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As two necessary steps in phase-field simulation, parameters calculation and results storage play an important role to ensure the accuracy of simulation results. A strategy of parameters calculation and results storage was presented for phase-field simulation in α-Mg dendrite growth of Mg-5wt%Zn alloy under isothermal solidification. Based on the phase diagram and empirical formulas, key parameters of the phase-field model (equilibrium partition coefficient k, liquidus slope m, solutal diffusion coefficient in liquid Dl , solutal diffusion coefficient in solid Ds , etc.) can be obtained. Both structured grid and structured point storage methods can be used to store simulation results, but using the latter method will reduce about 60% storage space and 37.5% storage time compared to the former. Finally, convergent simulation results of α-Mg dendrite growth were obtained and in good agreement with the optical micrograph of experimental results, which verify the accuracy of parameters and stability of storage methods.

The perovskite light emitting diodes (PeLED / PeLEDs) possess the high efficiency and the wonderful color purity properties. However, the poor operational stability has hindered its broader development and commercial application. Utilizing the all-inorganic perovskites to fabricate PeLEDs is considered useful for enhancing device stability. In contrast, the resultant perovskite crystals in the emissive film show large grain sizes and low photoluminance efficiency. In this work, the sodium trifluoroacetate additive is introduced into all inorganic perovskite films to passivate surface defects and control the growth of the CsPbBr3 crystal. This approach results in inorganic perovskites with smaller grains and uniform surface morphology, which enables improved device performance.

The development of the construction industry promotes the development of BIM technology, which in turn promotes the development of the construction industry. This paper first analyzes the status quo of BIM technology, construction organization design and engineering cost, and then analyzes the construction organization design and engineering cost application based on BIM technology. This paper takes a residential building as an example for detail, uses BIM technology to carry out modeling and measurement, construction schedule plan, site layout and project cost, and conducts the rationality analysis of the quantity and the rationality of the cost. The results show that the development of BIM technology greatly facilitates the construction organization design and engineering cost of construction projects.

Nonlinear normal modes are periodic orbits that survive in nonlinear chains, whose instability plays a crucial role in the dynamics of many-body Hamiltonian systems toward thermalization. Here we focus on how the stability of nonlinear modes depends on the perturbation strength and the system size to observe whether they have the same behavior in different models. To this end, as illustrating examples, the instability dynamics of the N/2 mode in both the Fermi–Pasta–Ulam–Tsingou-α and -β chains under fixed boundary conditions are studied systematically. Applying the Floquet theory, we show that for both models the stability time T as a function of the perturbation strength λ follows the same behavior; i.e., T ∝ ( λ − λ c ) − 1 2 , where λ c is the instability threshold. The dependence of λ c on N is also obtained. The results of T and λ c agree well with those obtained by the direct molecular dynamics simulations. Finally, the effect of instability dynamics on the thermalization properties of a system is briefly discussed.

In this letter, a strategy dedicated to the concise and efficient development of the customized large-signal models for GaAs HEMTs is proposed, which is specialized for MMIC designers. The core concepts of the strategy are a deconstruction of the original thought of model construction and dimension reduction of the objective functions of optimization algorithms. The development of an Angelov-based customized large-signal model following this strategy has been successfully applied to GaAs HEMTs in 70nm process. The results show that it takes less than five minutes to execute such a parameter extraction algorithm with a one-button extraction function and good agreement is achieved between the model simulation and device measurement up to 65GHz.

Machine learning provides a way to use only portions of the variables of a spatiotemporal system to predict its subsequent evolution and consequently avoids the curse of dimensionality. The learning machines employed for this purpose, in essence, are time-delayed recurrent neural networks with multiple input neurons and multiple output neurons. We show in this paper that such kinds of learning machines have a poor generalization ability to variables that have not been trained with. We then present a one-dimensional time-delayed recurrent neural network for the same aim of model-free prediction. It can be trained on different spatial variables in the training stage but initiated by the time series of only one spatial variable, and consequently possess an excellent generalization ability to new variables that have not been trained on. This network presents a new methodology to achieve fine-grained predictions from a learning machine trained on coarse-grained data, and thus provides a new strategy for certain applications such as weather forecasting. Numerical verifications are performed on the Kuramoto coupled oscillators and the Barrio−Varea−Aragon−Maini model.

