XTEM STUDY ON ION PLATED STAINLESS STEEL MULTI-LAYER FILMS

In this paper, the cross sectional microstructure and crystal structure of ion plated multi layer films of stainless steel (1Cr18Ni9Ti ) were studied by cross sectional transmission electron microscopy (XTEM). The results show that ion plated stainless steel multi layer films are fine grained double phase steel films of austenites and ferrites.Cross section film growing microstructures can be divided into three zones: fine equiaxed crystals, fine columnar crystals and coarse columnar crystals. Interfaces in multi layer films can promote fine grained growing and interrupt columnar grained growing,and improve properties of film materials.

Thermally conductive MWCNTs/Fe_(3)O_(4)/Ti_(3)C_(2)T_(x) MXene multi-layer films for broadband electromagnetic interference shielding

The Ti_(3)C_(2)T_(x)MXene is thought to be a promising candidate for next-generation electromagnetic interference(EMI) shielding materials.However,its broadband shielding capability and thermal conduction performance are insufficient to meet the growing demands.Herein,we reported a layer-by-layer composite film composed of Ti_(3)C_(2)T_(x)MXene,multi-walled carbon nanotubes(MWCNTs),and Fe_(3)O_(4)nanoparticles.Benefitting from the architecture and the synergistic effect of components,the obtained composite film exhibited high comprehensive performance.Specifically,the introduction of Fe_(3)O_(4)magnetic nanoparticles effectively reduced the impedance mismatch between the composite film and air and enhanced the magnetic loss of the composite film.The layered structure prolonged the transmission path of electromagnetic waves inside the composite film and constructed a rich conductive network,causing interfacial polarization and ohmic loss.The results indicated that the composite film(52 μm) delivered a high EMI shielding effectiveness of 49 dB in the frequency range from X-band to Ku-band.Furthermore,the MWCNTs layers in the composite films provided numerous heat transfer channels,reducing phonon scattering during heat transfer and resulting in a maximum thermal conductivity of 8.241 W/(m K).

Multi-layer structures including zigzag sculptured thin films for corrosion protection of AISI 304 stainless steel

To increase corrosion resistance of the sample,its electrical impedance must be increased.Due to the fact that electrical impedance depends on elements such as electrical resistance,capacitance,and inductance,by increasing the electrical resistance,reducing the capacitance and inductance,electrical impedance and corrosion resistance can be increased.Based on the fact that these elements depend on the type of material and the geometry of the material,multilayer structures with different geometries are proposed.For this purpose,conventional multilayer thin films,multilayer thin film including zigzag structure(zigzag 1)and multilayer thin film including double zigzag structure(zigzag 2)of manganese nitride are considered to protect AISI 304 stainless steel against corrosion in salt solution.These multilayer coatings including zigzag structures are prepared by alternately using the conventional deposition of thin film and glancing angle deposition method.After deposition,the samples are placed in a furnace under nitrogen flux for nitriding.The cross sections of the structures are observed by field emission scanning electron microscopy(FESEM).Atomic force microscope(AFM)is used to make surface analyses of the samples.The results show that the multilayer thin films including zigzag structures have smaller grains than conventional multilayer thin films,and the zigzag 2 structure has the smaller grain than the other two samples,which is attributed to the effect of shadowing and porosity on the oblique angle deposition method.Crystallography structures of the samples are studied by using x-ray diffraction(XRD)pattern and the results show that nitride phase formation in zigzag 2 structure is better than that in zigzag 1 structure and conventional multilayer thin film.To investigate the corrosion resistances of the structures,electrochemical impedance spectroscopy(EIS)and potentiodynamic polarization tests are performed.The results reveal that the multilayer thin films with zigzag structures have better corrosion protection than the conventional multilayer thin films,and the zigzag structure 2 has the smallest corrosion current and the highest corrosion resistance.The electrical impedances of the samples are investigated by simulating equivalent circuits.The high corrosion resistance of zigzag 2 structure as compared with conventional multilayer structure and zigzag 1 structure,is attributed to the high electrical impedance of the structure due to its small capacitance and high electrical resistance.Finally,the surfaces of corroded samples are observed by scanning electron microscope(SEM).

