An Ultra-wide-band Tightly Coupled Dipole Reflectarray Antenna

A novel ultra-wide-band tightly coupled dipole reflectarray (TCDR) antenna is presented in this paper. This reflectarray antenna consists of a wide-band feed and a wide-band reflecting surface. The feed is a log-periodic dipole array antenna. The reflecting surface consists of 26×11 unit cells. Each cell is composed of a tightly coupled dipole and a delay line. The minimum distance between adjacent cells is 8mm, which is about 1/10 wavelength at the lowest operating frequency. By combining the advantages of reflectarray antennas and those of tightly coupled array antennas, the proposed TCDR antenna achieves ultra-wide bandwidth with reduced complexity and fabrication cost. A method to minimize the phase errors of the wideband reflectarray is also developed and a concept of “equivalent distance delay” is introduced to design the unit cell elements. To verify the simulations, a prototype operating from 3.4 to 10.6 GHz is simulated and fabricated. Good agreement between simulated and measured results is observed. Within the designed frequency band, the radiation pattern of the TCDR antenna is stable and the main beam of the antenna is not distorted or split. The side lobe levels of the radiation patterns are below -11.7 dB and the cross-polarization levels are below -20 dB in the entire operating band. This TCDR antenna combines the reflectarray and tightly coupled arrays for the 1st time and achieves the widest bandwidth (in terms of stable radiation patterns and low sidelobes) reported so far. This work is expected to have significant impact on antenna development for broadband satellite communications and the base stations in 5G mobile communications

Hybrid GRU-CNN Bilinear Parameters Initialization for Quantum Approximate Optimization Algorithm

The Quantum Approximate Optimization Algorithm (QAOA), a pivotal paradigm in the realm of variational quantum algorithms (VQAs), offers promising computational advantages for tackling combinatorial optimization problems. Well-defined initial circuit parameters, responsible for preparing a parameterized quantum state encoding the solution, play a key role in optimizing QAOA. However, classical optimization techniques encounter challenges in discerning optimal parameters that align with the optimal solution. In this work, we propose a hybrid optimization approach that integrates Gated Recurrent Units (GRU), Convolutional Neural Networks (CNN), and a bilinear strategy as an innovative alternative to conventional optimizers for predicting optimal parameters of QAOA circuits. GRU serves to stochastically initialize favorable parameters for depth-1 circuits, while CNN predicts initial parameters for depth-2 circuits based on the optimized parameters of depth-1 circuits. To assess the efficacy of our approach, we conducted a comparative analysis with traditional initialization methods using QAOA on Erd\H{o}s-R\'enyi graph instances, revealing superior optimal approximation ratios. We employ the bilinear strategy to initialize QAOA circuit parameters at greater depths, with reference parameters obtained from GRU-CNN optimization. This approach allows us to forecast parameters for a depth-12 QAOA circuit, yielding a remarkable approximation ratio of 0.998 across 10 qubits, which surpasses that of the random initialization strategy and the PPN2 method at a depth of 10. The proposed hybrid GRU-CNN bilinear optimization method significantly improves the effectiveness and accuracy of parameters initialization, offering a promising iterative framework for QAOA that elevates its performance

Polarization-Reconfigurable Circularly Polarized Planar Antenna Using Switchable Polarizer

A novel polarization-reconfigurable planar antenna is presented. The antenna consists of an electronically reconfigurable polarizer integrated with a printed slot. By changing the states of the PIN diodes on the polarizer, the linearly polarized (LP) waves radiated by the slot can be converted to either right-hand circularly polarized (RHCP) or left-hand circularly polarized (LHCP) waves. The polarizer contains 16 unit cells arranged as a 4 × 4 array. The antenna radiates RHCP waves if the PIN diodes on the top side of the polarizer are switched ON, while LHCP waves are radiated if the PIN diodes of the bottom side of the polarizer are switched ON instead. The physical mechanisms of the antenna are discussed and the parametric study is carried out by full-wave simulations. To verify the concept, one prototype at 2.5 GHz is designed, fabricated and measured. Good agreement between the measured and simulated results is obtained. The antenna achieves a gain ? 8.5 dBic in both RHCP and LHCP with aperture efficiency of 70%. Advantages of the proposed design include electronicallyreconfigurable polarizations for RHCP or LHCP, low profile, low cost, high isolation between the DC bias circuit and RF signals, high power handling capability and easy extension to large-scale arrays without increasing the complexity of the DC bias circuit. To the best knowledge of the authors, this is the first report of an electronically polarization-reconfigurable circularly polarized antenna with a single-substrate polarizer