Phase unwrapping plays an important role in optical phase measurements. In particular, phase unwrapping under heavy noise conditions remains an open issue. In this paper, a deep learning-based method is proposed to conduct the phase unwrapping task by combining Zernike polynomial fitting and a Swin-Transformer network. In this proposed method, phase unwrapping is regarded as a regression problem, and the Swin-Transformer network is used to map the relationship between the wrapped phase data and the Zernike polynomial coefficients. Because of the self-attention mechanism of the transformer network, the fitting coefficients can be estimated accurately even under extremely harsh noise conditions. Simulation and experimental results are presented to demonstrate the outperformance of the proposed method over the other two polynomial fitting-based methods. This is a promising phase unwrapping method in optical metrology, especially in electronic speckle pattern interferometry.

One of the important features of the “new information age” is “big data”. In the age of big data, with the introduction of student information management systems, colleges and universities are increasingly paying attention to systematically managing student information management and improving their efficiency, effective management of student information and innovative development to build a new model of management system. In studying the evolution of student information management, big data technologies emerging in the information age play an important role. By leveraging big data to improve systematic management of student information, colleges and universities can manage student information faster and more efficiently and make new contributions to the advancement of student information management. In this article, information management is considered as the theoretical basis for research, big data technology is used as the main search algorithm, and its important content is combined to analyze and study the possibilities of the student information management system. In this article, an information management system for university students is used as a research object, which is optimized and improved through big data technologies. Big Data technology can be seen as a kind of algorithm for analyzing and processing data. Therefore, it can be used to create a student information management strategy. The experimental results show that this research has a better impact on the creation and implementation of an information management system for students using Big Data technology and the application of Big Data technology in the information management system for students.

The current article explores the effect of viscous dissipation on the hybrid nanofluid flow over a stretching sheet. Further, different nanoparticles can be used to enhance the thermal conductivity of the fluid. The resultant suspension is examined with the effect of velocity slip. The velocity slip effect is incorporated in the boundary condition of the momentum equation. Heat transfer analysis is done in presence of convective conditions and thermal radiation. Comparative study of different hybrid nanofluids and nanofluid is considered. Here we have chosen manganese Zinc ferrite MnZnFe2O4 and Nickle Zinc ferrite NiZnFe2O4 as nanoparticles in base fluids Kerosene oil and engine oil. Mathematical modeling of the present flow system is illustrated and solved by the shooting built-in method. Graphs for velocity, temperature, skin friction and Nusselt number are presented for different parameters. Here we noticed that velocity profile of MnZnF e 2 O 4 − NiZnF e 2 O 4 − C 1 0 H 2 2 − C 8 H 18 is maximum as compared to other hybrid nanofluids. Velocity and temperature have opposite effects against slip parameter. The temperature of the fluid rises with Biot number and thermal radiation.

This paper discusses the performance of an improved dual-hop mixed radio frequency (RF) / free space optical (FSO) relay communication system in the present of multiple co-channel interferences (CCIs) at the relay node. Multi-user diversity(MUD) technology has been adopted to improve the RF link performance. In order to improve the performance of the FSO link, multi-aperture receiver scheme has been implemented. The multi-user RF link experiences Nakagami-m fading, while the FSO link is subjected to Exponentiated Weibull distributed atmospheric turbulence. Moreover, the CCIs at the relay node are assumed to undergo Nakagami-m fading. For this proposed system, the exact closed-form expression for the outage probability (OP) has been derived. To quickly understand the effects of different parameters on the system performance, the asymptotic expression for the case of high signal-to-noise (SNR) has been further presented. Results show that the diversity order of this proposed system is min (αβM/2,m 1 K), where M represents the number of receiver apertures; K denotes the number of users; α, β and m 1 are the channel parameters. Additionally, the effects of various parameters on system performance have been investigated. Finally, the numerical results have been validated by Monte-Carlo simulations.

