Spatial electron-spin splitting in single-layered semiconductor microstructure modulated by Dresselhaus spin-orbit coupling

Combining theory and computation,we explore the Goos–H¨anchen(GH)effect for electrons in a single-layered semiconductor microstructure(SLSM)modulated by Dresselhaus spin–orbit coupling(SOC).GH displacement depends on electron spins thanks to Dresselhaus SOC,therefore electron spins can be separated from the space domain and spinpolarized electrons in semiconductors can be realized.Both the magnitude and sign of the spin polarization ratio change with the electron energy,in-plane wave vector,strain engineering and semiconductor layer thickness.The spin polarization ratio approaches a maximum at resonance;however,no electron-spin polarization occurs in the SLSM for a zero in-plane wave vector.More importantly,the spin polarization ratio can be manipulated by strain engineering or semiconductor layer thickness,giving rise to a controllable spatial electron-spin splitter in the field of semiconductor spintronics.

RESEARCH ON IMPERFECTION SENSITIVE REGION OF SINGLE-LAYER LATTICED DOMES

The concept of the imperfection sensitive region is given. The advanced stochastic imperfection method is used to research the imperfection sensitive region of single-layer latticed domes. Taking a K6 single-layer latticed dome with a diameter of 50 m as an example, its imperfection sensitive region is made up of the first 12 kinds of joints. The influence of the imperfections of support joints on the stability of the K6 single-layer latticed dome is negligible. Influences of the joint imperfections of the main rib and the secondary rib on the structural stability are similar. The initial deviations of these joints all greatly lower the critical load of the dome. Results show that the method can analyze the structural imperfection sensitive region quantitatively and accurately.

Superconducting Single-Layer T-Graphene and Novel Synthesis Routes

Single-layer superconductors are ideal materials for fabricating superconducting nano devices.However,up to date,very few single-layer elemental superconductors have been predicted and especially no one has been successfully synthesized yet.Here,using crystal structure search techniques and ab initio calculations,we predict that a single-layer planar carbon sheet with 4-and 8-membered rings called T-graphene is a new intrinsic elemental superconductor with superconducting critical temperature(Tc)up to around 20.8 K.More importantly,we propose a synthesis route to obtain such a single-layer T-graphene,that is,a T-graphene potassium intercalation compound(C4 K with P4/mmm symmetry)is firstly synthesized at high pressure(>11.5 GPa)and then quenched to ambient condition;and finally,the single-layer T-graphene can be either exfoliated using the electrochemical method from the bulk C4 K,or peeled off from bulk T-graphite C4,where C4 can be obtained from C4 K by evaporating the K atoms.Interestingly,we find that the calculated Tc of C4 K is about 30.4 K at 0 GPa,which sets a new record for layered carbon-based superconductors.The present findings add a new class of carbon-based superconductors.In particular,once the single-layer T-graphene is synthesized,it can pave the way for fabricating superconducting devices together with other 2 D materials using the layer-by-layer growth techniques.

Dynamic behavior of single-layer latticed cylindrical shells subjected to seismic loading

The single-layer latticed cylindrical shell is one of the most widely adopted space-fl'amed structures.In this paper,free vibration properties and dynamic response to horizontal and vertical seismic waves of single-layer latticed cylindrical shells are analyzed by the finite element method using ANSYS software.In the numerical study,where hundreds of cases were analyzed,the parameters considered included rise-span ratio,length-span ratio,surface load and member section size.Moreover,to better define the actual behavior of single-layer latticed shells,the study is focused on the dynamic stress response to both axial forces and bending moments.Based on the numerical results,the effects of the parameters considered on the stresses are discussed and a modified seismic force coefficient method is suggested.In addition,some advice based on these research results is presented to help in the future design of such structures.

Ultra-thin circularly polarized lens antenna based on single-layered transparent metasurface

Circularly polarized （CP） lens antenna has been applied to numerous wireless communication systems based on its unique advantages such as high antenna gain, low manufacturing cost, especially stable data transmission between the transmitter and the receiver. Unfortunately, current available CP lens antennas mostly suffer from high profile, low aperture efficiency as well as complex design. In this paper, we propose an ultra-thin CP lens antenna based on the designed single- layered Pancharatnam-Berry （PB） transparent metasurface with focusing property. The PB metasurface exhibits a high transmissivity, which ensures a high efficiency of the focusing property. Launched the metasurface with a CP patch antenna at its focal point, a low-profile lens antenna is simulated and measured. The experimental results show that our lens antenna exhibits a series of advantages including high radiation gain of 20.7 dB, aperture efficiency better than 41.3%, and also narrow half power beam width （HPBW） of 13°at about 14GHz. Our finding opens a door to realize ultra-thin transparent metasurface with other functionalities or at other working frequencies.

