding surgeries verifies the capability of our system to aid clinicians in developing a more prompt,precise,and consistent treatment strategy.

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.

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%.

Mathematical Modeling and a Multiswarm Collaborative Optimization Algorithm for Fuzzy Integrated Process Planning and Scheduling Problem

Considering both process planning and shop scheduling in manufacturing can fully utilize their complementarities,resulting in improved rationality of process routes and high-quality and efficient production. Hence,the study of Integrated Process Planning and Scheduling (IPPS) has become a hot topic in the current production field. However,when performing this integrated optimization,the uncertainty of processing time is a realistic key point that cannot be neglected. Thus,this paper investigates a Fuzzy IPPS (FIPPS) problem to minimize the maximum fuzzy completion time. Compared with the conventional IPPS problem,FIPPS considers the fuzzy process time in the uncertain production environment,which is more practical and realistic. However,it is difficult to solve the FIPPS problem due to the complicated fuzzy calculating rules. To solve this problem,this paper formulates a novel fuzzy mathematical model based on the process network graph and proposes a MultiSwarm Collaborative Optimization Algorithm (MSCOA) with an integrated encoding method to improve the optimization. Different swarms evolve in various directions and collaborate in a certain number of iterations. Moreover,the critical path searching method is introduced according to the triangular fuzzy number,allowing for the calculation of rules to enhance the local searching ability of MSCOA. The numerical experiments extended from the well-known Kim benchmark are conducted to test the performance of the proposed MSCOA. Compared with other competitive algorithms,the results obtained by MSCOA show significant advantages,thus proving its effectiveness in solving the FIPPS problem.

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.

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.

Novel modular quasi-zero stiffness vibration isolator with high linearity and integrated fluid damping

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

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.

Concurrent Two-Scale Topology Optimization of Thermoelastic Structures Using a M-VCUT Level Set Based Model of Microstructures

By analyzing the results of compliance minimization of thermoelastic structures,we observed that microstructures play an important role in this optimization problem.Then,we propose to use a multiple variable cutting(M-VCUT)level set-based model of microstructures to solve the concurrent two-scale topology optimization of thermoelastic structures.A microstructure is obtained by combining multiple virtual microstructures that are derived respectively from multiple microstructure prototypes,thus giving more diversity of microstructure and more flexibility in design optimization.The effective mechanical properties of microstructures are computed in an off-line phase by using the homogenization method,and then a mapping relationship between the design variables and the effective properties is established,which gives a data-driven model of microstructure.In the online phase,the data-driven model is used in the finite element analysis to improve the computational efficiency.The compliance minimization problem is considered,and the results of numerical examples prove that the proposed method is effective.