Pre-creep experiments were performed on chromium-nickel (Cr-Ni) stainless steel in the early stage of creep. The temperature was held for 500–2000 h under high-temperature load conditions (873 K and 150 MPa), and various analysis methods, including optical microscopy, electron backscatter diffraction (EBSD), transmission electron microscopy (TEM), and X-ray diffraction, were used to determine the pattern of dislocation evolution under different temperature-holding times. The results showed that the slip bands intersected at the initial stage of pre-creep, and a quadrilateral network structure was formed by the dislocation pinning. As the temperature-holding time increased, the dislocation network began to climb to form dislocation walls, dislocation cells, and other substructures. At 2000 h, the grain boundaries widened considerably; creep holes were found at the grain boundaries; and dislocation pairs with oscillating contrast occurred, which indicates nitrogen diffusion. The yield and tensile strengths of the Cr-Ni steel samples subjected to pre-creep at holding times of above 1000 h decreased after they were subjected to room-temperature tensile tests.

In this work, novel graphitic sheets with ripple-like folds (GSRFs) are synthesized from cheap resin via a facile route. The obtained GSRFs are used as a cladding layer for LiNi0.8Co0.15Al0.05O2 (NCA) particles to construct a GSRF@NCA composite cathode. Electrochemical testing for GSFR@NCA exhibits better cycling and C-rate performance than those of original NCA. Moreover, the capacity retention (85%) of the full-cell (GSFR@NCA versus graphite) is much higher than that (79%) of the full-cell (NCA versus graphite) after 400 cycles. Most importantly, this approach allows the preparation of GSFR@NCA with highly promising applications as a cathode for high-energy-density lithium-ion batteries, since in this contribution just simple equipment and a precursor with low cost are involved.

The ground environmental vibration caused by traffic load will attenuate monotonously with the increase of the distance from the load source. However, considering the complexity of stratum factors, the attenuation of ground vibration will have local amplification of ground vibration instead of monotonous attenuation. This article is based on RBF neural network. The method can predict the ground environment vibration of the local amplification phenomenon of the ground vibration. This paper selects the theoretical solution of the complex theoretical model to perform the fitting approximation and the numerical approximation with the measured discrete data. The results show that the numerical approximation is better. Since the RBF neural network does not require other neural network models to perform supervised learning training, the numerical convergence speed is also relatively fast.

In order to solve the problems of high cost and large input resources of traditional greenhouse management system, this paper designs an intelligent greenhouse management and control system. The core control part of the system uses a cloud integration design architecture chip, based on China’s Alibaba dominated YoC platform to realize the cloud integration design. The end side design with a master control board which using a 485 bus communication, and polling mode was adopted to realize the sensor data acquisition and actuator control; The cloud side creates Topic list on the cloud platform of Internet of things, communicates with the end side through the subscription and publication mechanism of MQTT protocol, and realizes data upload and cloud instruction acquisition. Finally, the function test is carried out in the environment of greenhouse simulation mode.

This paper centers on optimizing the signal timing scheme to reduce motor vehicle unregulated emissions from motor vehicles at the intersection by the integration method of VISSIM and MOVES. Taking the intersection of Hong Kong Middle Road and Fuzhou South Road in Qingdao as the research object. In VISSIM, according to the traffic flow, the signal timing scheme is optimized. The localized MOVES emission model calculates emissions of formaldehyde, ammonia and benzene. Compared with emissions of regulated pollutants before and after the optimization for the signal timing scheme, the result shows the optimized signal timing improves the passing capacity of the road intersection, and emissions of formaldehyde, NH3 and benzene reduces by 22%, 7% and 14% respectively. The result indicates that the optimized signal timing can effectively reduce motor vehicle unregulated emissions at the road intersection, which provides an effective way to protect the environment.

