Aircraft assembly is characterized by stringent precedence constraints,limited resource availability,spatial restrictions,and a high degree of manual intervention.These factors lead to considerable variability in oper...Aircraft assembly is characterized by stringent precedence constraints,limited resource availability,spatial restrictions,and a high degree of manual intervention.These factors lead to considerable variability in operator workloads and significantly increase the complexity of scheduling.To address this challenge,this study investigates the Aircraft Pulsating Assembly Line Scheduling Problem(APALSP)under skilled operator allocation,with the objective of minimizing assembly completion time.A mathematical model considering skilled operator allocation is developed,and a Q-Learning improved Particle Swarm Optimization algorithm(QLPSO)is proposed.In the algorithm design,a reverse scheduling strategy is adopted to effectively manage large-scale precedence constraints.Moreover,a reverse sequence encoding method is introduced to generate operation sequences,while a time decoding mechanism is employed to determine completion times.The problem is further reformulated as a Markov Decision Process(MDP)with explicitly defined state and action spaces.Within QLPSO,the Q-learning mechanism adaptively adjusts inertia weights and learning factors,thereby achieving a balance between exploration capability and convergence performance.To validate the effectiveness of the proposed approach,extensive computational experiments are conducted on benchmark instances of different scales,including small,medium,large,and ultra-large cases.The results demonstrate that QLPSO consistently delivers stable and high-quality solutions across all scenarios.In ultra-large-scale instances,it improves the best solution by 25.2%compared with the Genetic Algorithm(GA)and enhances the average solution by 16.9%over the Q-learning algorithm,showing clear advantages over the comparative methods.These findings not only confirm the effectiveness of the proposed algorithm but also provide valuable theoretical references and practical guidance for the intelligent scheduling optimization of aircraft pulsating assembly lines.展开更多
Acoustic-vortex(AV)tweezers ensure stable particle trapping at a zero-pressure center,while particle assembly between two vortex cores is still prevented by the high-potential barrier.Although a one-dimensional low-pr...Acoustic-vortex(AV)tweezers ensure stable particle trapping at a zero-pressure center,while particle assembly between two vortex cores is still prevented by the high-potential barrier.Although a one-dimensional low-pressure attractive path of particle assembly can be constructed by the interference between two independent cylindrical Bessel beams,it remains challenging to create two-dimensional(2D)neighboring vortexes using a source array in practical applications.In this paper,a three-step phase-reversal strategy of 2D particle assembly based on the synchronized evolution of a centrosymmetric array of M off-axis acoustic vortexes(OA-AVs)with a preset radial offset is proposed based on a ring array of planar sources.By introducing initial vortex phase differences of-2π/M and+2π/M to the vortex array,low-pressure patterns of an M-sided regular polygon and M-branched star are formed by connecting the vortex cores and the field center before and after the tangent state of adjacent OA-AVs.Center-oriented particle assembly is finally realized by a central AV constructed by coincident in-phase OA-AVs.The capability of particle manipulation in the lateral and radial directions is demonstrated by low-pressure patterns with acoustic radiation forces pointing to the field center during a synchronized central approach.The field evolution is certified by experimental field measurements for OA-AVs with different vo rtex numbers,initial vortex phase differences,and radial offsets using a ring array of 16 planar sources.The feasibility of particle assembly in two dimensions is also verified by the accurate manipulation of four particles using the low-pressure patterns of a four-sided polygon,a four-branched star,and a central AV in experiments.The three-step strategy paves a new way for 2D particle assembly based on the synchronize d evolution of centrosymmetric OA-AVs using a simplified single-sided source array,exhibiting excellent potential for the precise navigation and manipulation of cells and particles in biomedical applications.展开更多
The optically levitated mechanical system in vacuum is a powerful platform in physics.It has been displaying more extensive application prospects.This paper presents an experimental study of optical levitation,identif...The optically levitated mechanical system in vacuum is a powerful platform in physics.It has been displaying more extensive application prospects.This paper presents an experimental study of optical levitation,identification,motion measurement,and assembly of two-species photoluminescence nanoparticles.A laser trapping array simultaneously levitates nitrogen-vacancy(NV)nanodiamonds and Yb^(3+)/Er^(3+):NaYF_(4)nanoparticles.The species of each nanoparticle can be individually identified by measuring the photoluminescence spectrum.We choose the single NV nanodiamond and Yb^(3+)/Er^(3+):NaYF_(4)nanoparticle and assemble them into a Janus composite nanoparticle,which integrates the merits of the two components.This work demonstrates the potential advantages of a hybrid optically levitated system.It provides a practicable scheme for the study of macroscopic quantum phenomena and precision measurement,thanks to the spin manipulation or spin-mechanical coupling of an NV diamond and by simultaneously implementing laser refrigeration to the Yb^(3+)/Er^(3+):NaYF_(4)nanoparticle in an optically levitated composite nanoparticle.展开更多
Microorganisms can colonize the surface of microplastics(MPs)to form a distinctive microbiome,known as a“plastisphere”which is regarded as an anthropogenic niche for microbial growth.However,bacterial community asse...Microorganisms can colonize the surface of microplastics(MPs)to form a distinctive microbiome,known as a“plastisphere”which is regarded as an anthropogenic niche for microbial growth.However,bacterial community assembly in virgin and aging MP plastispheres across different habitats is poorly understood.This study aims to assess the variations in bacterial community assembly across different niches and habitats with an in situ ex-periment,in which constructed forest wetland(FW),natural lake wetland(LW),and lotus pond wetland(LP)were habitats,and plastispheres of virgin and aging low-density polyethylene(LDPE)MPs,as well as surround-ing wetland soils were niches.Significant niche-related differences in bacterial communities were observed,with lower diversity and enrichment of potential plastic-degrading bacteria in the plastisphere than in the soil bacterial communities.Furthermore,habitat-related differences exerted a more pronounced influence on the beta-diversity patterns of the bacterial communities.The linear regression analyses indicated that the local species pool con-tributed more to bacterial community assembly in the LW wetland,whereas the relative abundance of species was the primary factor in the LP wetland.The null model analysis indicated that plastisphere bacterial communi-ties were predominantly driven by the stochastic process,with a more deterministic assembly observed in the LP wetland and soil bacterial communities.Additionally,the primary ecological process shaping plastisphere com-munities shifted from drift in the virgin LDPE to homogenising dispersal in the aging LDPE.This study provides new insights into the fate and ecological impacts of MPs in wetlands,thereby facilitating the effective regulations of plastic pollution.展开更多