Optimization Design of the Multi-Layer Cross-Sectional Layout of An Umbilical Based on the GA-GLM

Marine umbilical is one of the key equipment for subsea oil and gas exploitation,which is usually integrated by a great number of different functional components with multi-layers.The layout of these components directly affects manufacturing,operation and storage performances of the umbilical.For the multi-layer cross-sectional layout design of the umbilical,a quantifiable multi-objective optimization model is established according to the operation and storage requirements.Considering the manufacturing factors,the multi-layering strategy based on contact point identification is introduced for a great number of functional components.Then,the GA-GLM global optimization algorithm is proposed combining the genetic algorithm and the generalized multiplier method,and the selection operator of the genetic algorithm is improved based on the steepest descent method.Genetic algorithm is used to find the optimal solution in the global space,which can converge from any initial layout to the feasible layout solution.The feasible layout solution is taken as the initial value of the generalized multiplier method for fast and accurate solution.Finally,taking umbilicals with a great number of components as examples,the results show that the cross-sectional performance of the umbilical obtained by optimization algorithm is better and the solution efficiency is higher.Meanwhile,the multi-layering strategy is effective and feasible.The design method proposed in this paper can quickly obtain the optimal multi-layer cross-sectional layout,which replaces the manual design,and provides useful reference and guidance for the umbilical industry.

Significantly Improved High-Temperature Energy Storage Performance of BOPP Films by Coating Nanoscale Inorganic Layer

Biaxially oriented polypropylene(BOPP)is one of the most commonly used commercial capacitor films,but its upper operating temperature is below 105℃due to the sharply increased electrical conduction loss at high temperature.In this study,growing an inorganic nanoscale coating layer onto the BOPP film's surface is proposed to suppress electrical conduction loss at high temperature,as well as increase its upper operating temperature.Four kinds of inorganic coating layers that have different energy band structure and dielectric property are grown onto the both surface of BOPP films,respectively.The effect of inorganic coating layer on the high-temperature energy storage performance has been systematically investigated.The favorable coating layer materials and appropriate thickness enable the BOPP films to have a significant improvement in high-temperature energy storage performance.Specifically,when the aluminum nitride(AIN)acts as a coating layer,the AIN-BOPP-AIN sandwich-structured films possess a discharged energy density of 1.5 J cm^(-3)with an efficiency of 90%at 125℃,accompanying an outstandingly cyclic property.Both the discharged energy density and operation temperature are significantly enhanced,indicating that this efficient and facile method provides an important reference to improve the high-temperature energy storage performance of polymer-based dielectric films.

Multi-layer perceptron-based data-driven multiscale modelling of granular materials with a novel Frobenius norm-based internal variable

One objective of developing machine learning(ML)-based material models is to integrate them with well-established numerical methods to solve boundary value problems(BVPs).In the family of ML models,recurrent neural networks(RNNs)have been extensively applied to capture history-dependent constitutive responses of granular materials,but these multiple-step-based neural networks are neither sufficiently efficient nor aligned with the standard finite element method(FEM).Single-step-based neural networks like the multi-layer perceptron(MLP)are an alternative to bypass the above issues but have to introduce some internal variables to encode complex loading histories.In this work,one novel Frobenius norm-based internal variable,together with the Fourier layer and residual architectureenhanced MLP model,is crafted to replicate the history-dependent constitutive features of representative volume element(RVE)for granular materials.The obtained ML models are then seamlessly embedded into the FEM to solve the BVP of a biaxial compression case and a rigid strip footing case.The obtained solutions are comparable to results from the FEM-DEM multiscale modelling but achieve significantly improved efficiency.The results demonstrate the applicability of the proposed internal variable in enabling MLP to capture highly nonlinear constitutive responses of granular materials.

Flexible, Transparent and Conductive Metal Mesh Films with Ultra‑High FoM for Stretchable Heating and Electromagnetic Interference Shielding

Despite the growing demand for transparent conductive films in smart and wearable electronics for electromagnetic interference(EMI)shielding,achieving a flexible EMI shielding film,while maintaining a high transmittance remains a significant challenge.Herein,a flexible,transparent,and conductive copper(Cu)metal mesh film for EMI shielding is fabricated by self-forming crackle template method and electroplating technique.The Cu mesh film shows an ultra-low sheet resistance(0.18Ω□^(-1)),high transmittance(85.8%@550 nm),and ultra-high figure of merit(>13,000).It also has satisfactory stretchability and mechanical stability,with a resistance increases of only 1.3%after 1,000 bending cycles.As a stretchable heater(ε>30%),the saturation temperature of the film can reach over 110°C within 60 s at 1.00 V applied voltage.Moreover,the metal mesh film exhibits outstanding average EMI shielding effectiveness of 40.4 dB in the X-band at the thickness of 2.5μm.As a demonstration,it is used as a transparent window for shielding the wireless communication electromagnetic waves.Therefore,the flexible and transparent conductive Cu mesh film proposed in this work provides a promising candidate for the next-generation EMI shielding applications.

