Effect of neutral polymeric bonding agent on tensile mechanical properties and damage evolution of NEPE propellant

Introducing Neutral Polymeric bonding agents(NPBA) into the Nitrate Ester Plasticized Polyether(NEPE)propellant could improve the adhesion between filler/matrix interface, thereby contributing to the development of new generations of the NEPE propellant with better mechanical properties. Therefore,understanding the effects of NPBA on the deformation and damage evolution of the NEPE propellant is fundamental to material design and applications. This paper studies the uniaxial tensile and stress relaxation responses of the NEPE propellant with different amounts of NPBA. The damage evolution in terms of interface debonding is further investigated using a cohesive-zone model(CZM). Experimental results show that the initial modulus and strength of the NEPE propellant increase with the increasing amount of NPBA while the elongation decreases. Meanwhile, the relaxation rate slows down and a higher long-term equilibrium modulus is reached. Experimental and numerical analyses indicate that interface debonding and crack propagation along filler-matrix interface are the dominant damage mechanism for the samples with a low amount of NPBA, while damage localization and crack advancement through the matrix are predominant for the ones with a high amount of NPBA. Finally, crosslinking density tests and simulation results also show that the effect of the bonding agent is interfacial rather than due to the overall crosslinking density change of the binder.

Micromechanism and mathematical model of stress sensitivity in tight reservoirs of binary granular medium

Research on reservoir rock stress sensitivity has traditionally focused on unary granular structures,neglecting the binary nature of real reservoirs,especially tight reservoirs.Understanding the stresssensitive behavior and mathematical characterization of binary granular media remains a challenging task.In this study,we conducted online-NMR experiments to investigate the permeability and porosity evolution as well as stress-sensitive control mechanisms in tight sandy conglomerate samples.The results revealed stress sensitivity coefficients between 0.042 and 0.098 and permeability damage rates ranging from 65.6%to 90.9%,with an average pore compression coefficient of 0.0168—0.0208 MPa 1.Pore-scale compression occurred in three stages:filling,compression,and compaction,with matrix pores playing a dominant role in pore compression.The stress sensitivity of binary granular media was found to be influenced by the support structure and particle properties.High stress sensitivity was associated with small fine particle size,high fines content,high uniformity coefficient of particle size,high plastic deformation,and low Young's modulus.Matrix-supported samples exhibited a high irreversible permeability damage rate(average=74.2%)and stress sensitivity coefficients(average=0.089),with pore spaces more slit-like.In contrast,grain-supported samples showed low stress sensitivity coefficients(average=0.021)at high stress stages.Based on the experiments,we developed a mathematical model for stress sensitivity in binary granular media,considering binary granular properties and nested interactions using Hertz contact deformation and Poiseuille theory.By describing the change in activity content of fines under stress,we characterized the non-stationary state of compressive deformation in the binary granular structure and classified the reservoir into three categories.The model was applied for production prediction using actual data from the Mahu reservoir in China,showing that the energy retention rates of support-dominated,fill-dominated,and matrix-controlled reservoirs should be higher than 70.1%,88%,and 90.2%,respectively.

Investigation of high rate mechanical flow followed by ignition for high-energy propellant under dynamic extrusion loading

Investigating the ignition response of nitrate ester plasticized polyether(NEPE) propellant under dynamic extrusion loading is of great significant at least for two cases. Firstly, it helps to understand the mechanism and conditions of unwanted ignition inside charged propellant under accident stimulus.Secondly, evaluates the risk of a shell crevice in a solid rocket motor(SRM) under a falling or overturning scene. In the present study, an innovative visual crevice extrusion experiment is designed using a dropweight apparatus. The dynamic responses of NEPE propellant during extrusion loading, including compaction and compression, rapid shear flow into the crevice, stress concentration, and ignition reaction, have been firstly observed using a high-performance high-speed camera. The ignition reaction is observed in the triangular region of the NEPE propellant sample above the crevice when the drop weight velocity was 1.90 m/s. Based on the user material subroutine interface UMAT provided by finite element software LS-DYNA, a viscoelastic-plastic model and dual ignition criterion related to plastic shear dissipation are developed and applied to the local ignition response analysis under crevice extrusion conditions. The stress concentration occurs in the crevice location of the propellant sample, the shear stress is relatively large, the effective plastic work is relatively large, and the ignition reaction is easy to occur. When the sample thickness decreases from 5 mm to 2.5 mm, the shear stress increases from 22.3 MPa to 28.6 MPa, the critical value of effective plastic work required for ignition is shortened from 1280 μs to 730 μs, and the triangular area is easily triggering an ignition reaction. The propellant sample with a small thickness is more likely to stress concentration, resulting in large shear stress and effective work, triggering an ignition reaction.