Modern manufacturing processes have become more reliant on automation because of the accelerated transition from Industry 3.0 to Industry 4.0.Manual inspection of products on assembly lines remains inefficient,prone t...Modern manufacturing processes have become more reliant on automation because of the accelerated transition from Industry 3.0 to Industry 4.0.Manual inspection of products on assembly lines remains inefficient,prone to errors and lacks consistency,emphasizing the need for a reliable and automated inspection system.Leveraging both object detection and image segmentation approaches,this research proposes a vision-based solution for the detection of various kinds of tools in the toolkit using deep learning(DL)models.Two Intel RealSense D455f depth cameras were arranged in a top down configuration to capture both RGB and depth images of the toolkits.After applying multiple constraints and enhancing them through preprocessing and augmentation,a dataset consisting of 3300 annotated RGB-D photos was generated.Several DL models were selected through a comprehensive assessment of mean Average Precision(mAP),precision-recall equilibrium,inference latency(target≥30 FPS),and computational burden,resulting in a preference for YOLO and Region-based Convolutional Neural Networks(R-CNN)variants over ViT-based models due to the latter’s increased latency and resource requirements.YOLOV5,YOLOV8,YOLOV11,Faster R-CNN,and Mask R-CNN were trained on the annotated dataset and evaluated using key performance metrics(Recall,Accuracy,F1-score,and Precision).YOLOV11 demonstrated balanced excellence with 93.0%precision,89.9%recall,and a 90.6%F1-score in object detection,as well as 96.9%precision,95.3%recall,and a 96.5%F1-score in instance segmentation with an average inference time of 25 ms per frame(≈40 FPS),demonstrating real-time performance.Leveraging these results,a YOLOV11-based windows application was successfully deployed in a real-time assembly line environment,where it accurately processed live video streams to detect and segment tools within toolkits,demonstrating its practical effectiveness in industrial automation.The application is capable of precisely measuring socket dimensions by utilising edge detection techniques on YOLOv11 segmentation masks,in addition to detection and segmentation.This makes it possible to do specification-level quality control right on the assembly line,which improves the ability to examine things in real time.The implementation is a big step forward for intelligent manufacturing in the Industry 4.0 paradigm.It provides a scalable,efficient,and accurate way to do automated inspection and dimensional verification activities.展开更多
Transformer-based models have significantly advanced binary code similarity detection(BCSD)by leveraging their semantic encoding capabilities for efficient function matching across diverse compilation settings.Althoug...Transformer-based models have significantly advanced binary code similarity detection(BCSD)by leveraging their semantic encoding capabilities for efficient function matching across diverse compilation settings.Although adversarial examples can strategically undermine the accuracy of BCSD models and protect critical code,existing techniques predominantly depend on inserting artificial instructions,which incur high computational costs and offer limited diversity of perturbations.To address these limitations,we propose AIMA,a novel gradient-guided assembly instruction relocation method.Our method decouples the detection model into tokenization,embedding,and encoding layers to enable efficient gradient computation.Since token IDs of instructions are discrete and nondifferentiable,we compute gradients in the continuous embedding space to evaluate the influence of each token.The most critical tokens are identified by calculating the L2 norm of their embedding gradients.We then establish a mapping between instructions and their corresponding tokens to aggregate token-level importance into instructionlevel significance.To maximize adversarial impact,a sliding window algorithm selects the most influential contiguous segments for relocation,ensuring optimal perturbation with minimal length.This approach efficiently locates critical code regions without expensive search operations.The selected segments are relocated outside their original function boundaries via a jump mechanism,which preserves runtime control flow and functionality while introducing“deletion”effects in the static instruction sequence.Extensive experiments show that AIMA reduces similarity scores by up to 35.8%in state-of-the-art BCSD models.When incorporated into training data,it also enhances model robustness,achieving a 5.9%improvement in AUROC.展开更多
Directional three-dimensional carbon-based foams are emerging as highly attractive candidates for promising electromagnetic wave absorbing materials(EWAMs)thanks to their unique architecture,but their construction usu...Directional three-dimensional carbon-based foams are emerging as highly attractive candidates for promising electromagnetic wave absorbing materials(EWAMs)thanks to their unique architecture,but their construction usually involves complex procedures and extremely depends on unidirectional freezing technique.Herein,we propose a groundbreaking approach that leverages the assemblies of salting-out protein induced by ammonium metatungstate(AM)as the precursor,and then acquire directional three-dimensional carbon-based foams through simple pyrolysis.The electrostatic interaction between AM and protein ensures well dispersion of WC_(1−x)nanoparticles on carbon frameworks.The content of WC_(1−x)nanoparticles can be rationally regulated by AM dosage,and it also affects the electromagnetic(EM)properties of final carbon-based foams.The optimized foam exhibits exceptional EM absorption performance,achieving a remarkable minimum reflection loss of−72.0 dB and an effective absorption bandwidth of 6.3 GHz when EM wave propagates parallel to the directional pores.Such performance benefits from the synergistic effects of macroporous architecture and compositional design.Although there is a directional dependence of EM absorption,radar stealth simulation demonstrates that these foams can still promise considerable reduction in radar cross section with the change of incident angle.Moreover,COMSOL simulation further identifies their good performance in preventing EM interference among different electronic components.展开更多
In the process of thin-wall parts assembly for an antenna,the parts assembly deformation deviation is occurring due to the riveting assembly.In view of the riveting assembly deformation problems,it can be analyzed thr...In the process of thin-wall parts assembly for an antenna,the parts assembly deformation deviation is occurring due to the riveting assembly.In view of the riveting assembly deformation problems,it can be analyzed through transient and static simulation.In this work,the theoretical deformation model for riveting assembly is established with round head rivet.The simulation analysis for riveting deformation is carried out with the riveting assembly piece including four rivets,which comparing with the measuring points experiment results of riveting test piece through dealing with the experimental data using the point coordinate transform method and the space line fitting method.Simultaneously,the deformation deviation of the overall thin-wall parts assembly structure is analyzed through finite element simulation;and its results are verified by the measuring experiment for riveting assembly with the deformation deviation of some key points on the thin-wall parts.Through the comparison analysis,it is shown that the simulation results agree well with the experimental results,which proves the correctness and effectiveness of the theoretical analysis,simulation results and the given experiment data processing method.Through the study on the riveting assembly for thin-wall parts,it will provide a theoretical foundation for improving thin-wall parts assembly quality of large antenna in future.展开更多