Target Controllability of Multi-Layer Networks With High-Dimensional Nodes

This paper studies the target controllability of multilayer complex networked systems,in which the nodes are highdimensional linear time invariant(LTI)dynamical systems,and the network topology is directed and weighted.The influence of inter-layer couplings on the target controllability of multi-layer networks is discussed.It is found that even if there exists a layer which is not target controllable,the entire multi-layer network can still be target controllable due to the inter-layer couplings.For the multi-layer networks with general structure,a necessary and sufficient condition for target controllability is given by establishing the relationship between uncontrollable subspace and output matrix.By the derived condition,it can be found that the system may be target controllable even if it is not state controllable.On this basis,two corollaries are derived,which clarify the relationship between target controllability,state controllability and output controllability.For the multi-layer networks where the inter-layer couplings are directed chains and directed stars,sufficient conditions for target controllability of networked systems are given,respectively.These conditions are easier to verify than the classic criterion.

A flexible ultra-broadband multi-layered absorber working at 2 GHz-40 GHz printed by resistive ink

A flexible extra broadband metamaterial absorber(MMA)stacked with five layers working at 2 GHz–40 GHz is investigated.Each layer is composed of polyvinyl chloride(PVC),polyimide(PI),and a frequency selective surface(FSS),which is printed on PI using conductive ink.To investigate this absorber,both one-dimensional analogous circuit analysis and three-dimensional full-wave simulation based on a physical model are provided.Various crucial electromagnetic properties,such as absorption,effective impedance,complex permittivity and permeability,electric current distribution and magnetic field distribution at resonant peak points,are studied in detail.Analysis shows that the working frequency of this absorber covers entire S,C,X,Ku,K and Ka bands with a minimum thickness of 0.098λ_(max)(λ_(max) is the maximum wavelength in the absorption band),and the fractional bandwidth(FBW)reaches 181.1%.Moreover,the reflection coefficient is less than-10 dB at 1.998 GHz–40.056 GHz at normal incidence,and the absorptivity of the plane wave is greater than 80%when the incident angle is smaller than 50°.Furthermore,the proposed absorber is experimentally validated,and the experimental results show good agreement with the simulation results,which demonstrates the potential applicability of this absorber at 2 GHz–40 GHz.

Dynamic Multi-Layer Perceptron for Fetal Health Classification Using Cardiotocography Data

Fetal health care is vital in ensuring the health of pregnant women and the fetus.Regular check-ups need to be taken by the mother to determine the status of the fetus’growth and identify any potential problems.To know the status of the fetus,doctors monitor blood reports,Ultrasounds,cardiotocography(CTG)data,etc.Still,in this research,we have considered CTG data,which provides information on heart rate and uterine contractions during pregnancy.Several researchers have proposed various methods for classifying the status of fetus growth.Manual processing of CTG data is time-consuming and unreliable.So,automated tools should be used to classify fetal health.This study proposes a novel neural network-based architecture,the Dynamic Multi-Layer Perceptron model,evaluated from a single layer to several layers to classify fetal health.Various strategies were applied,including pre-processing data using techniques like Balancing,Scaling,Normalization hyperparameter tuning,batch normalization,early stopping,etc.,to enhance the model’s performance.A comparative analysis of the proposed method is done against the traditional machine learning models to showcase its accuracy(97%).An ablation study without any pre-processing techniques is also illustrated.This study easily provides valuable interpretations for healthcare professionals in the decision-making process.

Effects of Thickness and Anisotropic Strain on Polarization Switching Properties of Sub-10nm Epitaxial Hf_(0.5)Zr_(0.5)O_(2)Thin Films

Doped HfO_(2)-based ferroelectric(FE)films are emerging as leading contenders for next-generation FE nonvolatile memories due to their excellent compatibility with complementary metal oxide semiconductor processes and robust ferroelectricity at nanoscale dimensions.Despite the considerable attention paid to the FE properties of HfO_(2)-based films in recent years,enhancing their polarization switching speed remains a critical research challenge.We demonstrate the strong ferroelectricity of sub-10nm Hf_(0.5)Zr_(0.5)O_(2)(HZO)thin films and show that the polarization switching speed of these thin films can be significantly affected by HZO thickness and anisotropically strained La_(0.67)Sr_(0.33)MO_(3)-buffered layer.Our observations indicate that the HZO thin film thickness and anisotropically strained La_(0.67)Sr_(0.33)MO_(3)layer influence the nucleation of reverse domains by altering the phase composition of the HZO thin film,thereby reducing the polarization switching time.Although the increase in HZO thickness and anisotropic compressive strain hinder the formation of the FE phase,they can enable faster switching.Our findings suggest that FE HZO ultrathin films with polar orthorhombic structures have broad application prospects in microelectronic devices.These insights into novel methods for increasing polarization switching speed are poised to advance the development of high-performance FE devices.