Based on the samples of 31 provinces (cities, autonomous regions) in China from 2000 to 2016, this paper studies the correlation and spillover of industrial agglomeration and haze pollution. The results show that: (1) the spillover effect of industrial agglomeration and haze pollution is obvious. Haze pollution is mainly high-high agglomeration and low low-low agglomeration, showing stability. (2) Haze pollution is also more serious in areas with high industrial concentration, and the two show correlation and consistency. Based on this, This paper suggests that the complementary mechanism of haze prevention and control should be improved to better strengthen regional cooperation and achieve the best effect of coordinated management of regional joint prevention and control.

This experimental study aims to investigate the capability of the ultrasonic method by using critically refracted longitudinal (LCR) wave for measuring welding stress in elastic limits.Ultrasonic technique is based on the linear relation between the ultrasonic wave velocity and the stress, known as the acoustoelastic effect.To determine acoustoelasticconstants, different amounts of stress were applied to the specimens by using uniaxial tensiletesting machine. The outcome of the study showed a linear relation between time-of-flight (TOF) measured and the tensile stress in the samplesand providedthe acoustoelasticconstants of Q345. This paper also analyzed the measurement influence factors including the thickness of couplant, temperature and residual stress.

Phase unwrapping is a crucial process to obtain the absolute phase profile in many optical phase measurement techniques such as interferometry, holography, profilometry, etc. In this paper, we have studied several phase unwrapping algorithms based on solving the discrete Poisson equation. The differences among those algorithms lie in two aspects: one is the way to calculate the input for the Poisson equation using the wrapped phase data and the other is the way to compute the output (unwrapped phase data) using the corresponding input. Firstly, the method to compute the input for the Poisson equation was investigated using the finite difference (FD) and fast Fourier transform(FFT) method. Then different methods, based on FFT or discrete cosine transform (DCT), were employed to calculate the unwrapped phase, and their performances were compared in terms of accuracy and efficiency. To enhance the precision of those algorithms, an iteration strategy was introduced and its performance was investigated under different noise conditions. Finally, several real phase data were tested by using the direct and iterative methods. The detailed software package can be found in https://www.mathworks.com/matlabcentral/fileexchange/71810-phase- unwrapping-algorithms-by-solving-the-poisson-equation.

The purpose of this paper is to investigate the dynamic characteristic of the scissor linear array deployable structure under the coupling action of clearance joints, where the kinematic model of the deployable structure with clearance is established according to the principle of the motion between joint elements. The normal and tangential contact forces between contact components are respectively described using the Flores contact force model and modified Column friction model. In the sequel of this process, the impact forces between the connected components are converted to the mass centers of links connected by this clearance joint, and the converted contact force and additional torque were integrated to the generalized force in motion equations of the deployable structure, and then the effect of joint clearance is introduced to deployable syetem. The simulation results show that the dynamic characteristics of the mechanism are very sensitive to the clearance position, and the movement of a joint clearance will affect the movement of the other joint clearance, which shows that clearance joints in deployable structure have a strong dynamic interaction and all the joints should be modeled as real joints.

In order to search for stable ferromagnets with high spin polarization in Heusler alloys for spintronic applications, we develop an efficient machine learning workflow based on a deep neural network, whose training data were collected from the open quantum materials database and high throughput calculation by first-principle calculations. The lattice constants, formation energy and spin polarization of 10 577 candidate materials were predicted, and 192 materials with high spin polarization were selected according to a spin polarization greater than 0.87 and formation energy less than 80 meV/atom. 57 of these alloys have been reported as Half-metal (100% spin polarization) according to previous researches, and 18 have been reported as semiconductors. Especially, 6 Heusler alloys were identified as promising half-metallic ferromagnets, and some of them have high Curie temperature above room temperature. Our study suggests this approach is an efficient method for the discovery of superior spintronic materials, which should be also suitable for exploring other functional materials.