Location layout of aircraft assembly is an important factor affecting product quality.Most of the existing re-searches use the combination of finite element analysis and intelligent algorithm to optimize the location ...Location layout of aircraft assembly is an important factor affecting product quality.Most of the existing re-searches use the combination of finite element analysis and intelligent algorithm to optimize the location layout,which are limited by numerical simulation accuracy and the selection and improvement of intelligent algorithms.At present,the analysis and decision-making technology based on field data is gradually applied in aircraft manufacturing.Based on the perception data of intelligent assembly unit of aircraft parts,a regression model of multi-input and multioutput support vector machine with Gauss kernel function as radial basis function is established,and the hyperparameters of the model are optimized by hybrid particle swarm optimization genetic algorithm(PSO-GA).GA-MSVR,PSO-MSVR and PSOGA-MSVR model are constructed respectively,and their results show that PSOGA-MSVR model has the best performance.Finally,the design of the aircraft wing location layout is taken as an example to verify the effectiveness of the method.展开更多
By taking advantage of recent advances in aptamer biology and nanotechnology, we developed a general approach for the design and fabrication of bioresponsive controlled delivery systems. It utilized the structure-swit...By taking advantage of recent advances in aptamer biology and nanotechnology, we developed a general approach for the design and fabrication of bioresponsive controlled delivery systems. It utilized the structure-switchable aptamer directed assembly and disassembly of gold nanoparticles from mesoporous silica supports, which enables the control of cargo release from the inside of the mesoporous nanoparticles specifically in the presence of target molecule.展开更多
Iridium nanoparticles (IrNPs) and submicroparticles (IrSMPs) with different shapes were synthesized and assembled on indium thin oxide (ITO) and Si substrates using two different methods: direct surface growth and dro...Iridium nanoparticles (IrNPs) and submicroparticles (IrSMPs) with different shapes were synthesized and assembled on indium thin oxide (ITO) and Si substrates using two different methods: direct surface growth and drop-drying assembly. The obtained IrNPs and IrSMPs were characterized using scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS). The IrSMPs (or IrNPs) with disc-like shape and irregular shapes were obtained on ITO substrate by direct surface growth method using polyvinylpyrrolidone (PVP) and sodium citrate as different stabilizers, respectively. The reaction time and the injection temperature of reducing agent are found to have great effect on the size and morphology of the surface-grown Ir particles. The disc-like, ellipsoidal, and spherical IrSMPs (or IrNPs) were also synthesized in homogeneous solution in the presence of H3BO3 and Na2B4O7 as assistant-stabilizer. These IrNPs and IrSMPs were used as building blocks to construct nanoparticle assemblies by using a simple drop-drying method. Uniform IrNP and IrSMP assemblies were successfully prepared on Si and ITO substrates, indicating that the drop-drying method is efficient for the preparation of not only nanoparticle assemblies but also submicroparticle assemblies.展开更多
In the present study,a facility,i.e.,a mechanical deflection system (MDS),was established and applied to assess the long-term reliability of the solder joints in plastic ball grid array (BGA) assembly.It was found tha...In the present study,a facility,i.e.,a mechanical deflection system (MDS),was established and applied to assess the long-term reliability of the solder joints in plastic ball grid array (BGA) assembly.It was found that the MDS not only quickly assesses the long-term reliability of solder joints within days,but can also mimic similar failure mechanisms in accelerated thermal cycling (ATC) tests. Based on the MDS and ATC reliability experiments,the acceleration factors (AF) were obtained for different reliability testing conditions.Furthermore,by using the creep constitutive relation and fatigue life model developed in part I,a numerical approach was established for the purpose of virtual life prediction of solder joints. The simulation results were found to be in good agreement with the test results from the MDS.As a result,a new reliability assessment methodology was established as an alternative to ATC for the evaluation of long-term reliability of plastic BGA assembly.展开更多
In order to analyze the welding thermal characteristics problem,the multiscale finite element(FE)model of T-shape thin-wall assembly structure for different thicknesses and the heat source model are established to emp...In order to analyze the welding thermal characteristics problem,the multiscale finite element(FE)model of T-shape thin-wall assembly structure for different thicknesses and the heat source model are established to emphatically study their welding temperature distributions under different conditions.Simultaneously,different welding technology parameters and welding directions are taken into account,and the fillet weld for different welding parameters is employed on the thin-wall parts.Through comparison analysis,the results show that different welding directions,welding thicknesses and welding heat source parameters have a certain impact on the temperature distribution.Meanwhile,for the thin-wall assembly structure of the same thickness,when the heat source is moving,the greater the moving speed,the smaller the heating area,and the highest temperature will decrease.Therefore,the welding temperature field distribution can be altered by adjusting welding parameters,heat source parameters,welding thickness and welding direction,which is conducive to reducing welding deformation and choosing an appropriate and optimal welding thickness of thin-wall parts and relative welding process parameters,thus improving thin-wall welding structure assembly precision in the actual large-size welding structure assembly process in future.展开更多
The finite element(FE)-based simulation of welding characteristics was carried out to explore the relationship among welding assembly properties for the parallel T-shaped thin-walled parts of an antenna structure.The ...The finite element(FE)-based simulation of welding characteristics was carried out to explore the relationship among welding assembly properties for the parallel T-shaped thin-walled parts of an antenna structure.The effects of welding direction,clamping,fixture release time,fixed constraints,and welding sequences on these properties were analyzed,and the mapping relationship among welding characteristics was thoroughly examined.Different machine learning algorithms,including the generalized regression neural network(GRNN),wavelet neural network(WNN),and fuzzy neural network(FNN),are used to predict the multiple welding properties of thin-walled parts to mirror their variation trend and verify the correctness of the mapping relationship.Compared with those from GRNN and WNN,the maximum mean relative errors for the predicted values of deformation,temperature,and residual stress with FNN were less than 4.8%,1.4%,and 4.4%,respectively.These results indicate that FNN generated the best predicted welding characteristics.Analysis under various welding conditions also shows a mapping relationship among welding deformation,temperature,and residual stress over a period of time.This finding further provides a paramount basis for the control of welding assembly errors of an antenna structure in the future.展开更多
Polypropylene（PP） meltblown fibers were coated with titanium dioxide（Ti O2） nanoparticles using layer-by-layer（Lb L） deposition technique. The fibers were first modified with 3layers of poly（4-styrenesulfonic a...Polypropylene（PP） meltblown fibers were coated with titanium dioxide（Ti O2） nanoparticles using layer-by-layer（Lb L） deposition technique. The fibers were first modified with 3layers of poly（4-styrenesulfonic acid）（PSS） and poly（diallyl-dimethylammonium chloride）（PDADMAC） to improve the anchoring of the Ti O2 nanoparticle clusters. PDADMAC, which is positively charged, was then used as counter polyelectrolyte in tandem with anionic Ti O2 nanoparticles to construct Ti O2/PDADMAC bilayer in the Lb L fashion. The number of deposited Ti O2/PDADMAC layers was varied from 1 to 7 bilayer, and could be used to adjust Ti O2 loading. The Lb L technique showed higher Ti O2 loading efficiency than the impregnation approach. The modified fibers were tested for their photocatalytic activity against a model dye, Methylene Blue（MB）. Results showed that the Ti O2 modified fibers exhibited excellent photocatalytic activity efficiency similar to that of Ti O2 powder dispersed in solution. The deposition of Ti O23 bilayer on the PP substrate was sufficient to produce nanocomposite fibers that could bleach the MB solution in less than 4 hr.Ti O2-Lb L constructions also preserved Ti O2 adhesion on substrate surface after 1 cycle of photocatalytic test. Successive photocatalytic test showed decline in MB reduction rate with loss of Ti O2 particles from the substrate outer surface. However, even in the third cycle, the Ti O2 modified fibers are still moderately effective as it could remove more than 95% of MB after 8 hr of treatment.展开更多