Centimeter-Scale Above-Room-Temperature Ferromagnetic Fe_(3)GaTe_(2)Thin Films by Molecular Beam Epitaxy

Fe_(3)GaTe_(2),as a layered ferromagnetic material,has a Curie temperature(T_(c))higher than room temperature,making it the key material in next-generation spintronic devices.To be used in practical devices,large-sized high-quality Fe_(3)GaTe_(2)thin films need to be prepared.Here,the centimeter-scale thin film samples with high crystal quality and above-room-temperature ferromagnetism with strong perpendicular magnetic anisotropy were prepared by molecular beam epitaxy technology.Furthermore,the Tc of the samples raises as the film thickness increases,and reaches 367K when the film thickness is 60 nm.This study provides material foundations for the new generation of van der Waals spintronic devices and paves the way for the commercial application of Fe_(3)GaTe_(2).

Multi-layer network embedding on scc-based network with motif

Interconnection of all things challenges the traditional communication methods,and Semantic Communication and Computing(SCC)will become new solutions.It is a challenging task to accurately detect,extract,and represent semantic information in the research of SCC-based networks.In previous research,researchers usually use convolution to extract the feature information of a graph and perform the corresponding task of node classification.However,the content of semantic information is quite complex.Although graph convolutional neural networks provide an effective solution for node classification tasks,due to their limitations in representing multiple relational patterns and not recognizing and analyzing higher-order local structures,the extracted feature information is subject to varying degrees of loss.Therefore,this paper extends from a single-layer topology network to a multi-layer heterogeneous topology network.The Bidirectional Encoder Representations from Transformers(BERT)training word vector is introduced to extract the semantic features in the network,and the existing graph neural network is improved by combining the higher-order local feature module of the network model representation network.A multi-layer network embedding algorithm on SCC-based networks with motifs is proposed to complete the task of end-to-end node classification.We verify the effectiveness of the algorithm on a real multi-layer heterogeneous network.

Ultrathin Limit on the Anisotropic Superconductivity of Single-Layered Cuprate Films

Exploring dimensionality effects on cuprates is important for understanding the nature of high-temperature superconductivity.By atomically layer-by-layer growth with oxide molecular beam epitaxy,we demonstrate that La_(2−x)Sr_(x)CuO_(4)(x=0.15)thin films remain superconducting down to 2 unit cells of thickness but quickly reach the maximum superconducting transition temperature at and above 4 unit cells.By fitting the critical magnetic field(μ0H_(c2)),we show that the anisotropy of the film’s superconductivity increases with decreasing film thickness,indicating that the superconductivity of the film gradually evolves from weak three-to two-dimensional character.These results are helpful to gain more insight into the nature of high-temperature superconductivity with dimensionality.

Dynamic interwell connectivity analysis of multi-layer waterflooding reservoirs based on an improved graph neural network

The analysis of interwell connectivity plays an important role in the formulation of oilfield development plans and the description of residual oil distribution. In fact, sandstone reservoirs in China's onshore oilfields generally have the characteristics of thin and many layers, so multi-layer joint production is usually adopted. It remains a challenge to ensure the accuracy of splitting and dynamic connectivity in each layer of the injection-production wells with limited field data. The three-dimensional well pattern of multi-layer reservoir and the relationship between injection-production wells can be equivalent to a directional heterogeneous graph. In this paper, an improved graph neural network is proposed to construct an interacting process mimics the real interwell flow regularity. In detail, this method is used to split injection and production rates by combining permeability, porosity and effective thickness, and to invert the dynamic connectivity in each layer of the injection-production wells by attention mechanism.Based on the material balance and physical information, the overall connectivity from the injection wells,through the water injection layers to the production layers and the output of final production wells is established. Meanwhile, the change of well pattern caused by perforation, plugging and switching of wells at different times is achieved by updated graph structure in spatial and temporal ways. The effectiveness of the method is verified by a combination of reservoir numerical simulation examples and field example. The method corresponds to the actual situation of the reservoir, has wide adaptability and low cost, has good practical value, and provides a reference for adjusting the injection-production relationship of the reservoir and the development of the remaining oil.

