Showing papers by "Shanghai University published in 2022"

Investigation of terahertz high Q-factor of all-dielectric metamaterials

Abstract: We investigated the propagation properties of all-dielectric metamaterials (ADMs) based on a SiO2-Si asymmetric hybrid block, including the effects of structural parameters, asymmetrical degrees, carrier doping concentrations, and graphene Fermi levels. The Q-factor of Fano resonance reaches more than 270, and the amplitude modulation depth (MD) is about 75% if the asymmetric degree changes in the range of 2–10 μm. The carrier concentration of silicon significantly affects the intensity of excited Fano resonance. When the carrier concentration of Si is 1 × 1014 cm−3, the excited Fano resonance is the strongest, and the transmission peak is about 0.92. With the help of a uniform graphene layer, the Fano resonance can be effectively modulated, the frequency MD is about 20% if the Fermi level changes in the scope of 0.01–0.3 eV. These results can help us to design THz high Q-factor devices, such as sensors, filters, and modulators.

Improving Dendritic Neuron Model With Dynamic Scale-Free Network-Based Differential Evolution

Abstract: Some recent research reports that a dendritic neuron model (DNM) can achieve better performance than traditional artificial neuron networks (ANNs) on classification, prediction, and other problems when its parameters are well-tuned by a learning algorithm. However, the back-propagation algorithm (BP), as a mostly used learning algorithm, intrinsically suffers from defects of slow convergence and easily dropping into local minima. Therefore, more and more research adopts non-BP learning algorithms to train ANNs. In this paper, a dynamic scale-free network-based differential evolution (DSNDE) is developed by considering the demands of convergent speed and the ability to jump out of local minima. The performance of a DSNDE trained DNM is tested on 14 benchmark datasets and a photovoltaic power forecasting problem. Nine meta-heuristic algorithms are applied into comparison, including the champion of the 2017 IEEE Congress on Evolutionary Computation (CEC2017) benchmark competition effective butterfly optimizer with covariance matrix adapted retreat phase (EBOwithCMAR). The experimental results reveal that DSNDE achieves better performance than its peers.

Cooperatively enhanced coking resistance via boron nitride coating over Ni-based catalysts for dry reforming of methane

Abstract: Dry reforming of methane provides a feasible solution to reduce the greenhouse gas via simultaneously converting CH4 and CO2 into useful syngas. However, conventional Ni-based catalysts suffer from deactivation due to serious carbon coking during dry reforming of methane process. Herein, we propose a concept by reducing crystallinity of formed carbon and accelerating carbon oxidization to enhance the coking resistance of Ni-based catalysts. This concept was conducted through a boron nitride coating strategy over reducible oxides supported Ni catalysts, in which the increased carbon diffusion barrier, induced by the boron nitride coating, would lead to more amorphous carbon. While the amorphous carbon was efficiently gasified by active oxygen species derived from reducible oxides. Our findings demonstrate that the coke issues can be solved by building a dynamic carbon removal route.

Experimental characteristics and coupled nonlinear forced vibrations of axially travelling hyperelastic beams

Abstract: Comprehensively investigated in this paper is the coupled nonlinear dynamics of hyperelastic beams. Experimental testing is performed to accurately model the hyperelasticity using different hyperelastic energy density models. Samples were fabricated using 3D printing technique for flexible thermoplastic polyurethane filaments following the ASTM D638 guidance and tested using a tensile testing machine. For a proper hyperelastic energy density model, coupled nonlinear equations of motion are obtained via the von Karman geometrical nonlinearity and Hamilton’s principle. Free natural vibration response of the gyroscopic system is analysed using a generalised modal decomposition method and the influence of different parameters such as the hyperelastic stiffness term and the axial velocity on the natural frequencies is investigated. Complex mode shapes are obtained and the influence of axial velocity on altering the real and imaginary parts is discussed. Furthermore, a comprehensive analysis on the coupled nonlinear dynamics of the system is presented using a combination of Galerkin’s scheme and a dynamic equilibrium technique. The frequency response to different design parameters such as axial speed, axial tension, harmonic external load, hyperelastic parameters and geometrical imperfection is discussed in detail. It is shown that the system shows a wide range of rich nonlinear dynamics including hardening depending on the characteristics of the system.