Single-layer graphene as a highly selective barrier for vanadium crossover with high proton selectivity

We report near-zero crossover for vanadium cross-permeation through single-layer graphene immobilized at the interface of two Nafion?polymer electrolyte membranes.Vanadium ion diffusion and migration,including proton mobility through membrane composites,were studied with and without graphene under diffusion and migration conditions.Single-layer graphene was found to effectively inhibit vanadium ion diffusion and migration under specific conditions.The single-layer graphene composites also enabled remarkable ion transmission selectivity improvements over pure Nafion membranes,with proton transport being four orders of magnitude faster than vanadium ion transport.Resistivity values of 0.02±0.005Ωcm^(2) for proton and 223±4Ωcm^(2) for vanadium ion through single atomic layer graphene are reported.This high selectivity may have significant impact on flow battery applications or for other electrochemical devices where proton conductivity is required,and transport of other species is detrimental.Our results emphasize that crossover may be essentially completely eliminated in some cases,enabling for greatly improved operational viability.

Damage mechanism of single-layer reticulated domes under severe earthquakes

To study the damage mechanism of single-layer reticulated domes subject to severe earthquakes, three limit states of single-layer reticulated domes under earthquakes are defined firstly in this paper. Then, two failure modes are presented by analyzing damage behaviors, and their characteristics are pointed out respectively. Furthermore, the damage process is analyzed and the causes of structural damage in different levels are studied. Finally, by comparing deformation and vibration status of domes with different failure modes, the principles of different failures are revealed and an integrated frame of damage mechanism is set up.

Gap opening and tuning in single-layer graphene with combined electric and magnetic field modulation

The energy band structure of single-layer graphene under one-dimensional electric and magnetic field modulation is theoretically investigated. The criterion for bandgap opening at the Dirac point is analytically derived with a two-fold degeneracy second-order perturbation method. It is shown that a direct or an indirect bandgap semiconductor could be realized in a single-layer graphene under some specific configurations of the electric and magnetic field arrangement. Due to the bandgap generated in the single-layer graphene, the Klein tunneling observed in pristine graphene is completely suppressed.

Preliminary analysis of mode truncation of single-layered reticulated domes under earthquakes

In anti-seismic calculation, the mode truncation is a significant problem to engineers if the mode-superposition response spectrum method is used, which has not been completely solved yet in some large and complex structures such as reticulated domes. In this case, some useful advices, concentrating on the problem above, are expected through a careful and comprehensive investigation of this paper. During the investigation, the authors first point out shortcomings of former researches. Then frequency-spectrum characteristics of single-layered reticulated domes were studied from the perspective of structural responses. During this process, some important results such as the existence of the main resonant section, and the fact that the relative sensitivity of these domes under horizontal and vertical impulse varies with the different R/S ratios were achieved. Furthermore, based on the study of frequency-spectrum characteristics, as well as that of earthquake input, reasonable numbers of mode truncation in single layered reticulated domes with different R/S ratio were presented. Results of case studies prove the mode truncation number proposed is valid.

Nanoscale mass sensing based on vibration of single-layered graphene sheet in thermal environments

Based on vibration analysis, single-layered graphene sheet （SLGS） with multiple attached nanoparticles is developed as nanoscale mass sensor in thermal environments. Graphene sensors are assumed to be in simplysupported configuration. Based on the nonlocal plate the- ory which incorporates size effects into the classical theory, closed-form expressions lot the frequencies and relative fre- quency shills of SLGS-based mass sensor are derived using the Galerkin method. The suggested model is justified by a good agreement between the results given by the present model and available data in literature. The effects of tem- perature difference, nonlocal parameter, the location of the nanoparticle and the number of nanoparticles on the relative frequency shift of the mass sensor are also elucidated. The obtained results show that the sensitivity of the SLGS- based mass sensor increases with increasing temperature difference.

Theoretical Proposal for a Planar Single-Layer Carbon That Shows a Potential in Superconductivity

Single-layer superconductors[1]have been the subject of considerable interests as they are ideal systems for the fundamental understanding of two-dimensional(2D)physics and for device applications.A few singlelayer superconductors are experimentally achieved(e.g.,FeSe,MoS2,and NbSe2[2-4]in the field where either charge doping or tensile strain is often required to promote the superconductivity.

Electronic Structures and Optical Properties of Ga Doped Single-Layer Indium Nitride

Electronic structures and optical properties of single-layer In1-xGaxN are studied by employing Heyd-Scuseria-Ernzerh（HSE） method based on the first-principles. The band structure and density of states（DOS） of single-layer In1-xGaxN are calculated, and the band gap ranges from 1.8 eV to 3.8 eV as the ratio x changes, illustrating the potential for the tunability of band gap values via Ga doped. We also have investigated optical properties of single-layer In1-xGaxN such as dielectric function, refractive index and absorption coefficient, the main peak of dielectric function spectrum and the absorption edge are found to have a remarkable blue-shift as the concentration of Ga increases. Furthermore, the optical properties of single-layer In1-xGaxN are analyzed based on the band structures and DOS analysis. Such unique optical properties have profound application in nanoelectronics and optical devices.