Due to the excellent self-centering and load-carrying capability,curvic couplings have been widely used in advanced aero-engine rotors.However,curvic tooth surface errors lead to poor assembly precision.Traditional ph...Due to the excellent self-centering and load-carrying capability,curvic couplings have been widely used in advanced aero-engine rotors.However,curvic tooth surface errors lead to poor assembly precision.Traditional physical-master-gauge-based indirect tooth surface error measurement and circumferential assembly angle optimization methods have the disadvantages of high cost and weak generality.The unknown tooth surface fitting mechanism is a big barrier to assembly precision prediction and improvement.Therefore,this work puts forward a data-driven assembly simulation and optimization approach for aero-engine rotors connected by curvic couplings.The origin of curvic tooth surface error is deeply investigated.Using 5-axis sweep scan method,a large amount of high-precision curvic tooth surface data are acquired efficiently.Based on geometric models of parts,the fitting mechanism of curvic couplings is uncovered for assembly precision simulation and prediction.A circumferential assembly angle optimization model is developed to decrease axial and radial assembly runouts.Experimental results show that the assembly precision can be predicted accurately and improved dramatically.By uncovering the essential principle of the assembly precision formation and proposing circumferential assembly angle optimization model,this work is meaningful for assembly quality,efficiency and economy improvement of multistage aero-engine rotors connected by curvic couplings.展开更多
There are lots of researches on fixture layout optimization for large thin-walled parts.Current researches focus on the positioning problem,i.e.,optimizing the positions of a constant number of fixtures.However,how to...There are lots of researches on fixture layout optimization for large thin-walled parts.Current researches focus on the positioning problem,i.e.,optimizing the positions of a constant number of fixtures.However,how to determine the number of fixtures is ignored.In most cases,the number of fixtures located on large thin-walled parts is determined based on engineering experience,which leads to huge fixture number and extra waste.Therefore,this paper constructs an optimization model to minimize the number of fixtures.The constraints are set in the optimization model to ensure that the part deformation is within the surface profile tolerance.In addition,the assembly gap between two parts is also controlled.To conduct the optimization,this paper develops an improved particle swarm optimization(IPSO)algorithm by integrating the shrinkage factor and adaptive inertia weight.In the algorithm,particles are encoded according to the fixture position.Each dimension of the particle is assigned to a sub-region by constraining the optional position range of each fixture to improve the optimization efficiency.Finally,a case study on ship curved panel assembly is provided to prove that our method can optimize the number of fixtures while meeting the assembly quality requirements.This research proposes a method to optimize the number of fixtures,which can reduce the number of fixtures and achieve deformation control at the same time.展开更多
The liquid-crystal assembly of semiflexible-coil diblock copolymers with coil or semiflexible homopolymers is studied by dissipative particle dynamics simulation. Phase diagrams of the blends and orientation ordering ...The liquid-crystal assembly of semiflexible-coil diblock copolymers with coil or semiflexible homopolymers is studied by dissipative particle dynamics simulation. Phase diagrams of the blends and orientation ordering parameters among semiflexible blocks are constructed as a function of chain stiffness and homopolymer volume fraction. For semiflexible-coil/coil blends with varying stiffness of semiflexible blocks, we display the rich phase behaviors of the system transited from coil-coil/coil to rod-coil/coil blends. The disorder- lamellae or lamellae-liquid crystalline transition and ＂dry brush＂ phenomenon induced by coil homopolymers are observed. For semiflexible-coil/semiflexible blends, adding semiflexible homopolymers also leads to a disorder-order transition and even a transition between monolayer and bilayer smectic-A phase. The results demonstrate that blending homopolymers into semiflexible copolymers can induce liquid-crystal assembly and even improve the orientation ordering of semiflexible blocks effectively.展开更多
In this contribution,we utilized surface initiated atom transfer radical polymerization(SI-ATRP)to prepare organicinorganic hybrid core/shell silila nanoparticles(NPs),where silia particles acted as cores and polymeri...In this contribution,we utilized surface initiated atom transfer radical polymerization(SI-ATRP)to prepare organicinorganic hybrid core/shell silila nanoparticles(NPs),where silia particles acted as cores and polymeric shells(PAzoMA*)were attached to silica particles via covalent bond.Subsequently,chiroptical switch was sccessfully constructed on silica NPs surface taking advantage of supramolecular chiral self-assembly of the grafted side chain Azo-containing polymer(PAzoMA*).We found that the supramolecular chirality was highly dependent on the molecular weight of grafted PAzoMA*.Meanwhile,the supramolecular chirality could be regulated using 365 nm UV light iradiation and heating cooling treatment,and a reversible supramolecular chiroptical switch could be repeated for over five cycles on silia NPs surface.Moreover,when heated above the glass transition temperature(T_(g))of PAzoMA",the organic-inorganic hybrid nanoparticles(SiO_(2)@PAzoMA*NPs)still exhibited intense DRCD signals.Interestingly,the supramolecular chirality could be retained in solid film for more than 3 months.To conclude,we have prepared an organic inorganic hybrid core/shell chiral slia nanomaterial with dynamic reversible chirality,thermal stability and chiral storage functions,providing potential applications in dynamic asymmetric catalysis,chiral separation and so on.展开更多
A method of 3-D measuring fixture automatic assembly for auto-body part is presented. Locating constraint mapping technique and assembly rule-based reasoning are applied. Calculating algorithm of the position and pose...A method of 3-D measuring fixture automatic assembly for auto-body part is presented. Locating constraint mapping technique and assembly rule-based reasoning are applied. Calculating algorithm of the position and pose for the part model, fixture configuration and fixture elements in virtual auto-body assembly space are given. Transforming fixture element from itself coordinate system space to assembly space with homogeneous transformation matrix is realized. Based on the second development technique of unigraphics（UG）, the automated assembly is implemented with application program interface （API） function. Lastly the automated assembly of measuring fixture for rear longeron as a case is implemented.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.52475543)Natural Science Foundation of Henan(Grant No.252300421101)+1 种基金Henan Province University Science and Technology Innovation Talent Support Plan(Grant No.24HASTIT048)Science and Technology Innovation Team Project of Zhengzhou University of Light Industry(Grant No.23XNKJTD0101).