Performance Analysis and Optimization of Energy Harvesting Modulation for Multi-User Integrated Data and Energy Transfer

Integrated data and energy transfer(IDET)enables the electromagnetic waves to transmit wireless energy at the same time of data delivery for lowpower devices.In this paper,an energy harvesting modulation(EHM)assisted multi-user IDET system is studied,where all the received signals at the users are exploited for energy harvesting without the degradation of wireless data transfer(WDT)performance.The joint IDET performance is then analysed theoretically by conceiving a practical time-dependent wireless channel.With the aid of the AO based algorithm,the average effective data rate among users are maximized by ensuring the BER and the wireless energy transfer(WET)performance.Simulation results validate and evaluate the IDET performance of the EHM assisted system,which also demonstrates that the optimal number of user clusters and IDET time slots should be allocated,in order to improve the WET and WDT performance.

Assessing the energy release characteristics during the middle detonation reaction stage of aluminized explosives

Afterburning behind the detonation front of an aluminized explosive releases energy on the millisecond timescale,which prolong the release of detonation energy and the energy release at different stages also shows significant differences.However,at present,there are few effective methods for evaluating the energy release characteristics of the middle reaction stage of such explosives,which can have a duration of tens to hundreds of microseconds.The present work demonstrates an approach to assessing the midstage of an aluminized explosive detonation based on a water push test employing a high degree of confinement.In this method,the explosive is contained in a steel cylinder having one end closed that is installed at the bottom of a transparent water tank.Upon detonation,the gaseous products expand in one direction while forcing water ahead of them.The resulting underwater shock wave and the interface between the gas phase products and the water are tracked using an ultra-high-speed framing and streak camera.The shock wave velocity in water and the expansion work performed by the gaseous detonation products were calculated to assess the energy release characteristics of aluminized explosives such as CL-20 and RDX in the middle stage of the detonation reaction.During the middle stage of the detonation process of these aluminized explosives,the aluminum reaction reduced the attenuation of shock waves and increased the work performed by gas phase products.A higher aluminum content increased the energy output while the presence of oxidants slowed the energy release rate.This work demonstrates an effective means of evaluating the performance of aluminized explosives.

Effects of nano-metal oxide additives on ignition and combustion properties of MICs-boron rich fuels

Boron has been considered a promising powdered metal fuel for enhancing composite propellants'energy output due to its high energy density.However,the high ignition temperature and low combustion efficiency limit the application of boron powder due to the high boiling point of the boron oxide layer.Much research is ongoing to overcome these shortcomings,and one potential approach is to introduce a small quantity of metal oxide additives to promote the reaction of boron.This study prepared boron-rich fuels with 10 wt%of eight nano-metal oxide additives by mechanical ball milling.The effect of metal oxides on the thermo-oxidation,ignition,and combustion properties of boron powder was comprehensively studied by the thermogravimetric analysis(TG),the electrically heated filament setup(T-jump),and the laser-induced combustion experiments.TG experiments at 5 K/min found that Bi_(2)O_(3),MoO_(3),TiO_(2),Fe_(2)O_(3),and CuO can promote thermo-oxidation of boron.Compared to pure boron,Tonsetcan be reduced from 569℃to a minimum of 449℃(B/Bi_(2)O_(3)).Infrared temperature measurement in T-jump tests showed that when heated by an electric heating wire at rates from 1000 K/s to 25000 K/s,the ignition temperatures of B/Bi_(2)O_(3) are the lowest,even lower than the melting point of boron oxide.Ignition images and SEM for the products further showed that the high heating rate is beneficial to the rapid reaction of boron powder in the single-particle combustion state.Fuels(B/Bi_(2)O_(3),B/MoO_(3),and B/CuO)were mixed with the oxidant AP and ignited by laser to study the combustion performance.The results showed that B/CuO/AP has the largest flame area,the highest BO_(2) characteristic spectral intensity,and the largest burn rate for powder lines.To combine the advantages of CuO and Bi_(2)O_(3),binary metal oxide(CBO,mass ratio of 3:1)was prepared and the test results showed that CBO can very well improve both ignition and combustion properties of boron.Especially B/CBO/AP has the highest burn rate compared with all fuels containing other additives.It was found that multi-component metal-oxide additive can more synergistically improve the reaction characteristics of boron powder than unary additive.These findings contribute to the development of boron-rich fuels and their application in propellants.