Ultralow detection limit MEMS hydrogen sensor based on SnO2 with oxygen vacancies

Abstract: Controllable and efficient construction of oxygen vacancies on the surface of metal oxide semiconductors (MOSs) is essential for their application in the gas sensor. Herein, a general H2 reduction method is developed to synthesize SnO2 with oxygen vacancies defect (SnO2-D) by annealing the SnO2 in a H2 atmosphere at different temperature (300 °C, 400 °C and 500 °C), and then named SnO2-D3, SnO2-D4 and SnO2-D5, respectively. It was found that although the determined specific surface areas for pristine SnO2, SnO2-D3, SnO2-D4 and SnO2-D5 are 103.749 m2g−1, 63.316 m2g−1, 47.652 m2g−1 and 15.541 m2g−1, respectively, the gas sensitivity test results indicate that the SnO2-D4 Micro-Electro-Mechanical System (MEMS) sensor shows improved response and excellent low-concentration detection capability (down to 0.1 ppm) to H2 compared with that fabricated with pristine SnO2, SnO2-D3 and SnO2-D5. The abnormal relationship between specific surface area and gas sensing performance is attributed to the more oxygen vacancies of SnO2-D4 surface. In addition, ZnO (ZnO-D) and In2O3 (In2O3-D) with oxygen vacancy defects based on the H2 reduction method show better gas sensitivity than ZnO and In2O3 sensors, which further proves that oxygen vacancy defects can effectively improve the gas-sensing performance of MOSs.

Propagating Seismic Waves in VTI Attenuating Media Using Fractional Viscoelastic Wave Equation

Abstract: Seismic velocity and attenuation anisotropy are ubiquitous in the crust and upper mantle, significantly modulating the characteristics of seismic wave propagation in the Earth's interior. Accurate seismic wave modeling of velocity and attenuation anisotropy is essential for the understanding of wave propagation in the Earth's interior as well as constructing global and region-scale seismic full waveform tomography. Here, we derive a decoupled fractional Laplacian (DFL) viscoelastic wave equation to characterize the Earth's frequency-independent Q behavior in the vertical transversely isotropic (VTI) media. We verify the accuracy of the proposed viscoelastic wave equation by 2D synthetic examples; to show its applicability in crustal-scale seismic modeling, we present an example of 3D seismic wave propagation in the realistic Salton Trough model. Through extensive numerical tests, we conclude that the proposed viscoelastic wave equation is superior in four aspects. First, the viscoelastic wave equation takes VTI anisotropy of both velocity and attenuation into account and can describe the strong direction-dependent attenuation. Second, our derivation contains spatially independent Laplacians, and thus the proposed wave equation enjoys higher simulation accuracy for heterogeneous Q media. Third, the new viscoelastic wave equation can decouple the amplitude decay and the phase distortion, which is appealing for improving the resolution in seismic imaging and inversion. Lastly, compared to viscoelastic wave equations with time-fractional operators, our scheme has higher computational efficiency by avoiding substantial wavefield storage.

Simultaneously enhanced strength-ductility of AlCoCrFeNi2.1 eutectic high-entropy alloy via additive manufacturing

Abstract: The negative effects of thermal cycles in the process of additive manufacture present a challenge for the control of microstructure so as to fabricate the products with improved properties compared with conventional casting technique. In this work, AlCoCrFeNi2.1 eutectic high-entropy alloy (EHEA) was prepared by laser metal deposition (LMD). Compared with conventionally cast EHEA samples, the LMD-fabricated EHEA samples showed significantly enhanced tensile strength (by 19.7%) and increased tensile ductility (by 56.4%). Such enhancement in tensile properties was attributed to the refinement of the uniformly distributed eutectic-structure, which improved the strain hardening/dislocation accumulation capability of the EHEA. The present work provides a new strategy to utilize both the high cooling rates of LMD and the eutectic-structure characteristics for forming refined homogeneous structures and thus achieving superior mechanical properties to those prepared by traditional processing techniques.