文摘Aircraft assembly is characterized by stringent precedence constraints,limited resource availability,spatial restrictions,and a high degree of manual intervention.These factors lead to considerable variability in operator workloads and significantly increase the complexity of scheduling.To address this challenge,this study investigates the Aircraft Pulsating Assembly Line Scheduling Problem(APALSP)under skilled operator allocation,with the objective of minimizing assembly completion time.A mathematical model considering skilled operator allocation is developed,and a Q-Learning improved Particle Swarm Optimization algorithm(QLPSO)is proposed.In the algorithm design,a reverse scheduling strategy is adopted to effectively manage large-scale precedence constraints.Moreover,a reverse sequence encoding method is introduced to generate operation sequences,while a time decoding mechanism is employed to determine completion times.The problem is further reformulated as a Markov Decision Process(MDP)with explicitly defined state and action spaces.Within QLPSO,the Q-learning mechanism adaptively adjusts inertia weights and learning factors,thereby achieving a balance between exploration capability and convergence performance.To validate the effectiveness of the proposed approach,extensive computational experiments are conducted on benchmark instances of different scales,including small,medium,large,and ultra-large cases.The results demonstrate that QLPSO consistently delivers stable and high-quality solutions across all scenarios.In ultra-large-scale instances,it improves the best solution by 25.2%compared with the Genetic Algorithm(GA)and enhances the average solution by 16.9%over the Q-learning algorithm,showing clear advantages over the comparative methods.These findings not only confirm the effectiveness of the proposed algorithm but also provide valuable theoretical references and practical guidance for the intelligent scheduling optimization of aircraft pulsating assembly lines.
基金funded by the National Nature Science Foundation of China(11934009,12174198,and 12227808)the Natural Science Foundation of Jiangsu Province,China(BE2022814)+2 种基金the Universal Technology for Primary and Secondary Schoolsthe National Research Institute for Teaching Materialsthe Qing Lan Project of Jiangsu Province,China。
文摘Acoustic-vortex(AV)tweezers ensure stable particle trapping at a zero-pressure center,while particle assembly between two vortex cores is still prevented by the high-potential barrier.Although a one-dimensional low-pressure attractive path of particle assembly can be constructed by the interference between two independent cylindrical Bessel beams,it remains challenging to create two-dimensional(2D)neighboring vortexes using a source array in practical applications.In this paper,a three-step phase-reversal strategy of 2D particle assembly based on the synchronized evolution of a centrosymmetric array of M off-axis acoustic vortexes(OA-AVs)with a preset radial offset is proposed based on a ring array of planar sources.By introducing initial vortex phase differences of-2π/M and+2π/M to the vortex array,low-pressure patterns of an M-sided regular polygon and M-branched star are formed by connecting the vortex cores and the field center before and after the tangent state of adjacent OA-AVs.Center-oriented particle assembly is finally realized by a central AV constructed by coincident in-phase OA-AVs.The capability of particle manipulation in the lateral and radial directions is demonstrated by low-pressure patterns with acoustic radiation forces pointing to the field center during a synchronized central approach.The field evolution is certified by experimental field measurements for OA-AVs with different vo rtex numbers,initial vortex phase differences,and radial offsets using a ring array of 16 planar sources.The feasibility of particle assembly in two dimensions is also verified by the accurate manipulation of four particles using the low-pressure patterns of a four-sided polygon,a four-branched star,and a central AV in experiments.The three-step strategy paves a new way for 2D particle assembly based on the synchronize d evolution of centrosymmetric OA-AVs using a simplified single-sided source array,exhibiting excellent potential for the precise navigation and manipulation of cells and particles in biomedical applications.
基金supported in part by the National Natural Science Foundation of China(Grant Nos.61975101,11234008,11361161002,and 6157-1276)。
文摘The optically levitated mechanical system in vacuum is a powerful platform in physics.It has been displaying more extensive application prospects.This paper presents an experimental study of optical levitation,identification,motion measurement,and assembly of two-species photoluminescence nanoparticles.A laser trapping array simultaneously levitates nitrogen-vacancy(NV)nanodiamonds and Yb^(3+)/Er^(3+):NaYF_(4)nanoparticles.The species of each nanoparticle can be individually identified by measuring the photoluminescence spectrum.We choose the single NV nanodiamond and Yb^(3+)/Er^(3+):NaYF_(4)nanoparticle and assemble them into a Janus composite nanoparticle,which integrates the merits of the two components.This work demonstrates the potential advantages of a hybrid optically levitated system.It provides a practicable scheme for the study of macroscopic quantum phenomena and precision measurement,thanks to the spin manipulation or spin-mechanical coupling of an NV diamond and by simultaneously implementing laser refrigeration to the Yb^(3+)/Er^(3+):NaYF_(4)nanoparticle in an optically levitated composite nanoparticle.
基金supported by Shanghai Municipal Natural Science Foundation,China(No.21ZR1446800)the National Natural Science Foundation of China(No.41877425)the Fundamental Research Funds for the Central Universities(No.226-2024-00052)。
文摘Microorganisms can colonize the surface of microplastics(MPs)to form a distinctive microbiome,known as a“plastisphere”which is regarded as an anthropogenic niche for microbial growth.However,bacterial community assembly in virgin and aging MP plastispheres across different habitats is poorly understood.This study aims to assess the variations in bacterial community assembly across different niches and habitats with an in situ ex-periment,in which constructed forest wetland(FW),natural lake wetland(LW),and lotus pond wetland(LP)were habitats,and plastispheres of virgin and aging low-density polyethylene(LDPE)MPs,as well as surround-ing wetland soils were niches.Significant niche-related differences in bacterial communities were observed,with lower diversity and enrichment of potential plastic-degrading bacteria in the plastisphere than in the soil bacterial communities.Furthermore,habitat-related differences exerted a more pronounced influence on the beta-diversity patterns of the bacterial communities.The linear regression analyses indicated that the local species pool con-tributed more to bacterial community assembly in the LW wetland,whereas the relative abundance of species was the primary factor in the LP wetland.The null model analysis indicated that plastisphere bacterial communi-ties were predominantly driven by the stochastic process,with a more deterministic assembly observed in the LP wetland and soil bacterial communities.Additionally,the primary ecological process shaping plastisphere com-munities shifted from drift in the virgin LDPE to homogenising dispersal in the aging LDPE.This study provides new insights into the fate and ecological impacts of MPs in wetlands,thereby facilitating the effective regulations of plastic pollution.
基金National Science and Technology Council,the Republic of China,under grants NSTC 113-2221-E-194-011-MY3 and Research Center on Artificial Intelligence and Sustainability,National Chung Cheng University under the research project grant titled“Generative Digital Twin System Design for Sustainable Smart City Development in Taiwan.