Using MsfNet to Predict the ISUP Grade of Renal Clear Cell Carcinoma in Digital Pathology Images

Clear cell renal cell carcinoma(ccRCC)represents the most frequent form of renal cell carcinoma(RCC),and accurate International Society of Urological Pathology(ISUP)grading is crucial for prognosis and treatment selection.This study presents a new deep network called Multi-scale Fusion Network(MsfNet),which aims to enhance the automatic ISUP grade of ccRCC with digital histopathology pathology images.The MsfNet overcomes the limitations of traditional ResNet50 by multi-scale information fusion and dynamic allocation of channel quantity.The model was trained and tested using 90 Hematoxylin and Eosin(H&E)stained whole slide images(WSIs),which were all cropped into 320×320-pixel patches at 40×magnification.MsfNet achieved a micro-averaged area under the curve(AUC)of 0.9807,a macro-averaged AUC of 0.9778 on the test dataset.The Gradient-weighted Class Activation Mapping(Grad-CAM)visually demonstrated MsfNet’s ability to distinguish and highlight abnormal areas more effectively than ResNet50.The t-Distributed Stochastic Neighbor Embedding(t-SNE)plot indicates our model can efficiently extract critical features from images,reducing the impact of noise and redundant information.The results suggest that MsfNet offers an accurate ISUP grade of ccRCC in digital images,emphasizing the potential of AI-assisted histopathological systems in clinical practice.

Experimental Study on the Attenuation Law of Vibration Wave Propagation in Natural Gas Wells in Coal-Gas Cross-Mining Area

Aiming at the safety distance between coal mining working face and natural gas wells in the cross-mining area of multiple mineral resources, the cross- mining area of gas and coal resources in the Ordos Basin is taken as the engineering background. An anti-collision early warning technology method based on vibration wave propagation attenuation monitoring is proposed to prevent collision accidents between road headers and natural gas wells. Through the steel pipe and steel pipe concrete knocking vibration test and underground digging vibration test, the research results show that: The exponential decay coefficients of the vibration wave in steel pipe, steel pipe concrete and coal rock respectively are 0.1, 0.1140 and 0.03, which are all in accordance with the exponential decay law, and the vibration wave firstly decays sharply and then decays slowly;the formula for the distance from the road header to the natural gas well was derived based on the vibration attenuation formula, to provide a new method for realizing the problem of precise and coordinated extraction by surface monitoring of the distance from down hole road headers to gas wells, collision prevention prediction and warning and prevention of collision of extraction equipment with gas wells.

Experimental study of surfactant-enhanced spontaneous imbibition in fractured tight sandstone reservoirs: The effect of fracture distribution

Spontaneous imbibition is an important phenomenon in tight reservoirs.The existence of a large number of fractures and micro-nano pores is the key factor affecting the spontaneous imbibition of tight reservoirs.In this study,based on high-pressure mercury injection and nuclear magnetic resonance experiments,the pore distribution of tight sandstone is described.The influence of fractures,core porosity and permeability,and surfactants on the spontaneous imbibition of tight sandstone are studied by physical fracturing,interfacial tension test,wettability test and imbibition experiments.The results show that:the pore radius of tight sandstone is concentrated in 0.01-1 mm.Fractures can effectively reduce the oil drop adsorption on the core surface,enhancing the imbibition recovery of the tight sandstone with an increase of about 10%.As the number of fractures increases,the number of oil droplets adsorbed on the core surface decrease and the imbibition rate increases.The imbibition recovery increases with the increase in pore connectivity,while the imbibition rate increases with the increases in core porosity and permeability.The surfactant can improve the core water wettability and reduce the oilwater interfacial tension,reducing the adsorption of oil droplets on the core surface,and improving the core imbibition recovery with an increase of about 15%.In a word,the existence of fractures and surfactants can enhance the pore connectivity of the reservoir,reduce the adsorption of oil droplets on the core surface,and improve the imbibition rate and recovery rate of the tight oil reservoir.