Active electrocatalysts are the key to water splitting for hydrogen production through the electrolysis. In this paper, 50 nm silver nanoplates were used as templates for synthesis of Au–Ag island-shaped nanoplates by controlling the surface chemistry. The guiding mechanism of polyvinylpyrrolidone (PVP, Mw = 40 000) to Au–Ag island-shaped nanoplates crystal was also further investigated. It is found that the surface energy of Ag nanoplates between (100) and (111) crystal planes can be regulated by varying the amount of PVP in the system. Then a uniform Au-Ag triangular island nanostructure was obtained. Compared with the Ag nanoplates catalysts, the Au–Ag island nanoplates catalysts show the superior catalytic performances in hydrogen evolution electrocatalysis (HER). These results demonstrate a new surface chemistry modification by PVP and a galvanic displacement reaction for designing the active electrocatalysts. More importantly, the Au–Ag island-shaped nanoplates show an unconventional growth mode of preserving the original Ag nano-triangular crystal structure. The enhanced performance in electrocatalysis can be mainly attributed to Au–Ag alloy structure, which allows the appearance of synergistic effects. The present work demonstrates the crucial roles of surface chemistry in catalysts synthesis, which may guide the design of active bimetallic catalysts.

The mechanism of single event transients in indium phosphide heterojunction bipolar transistors are studied with different laser energy, collector and irradiation positions based on a pulsed laser experiment. The area of the depletion region neutralized by the laser track determines the area of the funnel region, and affects the total charges collected by collector Q Total. The total charge collection consists of the charge collected in the depletion region, the charges collected in funnel region, and the diffusion charges. The larger the area of the neutralized depletion region, the larger the area of the funnel region, thus, the more electron–hole pairs would be collected. The influence of laser energy, collector bias and irradiation positions on total charge collection is studied and discussed in detail.

Single-crystal GaN layers have been obtained by nitriding β-Ga2O3 films in NH3 atmosphere. The effect of the temperature and time on the nitridation and conversion of Ga2O3 films have been investigated. The nitridation process results in lots of holes in the surface of films. The higher nitridation temperature and longer time can promote the nitridation and improve the crystal quality of GaN films. The converted GaN porous films show the single-crystal structures and low-stress, which can be used as templates for the epitaxial growth of high-quality GaN.

Although the regulation of silver nanostructures has been reported a lot, there are few reports on the simple green preparation method of ultra-long silver nanobelts and the formation mechanism of silver nanostructures is not uniform. In this paper, ultra-long silver nanobelts and dendrite silver were synthesized through a galvanic displacement and the growth mechanism of the silver nanosturture were investigated in detail. In the primary battery reaction, the introduction of copper ions could change the electric double layer and then affected the growth of silver nanosturcture. Different concentration of copper ion lead to different silver nanostructures. The greater the concentration of copper ions, the more the silver nanostructures grow in three dimensions.

Selective and sensitive determination of nitrite is of great importance in practical application. In the present work, a novel nitrite sensing platform was built based on the fabrication of nitrogen-doped-carbon-coated hexagonal cobalt oxyhydroxide (CN@CoOOH) on reduced graphene oxide (RGO) using zeolitic imidazolate framework (ZIF)-67 as a precursor. The CN@CoOOH/RGO nanocomposite was confirmed by UV-visible spectroscopy, Fourier transform infrared spectroscopy, x-ray photoelectron spectrum, transmission electron microscopy, scanning electron microscopy, and x-ray diffraction. We applied the nanocomposite to detect nitrite selectively and sensitively through amperometry for the first time. The anodic current values increased with the addition of nitrite. Therefore, the concentrations of nitrite were quantitatively detected using a CN@CoOOH/RGO based sensor. A wider linear range of 0.1 to 7000 μM was obtained with a lower detection limit of 10 nM (S/N = 3). The proposed method was also applied to detect nitrite released from normal liver cells and human hepatoma cells.

Electrohydrodynamic (EHD) printing is a promising technique for additive manufacturing of high-resolution features with low cost and high efficiency. One of the major issues in EHD printing is nozzle clogging, which often occurs in the printing of colloidal inks with high concentrations. We proposed a new EHD printing nozzle configuration with dual channels to enable ink flow circulation to resolve the above issue. In this study, we focused on the meniscus dynamics and jetting characteristics of this new EHD printing process. Various jetting modes, i.e. continuous jet, pulsating jet, and pulsating droplet, as a function of the electric field intensity and nozzle configuration, were discussed. Dot patterns on a flexible substrate have been demonstrated via the new EHD printing process when operated at the pulsating droplet mode.