文摘Modern manufacturing processes have become more reliant on automation because of the accelerated transition from Industry 3.0 to Industry 4.0.Manual inspection of products on assembly lines remains inefficient,prone to errors and lacks consistency,emphasizing the need for a reliable and automated inspection system.Leveraging both object detection and image segmentation approaches,this research proposes a vision-based solution for the detection of various kinds of tools in the toolkit using deep learning(DL)models.Two Intel RealSense D455f depth cameras were arranged in a top down configuration to capture both RGB and depth images of the toolkits.After applying multiple constraints and enhancing them through preprocessing and augmentation,a dataset consisting of 3300 annotated RGB-D photos was generated.Several DL models were selected through a comprehensive assessment of mean Average Precision(mAP),precision-recall equilibrium,inference latency(target≥30 FPS),and computational burden,resulting in a preference for YOLO and Region-based Convolutional Neural Networks(R-CNN)variants over ViT-based models due to the latter’s increased latency and resource requirements.YOLOV5,YOLOV8,YOLOV11,Faster R-CNN,and Mask R-CNN were trained on the annotated dataset and evaluated using key performance metrics(Recall,Accuracy,F1-score,and Precision).YOLOV11 demonstrated balanced excellence with 93.0%precision,89.9%recall,and a 90.6%F1-score in object detection,as well as 96.9%precision,95.3%recall,and a 96.5%F1-score in instance segmentation with an average inference time of 25 ms per frame(≈40 FPS),demonstrating real-time performance.Leveraging these results,a YOLOV11-based windows application was successfully deployed in a real-time assembly line environment,where it accurately processed live video streams to detect and segment tools within toolkits,demonstrating its practical effectiveness in industrial automation.The application is capable of precisely measuring socket dimensions by utilising edge detection techniques on YOLOv11 segmentation masks,in addition to detection and segmentation.This makes it possible to do specification-level quality control right on the assembly line,which improves the ability to examine things in real time.The implementation is a big step forward for intelligent manufacturing in the Industry 4.0 paradigm.It provides a scalable,efficient,and accurate way to do automated inspection and dimensional verification activities.
基金supported by Key Laboratory of Cyberspace Security,Ministry of Education,China。
文摘Transformer-based models have significantly advanced binary code similarity detection(BCSD)by leveraging their semantic encoding capabilities for efficient function matching across diverse compilation settings.Although adversarial examples can strategically undermine the accuracy of BCSD models and protect critical code,existing techniques predominantly depend on inserting artificial instructions,which incur high computational costs and offer limited diversity of perturbations.To address these limitations,we propose AIMA,a novel gradient-guided assembly instruction relocation method.Our method decouples the detection model into tokenization,embedding,and encoding layers to enable efficient gradient computation.Since token IDs of instructions are discrete and nondifferentiable,we compute gradients in the continuous embedding space to evaluate the influence of each token.The most critical tokens are identified by calculating the L2 norm of their embedding gradients.We then establish a mapping between instructions and their corresponding tokens to aggregate token-level importance into instructionlevel significance.To maximize adversarial impact,a sliding window algorithm selects the most influential contiguous segments for relocation,ensuring optimal perturbation with minimal length.This approach efficiently locates critical code regions without expensive search operations.The selected segments are relocated outside their original function boundaries via a jump mechanism,which preserves runtime control flow and functionality while introducing“deletion”effects in the static instruction sequence.Extensive experiments show that AIMA reduces similarity scores by up to 35.8%in state-of-the-art BCSD models.When incorporated into training data,it also enhances model robustness,achieving a 5.9%improvement in AUROC.
基金financially supported by the National Natural Science Foundation of China(Nos.22475057 and No.52373262).
文摘Directional three-dimensional carbon-based foams are emerging as highly attractive candidates for promising electromagnetic wave absorbing materials(EWAMs)thanks to their unique architecture,but their construction usually involves complex procedures and extremely depends on unidirectional freezing technique.Herein,we propose a groundbreaking approach that leverages the assemblies of salting-out protein induced by ammonium metatungstate(AM)as the precursor,and then acquire directional three-dimensional carbon-based foams through simple pyrolysis.The electrostatic interaction between AM and protein ensures well dispersion of WC_(1−x)nanoparticles on carbon frameworks.The content of WC_(1−x)nanoparticles can be rationally regulated by AM dosage,and it also affects the electromagnetic(EM)properties of final carbon-based foams.The optimized foam exhibits exceptional EM absorption performance,achieving a remarkable minimum reflection loss of−72.0 dB and an effective absorption bandwidth of 6.3 GHz when EM wave propagates parallel to the directional pores.Such performance benefits from the synergistic effects of macroporous architecture and compositional design.Although there is a directional dependence of EM absorption,radar stealth simulation demonstrates that these foams can still promise considerable reduction in radar cross section with the change of incident angle.Moreover,COMSOL simulation further identifies their good performance in preventing EM interference among different electronic components.
基金Project(51675100)supported by the National Natural Science Foundation of ChinaProject(2016ZX04004008)supported by the National Numerical Control Equipment Major Project of ChinaProject(6902002116)supported by the Foundation of Certain Ministry of China
文摘In the process of thin-wall parts assembly for an antenna,the parts assembly deformation deviation is occurring due to the riveting assembly.In view of the riveting assembly deformation problems,it can be analyzed through transient and static simulation.In this work,the theoretical deformation model for riveting assembly is established with round head rivet.The simulation analysis for riveting deformation is carried out with the riveting assembly piece including four rivets,which comparing with the measuring points experiment results of riveting test piece through dealing with the experimental data using the point coordinate transform method and the space line fitting method.Simultaneously,the deformation deviation of the overall thin-wall parts assembly structure is analyzed through finite element simulation;and its results are verified by the measuring experiment for riveting assembly with the deformation deviation of some key points on the thin-wall parts.Through the comparison analysis,it is shown that the simulation results agree well with the experimental results,which proves the correctness and effectiveness of the theoretical analysis,simulation results and the given experiment data processing method.Through the study on the riveting assembly for thin-wall parts,it will provide a theoretical foundation for improving thin-wall parts assembly quality of large antenna in future.
基金supported by the Equipment Pre-research Project of China (No. 41423010202)
文摘Location layout of aircraft assembly is an important factor affecting product quality.Most of the existing re-searches use the combination of finite element analysis and intelligent algorithm to optimize the location layout,which are limited by numerical simulation accuracy and the selection and improvement of intelligent algorithms.At present,the analysis and decision-making technology based on field data is gradually applied in aircraft manufacturing.Based on the perception data of intelligent assembly unit of aircraft parts,a regression model of multi-input and multioutput support vector machine with Gauss kernel function as radial basis function is established,and the hyperparameters of the model are optimized by hybrid particle swarm optimization genetic algorithm(PSO-GA).GA-MSVR,PSO-MSVR and PSOGA-MSVR model are constructed respectively,and their results show that PSOGA-MSVR model has the best performance.Finally,the design of the aircraft wing location layout is taken as an example to verify the effectiveness of the method.