Multi-Sinusoidal Waveform Shaping for Integrated Data and Energy Transfer in Aging Channels

Integrated data and energy transfer(IDET)is capable of simultaneously delivering on-demand data and energy to low-power Internet of Everything(Io E)devices.We propose a multi-carrier IDET transceiver relying on superposition waveforms consisting of multi-sinusoidal signals for wireless energy transfer(WET)and orthogonal-frequency-divisionmultiplexing(OFDM)signals for wireless data transfer(WDT).The outdated channel state information(CSI)in aging channels is employed by the transmitter to shape IDET waveforms.With the constraints of transmission power and WDT requirement,the amplitudes and phases of the IDET waveform at the transmitter and the power splitter at the receiver are jointly optimised for maximising the average directcurrent(DC)among a limited number of transmission frames with the existence of carrier-frequencyoffset(CFO).For the amplitude optimisation,the original non-convex problem can be transformed into a reversed geometric programming problem,then it can be effectively solved with existing tools.As for the phase optimisation,the artificial bee colony(ABC)algorithm is invoked in order to deal with the nonconvexity.Iteration between the amplitude optimisation and phase optimisation yields our joint design.Numerical results demonstrate the advantage of our joint design for the IDET waveform shaping with the existence of the CFO and the outdated CSI.

Numerical simulation of drop weight impact sensitivity evaluation criteria for pressed PBXs

A thorough understanding of drop-weight impacted responses for polymer-bonded explosives(PBXs)is significant to evaluate their impact sensitivity.The characteristics of the drop-weight impacted pressed PBXs including deforming,fracturing,forming a local high-temperature region and igniting,were simulated using a coupled mechanical-thermo-chemical model integrating micro-defects evolution.A novel evaluation method for impact sensitivity is established using the relation between the input kinetic energy and the output energy due to deformation,crushing energy,local hot spot energy and ignition.The effects of impact velocity on sensitivity were analyzed and the critical local ignition impact velocity is determined as 4.0-4.5 m/s.The simulated results show that shear-crack friction heating is the dominant ignition mechanism.The region along the boundary of PBXs sample is the most hazardous regions where ignition first occur.The propagation of stress wave in PBXs causes shear-crack hotspot and bulk temperature exhibiting an approximate 45°direction evolution path,which is the main reason that dominated damage-ignition region transits from the boundary to the central of sample.

Comparison of sequencing-based and array-based genotyping platforms for genomic prediction of maize hybrid performance

Genomic selection(GS)is a powerful tool for improving genetic gain in maize breeding.However,its routine application in large-scale breeding pipelines is limited by the high cost of genotyping platforms.Although sequencing-based and array-based genotyping platforms have been used for GS,few studies have compared prediction performance among platforms.In this study,we evaluated the predictabilities of four agronomic traits in 305 maize hybrids derived from 149 parental lines subjected to genotyping by sequencing(GBS),a 40K SNP array,and target sequence capture(TSC)using eight GS models.The GBS marker dataset yielded the highest predictabilities for all traits,followed by TSC and SNP array datasets.We investigated the effect of marker density and statistical models on predictability among genotyping platforms and found that 1K SNPs were sufficient to achieve comparable predictabilities to 10K and all SNPs,and BayesB,GBLUP,and RKHS performed well,while XGBoost performed poorly in most cases.We also selected significant SNP subsets using genome-wide association study(GWAS)analyses in three panels to predict hybrid performance.GWAS facilitated selecting effective SNP subsets for GS and thus reduced genotyping cost,but depended heavily on the GWAS panel.We conclude that there is still room for optimization of the existing SNP array,and using genotyping by target sequencing(GBTS)techniques to integrate a few functional markers identified by GWAS into the 1K SNP array holds great promise of being an effective strategy for developing desirable GS breeding arrays.

UAV-Aided Data and Energy Integrated Network: System Design and Prototype Development

Terminal devices deployed in outdoor environments are facing a thorny problem of power supply.Data and energy integrated network(DEIN)is a promising technology to solve the problem,which simultaneously transfers data and energy through radio frequency signals.State-of-the-art researches mostly focus on theoretical aspects.By contrast,we provide a complete design and implementation of a fully functioning DEIN system with the support of an unmanned aerial vehicle(UAV).The UAV can be dispatched to areas of interest to remotely recharge batteryless terminals,while collecting essential information from them.Then,the UAV uploads the information to remote base stations.Our system verifies the feasibility of the DEIN in practical applications.