2D phase-unwrapping algorithms (PUAs) are commonly used to obtain a continuous phase map from the sawtooth-shaped phase map. However, implementing PUAs can be time consuming, and the accuracy of those algorithms may be low if there is heavy noise. In this paper, we develop a simple and robust PUA based on the transport of intensity equation (TIE). In our method, the TIE was solved using the fast cosine transform, and a phase correction operation was introduced after the TIE was solved. Because of the phase correction operation, the proposed method can obtain a satisfactory unwrapping result even in a notably hash noise condition. The simulation and experimental results are presented to validate the effectiveness of the proposed method. The detailed software package can be found at https://ww2.mathworks.cn/matlabcentral/fileexchange/68493-robust-2d-phase-unwrapping-algorithm.

In this article, the spin-dependent electronic and transport properties of the armchair boron–phosphorous nanoribbons (ABPNRs) are mainly studied by using the non-equilibrium Green function method combined with the spin-polarized density function theory. Our calculated electronic structures indicate that the edge hydrogenated ABPNRs exhibit a ferromagnetic bipolar magnetic semiconductor property, and that the Si atom doping can make ABPNRs convert into up-spin dominated half metal. The spin-resolved transport property results show that the doped devices can realize 100% spin-filtering function, and that the interesting negative differential resistance phenomenon can be observed. Our calculations suggest that the ABPNRs can be constructed as a spin heterojunction by introducing Si doping partially, and it would be used as a spin-diode for nano-spintronics in future.

This paper starts with the importance of public resource transaction, enumerates the current situation of large data application in the field of public resource transaction, analyzes the significance and function of big data application in this field, gives the big data application prospect of public resource transaction, proposes the general framework and technology overview of large data application based on public resource transaction management, and points out that the public resource transaction based on big data is the future direction of development.

Phase-shifting fringe projection profilometry (PSFPP) is a three-dimensional (3D) measurement technique widely adopted in industry measurement. It recovers the 3D profile of measured objects with the aid of the fringe phase. The phase accuracy is among the dominant factors that determine the 3D measurement accuracy. Evaluation of the phase accuracy helps refine adjustable measurement parameters, contributes to evaluating the 3D measurement accuracy, and facilitates improvement of the measurement accuracy. Although PSFPP has been deeply researched, an effective, easy-to-use phase accuracy evaluation method remains to be explored. In this paper, methods based on the uniform-phase coded image (UCI) are presented to accomplish phase accuracy evaluation for PSFPP. These methods work on the principle that the phase value of a UCI can be manually set to be any value, and once the phase value of a UCI pixel is the same as that of a pixel of a corresponding sinusoidal fringe pattern, their phase accuracy values are approximate. The proposed methods provide feasible approaches to evaluating the phase accuracy for PSFPP. Furthermore, they can be used to experimentally research the property of the random and gamma phase errors in PSFPP without the aid of a mathematical model to express random phase error or a large-step phase-shifting algorithm. In this paper, some novel and interesting phenomena are experimentally uncovered with the aid of the proposed methods.

With economy's continuous rapid growth, textile industry is required to search for new rules and adjust strategies in order to optimize industrial structure and rationalize social spending. The sustainable development of China's textile industry is a comprehensive research subject. This study analyzed the status of China's textile industry and constructed the evaluation model based on the economical, ecologic, and social benefits. Analytic Hierarchy Process (AHP) and Data Envelopment Analysis (DEA) were used for an empirical study of textile industry. The result of evaluation model suggested that the status of the textile industry has become the major problems in the sustainable development of China's textile industry. It's nearly impossible to integrate into the global economy if no measures are taken. The enterprises concerned with the textile industry status should be reformed in terms of product design, raw material selection, technological reform, technological progress, and management, in accordance with the ideas and requirements of sustainable development. The results of this study are benefit for 1) discover the main elements restricting the industry's sustainable development; 2) seek for corresponding solutions for policy formulation and implementation of textile industry; 3) provide references for enterprises' development transformation in strategic deployment, fund allocation, and personnel assignment.