Target layer state estimation in multi-layer complex dynamical networks considering nonlinear node dynamics

In many engineering networks, only a part of target state variables are required to be estimated.On the other hand,multi-layer complex network exists widely in practical situations.In this paper, the state estimation of target state variables in multi-layer complex dynamical networks with nonlinear node dynamics is studied.A suitable functional state observer is constructed with the limited measurement.The parameters of the designed functional observer are obtained from the algebraic method and the stability of the functional observer is proven by the Lyapunov theorem.Some necessary conditions that need to be satisfied for the design of the functional state observer are obtained.Different from previous studies, in the multi-layer complex dynamical network with nonlinear node dynamics, the proposed method can estimate the state of target variables on some layers directly instead of estimating all the individual states.Thus, it can greatly reduce the placement of observers and computational cost.Numerical simulations with the three-layer complex dynamical network composed of three-dimensional nonlinear dynamical nodes are developed to verify the effectiveness of the method.

Effect of drying methods on perovskite films and solar cells

The high efficiency,solution processibility,and flexibility of perovskite solar cells make them promising candidates for the photovoltaic industry[1−8].The deposition method is one of the most critical factors that affect the performance of perovskite films.Various deposition methods have been developed to make perovskite films,including spin-coating,slotdie coating.

Multi-layer phenomena in petawatt laser-driven acceleration of heavy ions

Laser-accelerated high-flux-intensity heavy-ion beams are important for new types of accelerators.A particle-in-cell program(Smilei) is employed to simulate the entire process of Station of Extreme Light(SEL) 100 PW laser-accelerated heavy particles using different nanoscale short targets with a thickness of 100 nm Cr, Fe, Ag, Ta, Au, Pb, Th and U, as well as 200 nm thick Al and Ca. An obvious stratification is observed in the simulation. The layering phenomenon is a hybrid acceleration mechanism reflecting target normal sheath acceleration and radiation pressure acceleration, and this phenomenon is understood from the simulated energy spectrum,ionization and spatial electric field distribution. According to the stratification, it is suggested that high-quality heavy-ion beams could be expected for fusion reactions to synthesize superheavy nuclei. Two plasma clusters in the stratification are observed simultaneously, which suggest new techniques for plasma experiments as well as thinner metal targets in the precision machining process.

A Well Productivity Model for Multi-Layered Marine and Continental Transitional Reservoirs with Complex Fracture Networks

Using the typical characteristics of multi-layered marine and continental transitional gas reservoirs as a basis,a model is developed to predict the related well production rate.This model relies on the fractal theory of tortuous capillary bundles and can take into account multiple gas flow mechanisms at the micrometer and nanometer scales,as well as the flow characteristics in different types of thin layers(tight sandstone gas,shale gas,and coalbed gas).Moreover,a source-sink function concept and a pressure drop superposition principle are utilized to introduce a coupled flow model in the reservoir.A semi-analytical solution for the production rate is obtained using a matrix iteration method.A specific well is selected for fitting dynamic production data,and the calculation results show that the tight sandstone has the highest gas production per unit thickness compared with the other types of reservoirs.Moreover,desorption and diffusion of coalbed gas and shale gas can significantly contribute to gas production,and the daily production of these two gases decreases rapidly with decreasing reservoir pressure.Interestingly,the gas production from fractures exhibits an approximately U-shaped distribution,indicating the need to optimize the spacing between clusters during hydraulic fracturing to reduce the area of overlapping fracture control.The coal matrix water saturation significantly affects the coalbed gas production,with higher water saturation leading to lower production.

The role of polyurethane foam compressible layer in the mechanical behaviour of multi-layer yielding supports for deep soft rock tunnels

The polyurethane foam(PU)compressible layer is a viable solution to the problem of damage to the secondary lining in squeezing tunnels.Nevertheless,the mechanical behaviour of the multi-layer yielding supports has not been thoroughly investigated.To fill this gap,large-scale model tests were conducted in this study.The synergistic load-bearing mechanics were analyzed using the convergenceconfinement method.Two types of multi-layer yielding supports with different thicknesses(2.5 cm,3.75 cm and 5 cm)of PU compressible layers were investigated respectively.Digital image correlation(DIC)analysis and acoustic emission(AE)techniques were used for detecting the deformation fields and damage evolution of the multi-layer yielding supports in real-time.Results indicated that the loaddisplacement relationship of the multi-layer yielding supports could be divided into the crack initiation,crack propagation,strain-hardening,and failure stages.Compared with those of the stiff support,the toughness,deformability and ultimate load of the yielding supports were increased by an average of 225%,61%and 32%,respectively.Additionally,the PU compressible layer is positioned between two primary linings to allow the yielding support to have greater mechanical properties.The analysis of the synergistic bearing effect suggested that the thickness of PU compressible layer and its location significantly affect the mechanical properties of the yielding supports.The use of yielding supports with a compressible layer positioned between the primary and secondary linings is recommended to mitigate the effects of high geo-stress in squeezing tunnels.