Residual Feature Attentional Fusion Network for Lightweight Chest CT Image Super-Resolution

The diagnosis of COVID-19 requires chest computed tomography(CT).High-resolution CT images can provide more diagnostic information to help doctors better diagnose the disease,so it is of clinical importance to study super-resolution(SR)algorithms applied to CT images to improve the reso-lution of CT images.However,most of the existing SR algorithms are studied based on natural images,which are not suitable for medical images;and most of these algorithms improve the reconstruction quality by increasing the network depth,which is not suitable for machines with limited resources.To alleviate these issues,we propose a residual feature attentional fusion network for lightweight chest CT image super-resolution(RFAFN).Specifically,we design a contextual feature extraction block(CFEB)that can extract CT image features more efficiently and accurately than ordinary residual blocks.In addition,we propose a feature-weighted cascading strategy(FWCS)based on attentional feature fusion blocks(AFFB)to utilize the high-frequency detail information extracted by CFEB as much as possible via selectively fusing adjacent level feature information.Finally,we suggest a global hierarchical feature fusion strategy(GHFFS),which can utilize the hierarchical features more effectively than dense concatenation by progressively aggregating the feature information at various levels.Numerous experiments show that our method performs better than most of the state-of-the-art(SOTA)methods on the COVID-19 chest CT dataset.In detail,the peak signal-to-noise ratio(PSNR)is 0.11 dB and 0.47 dB higher on CTtest1 and CTtest2 at×3 SR compared to the suboptimal method,but the number of parameters and multi-adds are reduced by 22K and 0.43G,respectively.Our method can better recover chest CT image quality with fewer computational resources and effectively assist in COVID-19.

Multi-Classification of Polyps in Colonoscopy Images Based on an Improved Deep Convolutional Neural Network

Achieving accurate classification of colorectal polyps during colonoscopy can avoid unnecessary endoscopic biopsy or resection.This study aimed to develop a deep learning model that can automatically classify colorectal polyps histologically on white-light and narrow-band imaging(NBI)colonoscopy images based on World Health Organization(WHO)and Workgroup serrAted polypS and Polyposis(WASP)classification criteria for colorectal polyps.White-light and NBI colonoscopy images of colorectal polyps exhibiting pathological results were firstly collected and classified into four categories:conventional adenoma,hyperplastic polyp,sessile serrated adenoma/polyp(SSAP)and normal,among which conventional adenoma could be further divided into three sub-categories of tubular adenoma,villous adenoma and villioustublar adenoma,subsequently the images were re-classified into six categories.In this paper,we proposed a novel convolutional neural network termed Polyp-DedNet for the four-and six-category classification tasks of colorectal polyps.Based on the existing classification network ResNet50,Polyp-DedNet adopted dilated convolution to retain more high-dimensional spatial information and an Efficient Channel Attention(ECA)module to improve the classification performance further.To eliminate gridding artifacts caused by dilated convolutions,traditional convolutional layers were used instead of the max pooling layer,and two convolutional layers with progressively decreasing dilation were added at the end of the network.Due to the inevitable imbalance of medical image data,a regularization method DropBlock and a Class-Balanced(CB)Loss were performed to prevent network overfitting.Furthermore,the 5-fold cross-validation was adopted to estimate the performance of Polyp-DedNet for the multi-classification task of colorectal polyps.Mean accuracies of the proposed Polyp-DedNet for the four-and six-category classifications of colorectal polyps were 89.91%±0.92%and 85.13%±1.10%,respectively.The metrics of precision,recall and F1-score were also improved by 1%∼2%compared to the baseline ResNet50.The proposed Polyp-DedNet presented state-of-the-art performance for colorectal polyp classifying on white-light and NBI colonoscopy images,highlighting its considerable potential as an AI-assistant system for accurate colorectal polyp diagnosis in colonoscopy.

Damage-ignition mechanism studies on modified propellant with different crosslinking density under dynamic loading

The study of high-energy and low-vulnerability propellants is important for the power performance and safety of solid propellant rocket motors.The modified split Hopkinson pressure bar(SHPB)tests are performed on two kinds of propellant with different crosslinking density to study the dynamic mechanical responses and damage-ignition mechanism.SHPB apparatus is equipped with a highperformance infrared camera and high-speed camera to capture the deformation,damage-ignition feature and temperature evolution images in the impact process.The results suggested that the mechanical responses and damage-ignition mechanism of the propellants were affected by the strain rates and crosslinking density.The damage-ignition degree is more intense and the reaction occurs earlier with the increase of strain rates.For propellant 1 with higher crosslinking density,the critical ignition strain rate is 4500 s^(-1).Two kinds of propellants show different ignition mechanism,i.e.crack generation,propagation and final fracture for propellant 1 while viscous shear flow for propellant 2.Meanwhile,the SEM images also reveal the difference of damage-ignition mechanism of the two kinds of propellants.Finally,the ignition mechanism under different strain rates and critical ignition strain rate of propellants are further explained by the theoretical calculation of temperature variations.