Solenoid-free current drive via ECRH in EXL-50 spherical torus plasmas

As a new spherical tokamak (ST) designed to simplify engineering requirements of a possible future fusion power source, the EXL-50 experiment features a low aspect ratio (A) vacuum vessel (VV), encircling a central post assembly containing the toroidal field coil conductors without a central solenoid. Multiple electron cyclotron resonance heating (ECRH) resonances are located within the VV to improve current drive effectiveness. Copious energetic electrons are produced and measured with hard X-ray detectors, carry the bulk of the plasma current ranging from 50kA to 150kA, which is maintained for more than 1s duration. It is observed that over one Ampere current can be maintained per Watt of ECRH power issued from the 28-GHz gyrotrons. The plasma current reaches Ip>80kA for high density (>5e18me-2) discharge with 150kW ECHR heating. An analysis was carried out combining reconstructed multi-fluid equilibrium, guiding-center orbits of energetic electrons, and resonant heating mechanisms. It is verified that in EXL-50 a broadly distributed current of energetic electrons creates smaller closed magnetic-flux surfaces of low aspect ratio that in turn confine the thermal plasma electrons and ions and participate in maintaining the equilibrium force-balance

Optoelectronic Properties of MAPbBr₃ Perovskite Light-Emitting Diodes Using Anti-Solvent and PEDOT:PSS/PVK Double-Layer Hole Transport Layers

Perovskite light-emitting diodes (PeLEDs) have attracted extensive attention due to their advantages such as low-temperature solution processing, high photoluminescence quantum efficiency, high color purity, tunable wavelength, and excellent carrier mobility. The hole transport layer plays an important role in the device’s performance. In this paper, the effect of anti-solvent (ethyl acetate) on the performance of PeLEDs was studied in order to determine the optimal anti-solvent condition. The effect of PEDOT:PSS/PVK double-layer hole transport layers on the optoelectronic properties of MAPbBr3 PeLEDs was investigated. The device with 8 mg/mL PVK produced the best results, with a maximum luminance of 5139 cd/m2 and a maximum current efficiency of 2.77 cd/A. Compared with the control device with PEDOT:PSS HTL, the maximum luminance of the device with 8 mg/mL PVK is increased by 2.02 times, and the maximum current efficiency is increased by 188%. The experimental results show that the addition of PVK helps to reduce the size of perovskite particles, contributing to the spatial confinement of excitons, and suppress the quenching of luminescence occurring at the interface between PEDOT:PSS and MAPbBr3, thereby enhancing the optoelectronic performance of PeLEDs. The results of this paper can provide a basis for the improvement and industrialization of PeLEDs

The Optuna–LightGBM–XGBoost Model: A Novel Approach for Estimating Carbon Emissions Based on the Electricity–Carbon Nexus

With the challenge posed by global warming, accurately estimating and managing carbon emissions becomes a key step for businesses, especially power generation companies, to reduce their environmental impact. Optuna–LightGBM–XGBoost, a novel power and carbon emission relationship model that aims to improve the efficiency of carbon emission monitoring and estimation for power generation companies, is proposed in this paper. Deeply exploring the intrinsic link between power production data and carbon emissions, this model paves a new path for “measuring carbon through electricity”, in contrast to the emission factor method commonly used in China. Unit data from power generation companies are processed into structured tabular data, and a parallel processing framework is constructed with LightGBM and XGBoost, and optimized with the Optuna algorithm. The multilayer perceptron (MLP) is used to fuse features to enhance prediction accuracy by capturing characters that the individual models cannot detect. Simulation results show that Optuna–LightGBM–XGBoost can achieve better performance compared to existing methods. The mean absolute error (MAE), mean squared error (MSE), mean absolute percentage error (MAPE), and coefficient of determination (R2) of the model are 0.652, 0.939, 0.136, and 0.994, respectively. This not only helps governments and enterprises to develop more scientific and reasonable emission reduction strategies and policies, but also lays a solid foundation for achieving global carbon neutrality goals