基金supported by the Inner Mongolia Power(Group) Co., Ltd.,Technology Project (No. 2016-20)
文摘By taking advantage of recent advances in aptamer biology and nanotechnology, we developed a general approach for the design and fabrication of bioresponsive controlled delivery systems. It utilized the structure-switchable aptamer directed assembly and disassembly of gold nanoparticles from mesoporous silica supports, which enables the control of cargo release from the inside of the mesoporous nanoparticles specifically in the presence of target molecule.
基金financially supported by the National Natural Science Foundation of China (Nos.20973020 and21173016)Doctoral Fund of Ministry of Education of China (No. 20101102110002)+1 种基金Program for New Century Excellent Talents in University (No.NCET-08-0034)Program for Changjiang Scholars and Innovative Research Team in University (No.IRT0805)
文摘Iridium nanoparticles (IrNPs) and submicroparticles (IrSMPs) with different shapes were synthesized and assembled on indium thin oxide (ITO) and Si substrates using two different methods: direct surface growth and drop-drying assembly. The obtained IrNPs and IrSMPs were characterized using scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS). The IrSMPs (or IrNPs) with disc-like shape and irregular shapes were obtained on ITO substrate by direct surface growth method using polyvinylpyrrolidone (PVP) and sodium citrate as different stabilizers, respectively. The reaction time and the injection temperature of reducing agent are found to have great effect on the size and morphology of the surface-grown Ir particles. The disc-like, ellipsoidal, and spherical IrSMPs (or IrNPs) were also synthesized in homogeneous solution in the presence of H3BO3 and Na2B4O7 as assistant-stabilizer. These IrNPs and IrSMPs were used as building blocks to construct nanoparticle assemblies by using a simple drop-drying method. Uniform IrNP and IrSMP assemblies were successfully prepared on Si and ITO substrates, indicating that the drop-drying method is efficient for the preparation of not only nanoparticle assemblies but also submicroparticle assemblies.
基金The project supported by the National Natural Science Foundation of China (59705008)
文摘In the present study,a facility,i.e.,a mechanical deflection system (MDS),was established and applied to assess the long-term reliability of the solder joints in plastic ball grid array (BGA) assembly.It was found that the MDS not only quickly assesses the long-term reliability of solder joints within days,but can also mimic similar failure mechanisms in accelerated thermal cycling (ATC) tests. Based on the MDS and ATC reliability experiments,the acceleration factors (AF) were obtained for different reliability testing conditions.Furthermore,by using the creep constitutive relation and fatigue life model developed in part I,a numerical approach was established for the purpose of virtual life prediction of solder joints. The simulation results were found to be in good agreement with the test results from the MDS.As a result,a new reliability assessment methodology was established as an alternative to ATC for the evaluation of long-term reliability of plastic BGA assembly.
基金The National Natural Science Foundation of China(No.51675100)the National Numerical Control Equipment Major Project of China(o.2016ZX04004008)
文摘In order to analyze the welding thermal characteristics problem,the multiscale finite element(FE)model of T-shape thin-wall assembly structure for different thicknesses and the heat source model are established to emphatically study their welding temperature distributions under different conditions.Simultaneously,different welding technology parameters and welding directions are taken into account,and the fillet weld for different welding parameters is employed on the thin-wall parts.Through comparison analysis,the results show that different welding directions,welding thicknesses and welding heat source parameters have a certain impact on the temperature distribution.Meanwhile,for the thin-wall assembly structure of the same thickness,when the heat source is moving,the greater the moving speed,the smaller the heating area,and the highest temperature will decrease.Therefore,the welding temperature field distribution can be altered by adjusting welding parameters,heat source parameters,welding thickness and welding direction,which is conducive to reducing welding deformation and choosing an appropriate and optimal welding thickness of thin-wall parts and relative welding process parameters,thus improving thin-wall welding structure assembly precision in the actual large-size welding structure assembly process in future.
基金The Natural Science Foundation of Jiangsu Province,China(No.BK20200470)China Postdoctoral Science Foundation(No.2021M691595)Innovation and Entrepreneurship Plan Talent Program of Jiangsu Province(No.AD99002).
文摘The finite element(FE)-based simulation of welding characteristics was carried out to explore the relationship among welding assembly properties for the parallel T-shaped thin-walled parts of an antenna structure.The effects of welding direction,clamping,fixture release time,fixed constraints,and welding sequences on these properties were analyzed,and the mapping relationship among welding characteristics was thoroughly examined.Different machine learning algorithms,including the generalized regression neural network(GRNN),wavelet neural network(WNN),and fuzzy neural network(FNN),are used to predict the multiple welding properties of thin-walled parts to mirror their variation trend and verify the correctness of the mapping relationship.Compared with those from GRNN and WNN,the maximum mean relative errors for the predicted values of deformation,temperature,and residual stress with FNN were less than 4.8%,1.4%,and 4.4%,respectively.These results indicate that FNN generated the best predicted welding characteristics.Analysis under various welding conditions also shows a mapping relationship among welding deformation,temperature,and residual stress over a period of time.This finding further provides a paramount basis for the control of welding assembly errors of an antenna structure in the future.
基金supported by Rachadapisek Sompote Fund for Postdoctoral Fellowship, Chulalongkorn University, Thailandthe Nanotechnology Center (NANOTEC), NSTDA Ministry of Science and Technology, Thailand, through its program of Center of Excellence Network+1 种基金National Research University Project of CHEthe Rachadapisek Sompote Endowment Fund (No. AM1041A)
文摘Polypropylene（PP） meltblown fibers were coated with titanium dioxide（Ti O2） nanoparticles using layer-by-layer（Lb L） deposition technique. The fibers were first modified with 3layers of poly（4-styrenesulfonic acid）（PSS） and poly（diallyl-dimethylammonium chloride）（PDADMAC） to improve the anchoring of the Ti O2 nanoparticle clusters. PDADMAC, which is positively charged, was then used as counter polyelectrolyte in tandem with anionic Ti O2 nanoparticles to construct Ti O2/PDADMAC bilayer in the Lb L fashion. The number of deposited Ti O2/PDADMAC layers was varied from 1 to 7 bilayer, and could be used to adjust Ti O2 loading. The Lb L technique showed higher Ti O2 loading efficiency than the impregnation approach. The modified fibers were tested for their photocatalytic activity against a model dye, Methylene Blue（MB）. Results showed that the Ti O2 modified fibers exhibited excellent photocatalytic activity efficiency similar to that of Ti O2 powder dispersed in solution. The deposition of Ti O23 bilayer on the PP substrate was sufficient to produce nanocomposite fibers that could bleach the MB solution in less than 4 hr.Ti O2-Lb L constructions also preserved Ti O2 adhesion on substrate surface after 1 cycle of photocatalytic test. Successive photocatalytic test showed decline in MB reduction rate with loss of Ti O2 particles from the substrate outer surface. However, even in the third cycle, the Ti O2 modified fibers are still moderately effective as it could remove more than 95% of MB after 8 hr of treatment.