Bearing Fault Diagnosis with DDCNN Based on Intelligent Feature Fusion Strategy in Strong Noise

Intelligent fault diagnosis in modern mechanical equipment maintenance is increasingly adopting deep learning technology.However,conventional bearing fault diagnosis models often suffer from low accuracy and unstable performance in noisy environments due to their reliance on a single input data.Therefore,this paper proposes a dual-channel convolutional neural network(DDCNN)model that leverages dual data inputs.The DDCNN model introduces two key improvements.Firstly,one of the channels substitutes its convolution with a larger kernel,simplifying the structure while addressing the lack of global information and shallow features.Secondly,the feature layer combines data from different sensors based on their primary and secondary importance,extracting details through small kernel convolution for primary data and obtaining global information through large kernel convolution for secondary data.Extensive experiments conducted on two-bearing fault datasets demonstrate the superiority of the two-channel convolution model,exhibiting high accuracy and robustness even in strong noise environments.Notably,it achieved an impressive 98.84%accuracy at a Signal to Noise Ratio(SNR)of−4 dB,outperforming other advanced convolutional models.

The Pythium periplocum elicitin PpEli2 confers broad-spectrum disease resistance by triggering a novel receptor-dependent immune pathway in plants

Elicitins are microbe-associated molecular patterns produced by oomycetes to elicit plant defense.It is still unclear whether elicitins derived from non-pathogenic oomycetes can be used as bioactive molecules for disease control.Here,for the first time we identify and characterize an elicitin named PpEli2 from the soil-borne oomycete Pythium periplocum,which is a non-pathogenic mycoparasite colonizing the root ecosystem of diverse plant species.Perceived by a novel cell surface receptor-like protein,REli,that is conserved in various plants(e.g.tomato,pepper,soybean),PpEli2 can induce hypersensitive response cell death and an immunity response in Nicotiana benthamiana.Meanwhile,PpEli2 enhances the interaction between REli and its co-receptor BAK1.The receptor-dependent immune response triggered by PpEli2 is able to protect various plant species against Phytophthora and fungal infections.Collectively,our work reveals the potential agricultural application of non-pathogenic elicitins and their receptors in conferring broad-spectrum resistance for plant protection.

5.9 GHz Vehicular Channels Comparisons Between Two Traffic Status for Dense Urban Area

This study focused on differences in vehicle-to-vehicle radio channel character- istics in the same region but different traffic density and speeds at 5.9 GHz （congestion and non-congestion）. The continuous measurement campaign was conducted on a city expressway through the complex dense urban area in Wu- hart, China. Small-scale channel characteris- tics including power delay profile, amplitude fading distribution, K-factor, delay spread and Doppler shift were obtained, respectively. Spe- cifically, the cumulative distribution function of root mean square delay spreads and root mean square Doppler spreads in the non-con- gested scenario and congested scenario were all fitted well with Lognormal distribution. We also found out that different intensity of traffic and speed of vehicles have little effect on root mean square delay spreads, but have a big im- pact on root mean square Doppler spreads and level crossing rate. According to estimation outcomes, the V2V channel characteristics for urban areas in Chinese big city were differ- ent from the previous measured results under similar scenarios in Europe. Delay spread and level crossing rate in this study can provide significant references to design the wireless communication system for vehicle-to-vehicle channel.

基于电场驱动熔融喷射3D打印大面积聚甲基丙烯酸甲酯微结构制造方法

针对大面积聚甲基丙烯酸甲酯(PMMA)微结构低成本制造的难题以及高分辨率PMMA成型的实际需求,提出一种基于电场驱动熔融喷射沉积3D打印实现大面积PMMA微结构高效低成本制造的新方法。通过高速摄像机实验观测和系列打印实验研究,揭示了主要工艺参数对于成型过程、打印分辨率、打印质量的影响和规律,优化的工艺参数范围为:电压1200~1300 V,气压3~10 kPa,打印高度200~400μm,打印速度5~20 mm/s,材料加热温度210~230℃。利用提出的新方法,结合优化出的工艺参数,采用内径250μm的喷嘴,实现了最小特征尺寸15μm、图形面积70 mm×70 mm大尺寸微模具以及高宽比达到9∶1大面积复杂微结构和组织工程支架的制造。