Deposition mechanism of nano-structured single-layered C_(36) film on a diamond (100) crystal plane

The Brenner-LJ potential is adopted to describe the interaction between C36 clusters and diamond surface, and the deposition mechanism of multi-C36 clusters on the diamond surface is also studied by using the method of molecular dynamics simulation. The simulation results show that the competition effects of two interactions, i.e. the interaction between cluster and cluster and the interaction between cluster and crystal plane, are studied, and then the influence of these competition effects on C36 cluster deposition is analysed. The finding is that when an incident energy is appropriately chosen, C36 clusters can be chemically adsorbed and deposited steadily on the diamond surface in the form of single-layer, and in the deposition process the multi-C36 clusters present a phenomenon of energy transmission. The experimental result shows that at a temperature of 300K, in order to deposit C36 clusters into a steady nanostructured single-layered film, the optimal incident energy is between 10 and 18 eV, if the incident energy is larger than 18 eV, the C36 clusters will be deposited into an island nano-structured film.

On hydraulic falls of single-layer flow

Hydraulic falls of single-layer now are determined theoretically in terms of a time-dependent averaged fKdV equation(AfKdV equation)in phase coordinate. From the theory of the present paper it was known that difference of the asymptotic mean levels upstream and downsream at the subcritical cutoff points is just equal to a subcritical value of the AfKdV equation An experiment is carried out to examine the theoretical results. From comparison between theoreticaland experimental results, it was shown that they are in good agreement.At the same time, it should be pointed out that the theory of the present paper is agreement with the experimental and numerical results of Forbes and can be employed to find the generating properties of the precursor solitons at near-resonance.

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.

Magnetic phase diagram of single-layer CrBr_(3)

We theoretically provide a magnetic phase diagram for the single-layer(SL)CrBr_(3),which could be effectively tuned by both strain engineering and charge doping in SL-CrBr_(3).Through systematical first-principles calculations and Heisenberg model Hamiltonian simulations,three different magnetic phases in SL-CrBr_(3),which are off-plane ferromagnetic,in-plane ferromagnetic and in-plane Neél-antiferromagnetic phases,are found in the strain and charge doping regimes we studied.Furthermore,our results show that higher order Heisenberg exchange parameters and anisotropy exchange parameters should be taken into account for accurately illustrating the magnetic phase transition in SL-CrBr_(3).As a result,we find from the SpinW simulation that the Curie temperature is about T_(c)=38.4 K,which is well consistent with the experimental result 34 K[Nano Lett.193138(2019)].The findings here may be confirmed in future experiments,and may be useful for the potential applications of SL-CrBr_(3)in spintronics field.

Lower Bounds of Decay Rates for Solution to the Single-Layer Quasi-Geostrophic Model

In this paper, we study the long-time behavior of solutions of the single-layer quasi-geostrophic model arising from geophysical fluid dynamics. We obtain the lower bound of the decay estimate of the solution. Utilizing the Fourier splitting method, under suitable assumptions on the initial data, for any multi-index α, we show that the solution Ψ satisfies .

Lowering the Operational Voltage of Single-Layer Polymer Electroluminescent Devices by Using CuO_x Modifying Indium-Tin Oxide Electrode

In this study it is demonstrated that oxygen-plasma-generated CuOx can enhance the holes injection from ITO anode into polymer layer in single-layer polymer EL devices. The possible reason for this enhancement is because the ITO anode modified with CuOx possesses much higher work function than pure ITO anode, which reduces the barrier for hole-injection and further lowers the operational voltage of the polymer EL devices. The work function shift is probable due to the oxygen-plasma-generated CuOx can store more releasable oxygen, and the releasable oxygen in turn changes the oxygen concentration just near ITO surface, which will shift the work function of ITO anode.

Recommendation System Based on Perceptron and Graph Convolution Network

The relationship between users and items,which cannot be recovered by traditional techniques,can be extracted by the recommendation algorithm based on the graph convolution network.The current simple linear combination of these algorithms may not be sufficient to extract the complex structure of user interaction data.This paper presents a new approach to address such issues,utilizing the graph convolution network to extract association relations.The proposed approach mainly includes three modules:Embedding layer,forward propagation layer,and score prediction layer.The embedding layer models users and items according to their interaction information and generates initial feature vectors as input for the forward propagation layer.The forward propagation layer designs two parallel graph convolution networks with self-connections,which extract higher-order association relevance from users and items separately by multi-layer graph convolution.Furthermore,the forward propagation layer integrates the attention factor to assign different weights among the hop neighbors of the graph convolution network fusion,capturing more comprehensive association relevance between users and items as input for the score prediction layer.The score prediction layer introduces MLP(multi-layer perceptron)to conduct non-linear feature interaction between users and items,respectively.Finally,the prediction score of users to items is obtained.The recall rate and normalized discounted cumulative gain were used as evaluation indexes.The proposed approach effectively integrates higher-order information in user entries,and experimental analysis demonstrates its superiority over the existing algorithms.

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.