基金co-supported by the National Basic Research Project(Nos.J2022-VII-0001-0043 and 2017-VII-0010-0104)the Fundamental Research Funds for the Central Universities,and the National Natural Science Foundation of China(No.72231008)。
文摘Due to the excellent self-centering and load-carrying capability,curvic couplings have been widely used in advanced aero-engine rotors.However,curvic tooth surface errors lead to poor assembly precision.Traditional physical-master-gauge-based indirect tooth surface error measurement and circumferential assembly angle optimization methods have the disadvantages of high cost and weak generality.The unknown tooth surface fitting mechanism is a big barrier to assembly precision prediction and improvement.Therefore,this work puts forward a data-driven assembly simulation and optimization approach for aero-engine rotors connected by curvic couplings.The origin of curvic tooth surface error is deeply investigated.Using 5-axis sweep scan method,a large amount of high-precision curvic tooth surface data are acquired efficiently.Based on geometric models of parts,the fitting mechanism of curvic couplings is uncovered for assembly precision simulation and prediction.A circumferential assembly angle optimization model is developed to decrease axial and radial assembly runouts.Experimental results show that the assembly precision can be predicted accurately and improved dramatically.By uncovering the essential principle of the assembly precision formation and proposing circumferential assembly angle optimization model,this work is meaningful for assembly quality,efficiency and economy improvement of multistage aero-engine rotors connected by curvic couplings.
基金Supported by National Natural Science Foundation of China(Grant No.52005371)Shanghai Pujiang Program of China(Grant No.2020PJD071)+1 种基金Shanghai Municipal Natural Science Foundation of China(Grant No.22ZR1463900)Fundamental Research Funds for the Central Universities of China.
文摘There are lots of researches on fixture layout optimization for large thin-walled parts.Current researches focus on the positioning problem,i.e.,optimizing the positions of a constant number of fixtures.However,how to determine the number of fixtures is ignored.In most cases,the number of fixtures located on large thin-walled parts is determined based on engineering experience,which leads to huge fixture number and extra waste.Therefore,this paper constructs an optimization model to minimize the number of fixtures.The constraints are set in the optimization model to ensure that the part deformation is within the surface profile tolerance.In addition,the assembly gap between two parts is also controlled.To conduct the optimization,this paper develops an improved particle swarm optimization(IPSO)algorithm by integrating the shrinkage factor and adaptive inertia weight.In the algorithm,particles are encoded according to the fixture position.Each dimension of the particle is assigned to a sub-region by constraining the optional position range of each fixture to improve the optimization efficiency.Finally,a case study on ship curved panel assembly is provided to prove that our method can optimize the number of fixtures while meeting the assembly quality requirements.This research proposes a method to optimize the number of fixtures,which can reduce the number of fixtures and achieve deformation control at the same time.
基金financially supported by the National Natural Science Foundation of China(No.21674082)
文摘The liquid-crystal assembly of semiflexible-coil diblock copolymers with coil or semiflexible homopolymers is studied by dissipative particle dynamics simulation. Phase diagrams of the blends and orientation ordering parameters among semiflexible blocks are constructed as a function of chain stiffness and homopolymer volume fraction. For semiflexible-coil/coil blends with varying stiffness of semiflexible blocks, we display the rich phase behaviors of the system transited from coil-coil/coil to rod-coil/coil blends. The disorder- lamellae or lamellae-liquid crystalline transition and ＂dry brush＂ phenomenon induced by coil homopolymers are observed. For semiflexible-coil/semiflexible blends, adding semiflexible homopolymers also leads to a disorder-order transition and even a transition between monolayer and bilayer smectic-A phase. The results demonstrate that blending homopolymers into semiflexible copolymers can induce liquid-crystal assembly and even improve the orientation ordering of semiflexible blocks effectively.
基金by the National Natural Science Foundation of China(Nos.21971180 and 92056111)Natural Science Key Basic Research of Jiangsu Province for Higher Education(No.19KJA360006)+2 种基金Postgraduate Research&Practice Innovation Program of Jiangsu Provinee(No.KYCX20_2655)College Students'Innovation and Entrepreneurship Program(No.201910285021Z)the Priority Academic Program Development(PAPD)of Jiangsu Higher Education Institutions and the Program of Innovative Research Team of Soochow University.Prof.W.Zhang thanks Mr.J.Z.Wang in University of Waterloo for English editing.
文摘In this contribution,we utilized surface initiated atom transfer radical polymerization(SI-ATRP)to prepare organicinorganic hybrid core/shell silila nanoparticles(NPs),where silia particles acted as cores and polymeric shells(PAzoMA*)were attached to silica particles via covalent bond.Subsequently,chiroptical switch was sccessfully constructed on silica NPs surface taking advantage of supramolecular chiral self-assembly of the grafted side chain Azo-containing polymer(PAzoMA*).We found that the supramolecular chirality was highly dependent on the molecular weight of grafted PAzoMA*.Meanwhile,the supramolecular chirality could be regulated using 365 nm UV light iradiation and heating cooling treatment,and a reversible supramolecular chiroptical switch could be repeated for over five cycles on silia NPs surface.Moreover,when heated above the glass transition temperature(T_(g))of PAzoMA",the organic-inorganic hybrid nanoparticles(SiO_(2)@PAzoMA*NPs)still exhibited intense DRCD signals.Interestingly,the supramolecular chirality could be retained in solid film for more than 3 months.To conclude,we have prepared an organic inorganic hybrid core/shell chiral slia nanomaterial with dynamic reversible chirality,thermal stability and chiral storage functions,providing potential applications in dynamic asymmetric catalysis,chiral separation and so on.
文摘A method of 3-D measuring fixture automatic assembly for auto-body part is presented. Locating constraint mapping technique and assembly rule-based reasoning are applied. Calculating algorithm of the position and pose for the part model, fixture configuration and fixture elements in virtual auto-body assembly space are given. Transforming fixture element from itself coordinate system space to assembly space with homogeneous transformation matrix is realized. Based on the second development technique of unigraphics（UG）, the automated assembly is implemented with application program interface （API） function. Lastly the automated assembly of measuring fixture for rear longeron as a case is implemented.
