Abstract:In this work, the TiO2/Sb2S3 nanorod arrays (NRAs) were synthesized through a two-stage hydrothermal route for photoelectrochemical (PEC) water splitting. The effect of annealing treatment in Ar ambience on the PEC activity of TiO2/Sb2S3 composite sample was investigated by electrochemical impedance analysis, including Nyquist and Mott-Schottky (M-S) plots. It was demonstrated that vacuum annealing could crystallize Sb2S3 component and change its color from red to black, leading to an increment of photocurrent density from 1.9 A/m2 to 4.25 A/m2 at 0 V versus saturated calomel electrode (VSCE). The enhanced PEC performance was mainly attributed to the improved visible light absorption. Moreover, annealing treatment facilitated retarding the electron-hole recombination occurred at the solid/liquid interfaces. Our work might provide a novel strategy for enhancing the PEC performance of a semiconductor electrode.

Abstract:Cu2ZnSn(S,Se)4 (CZTSSe) is considered to be the most potential light-absorbing material to replace CuInGaSe2 (CIGS), but the actual photoelectric conversion efficiency of such cells is much lower than that of CIGS. One of the reasons is the high recombination rate of carriers at the interface. In this paper, in order to reduce the carrier recombination, a new solar cell structure with double absorber layers of Al-doped ZnO (AZO)/intrinsic (i)-ZnO/CdS/ CZTSx1Se1-x1 (CZTSSe1)/CZTSx2Se1-x2 (CZTSSe2)/Mo was proposed, and the optimal conduction band offsets (CBOs) of CdS/CZTSSe1 interface and CZTSSe1/CZTSSe2 interface were determined by changing the S ratio in CZTSSe1 and CZTSSe2, and the effect of thickness of CZTSSe1 on the performance of the cell was studied. The efficiencies of the optimized single and double absorber layers reached 17.97% and 23.4%, respectively. Compared with the single absorber layer structure, the proposed structure with double absorber layers has better cell performance.

Abstract:In this study, we design and numerically investigate a novel all optical D flip-flop (AODFF) based on linear photonic crystal (LPhC) structure that is composed of optical waveguides using the finite difference time domain (FDTD) method. The proposed structure has the hexagonal close packed of 16×20 circular rods that are suspended in the air substrate with a lattice constant of 606 nm. The plane wave expansion (PWE) method is used to obtain the band diagram for AODFF at an operating wavelength of 1 550 nm. The proposed optical flip-flop achieves a low delay time of 0.2 ps and a high contrast ratio (CR) of 10.33 dB. The main advantage of this design is that the input power as low as 1 mW/µm2 is sufficient for its operation, since no nonlinear rods are included. In addition, the footprint of the proposed AODFF is 100 µm2, which is smaller compared to the structures reported in the literature, and it has a fast switching frequency of 5 Tbit/s.

Abstract:This study begins with the fabrication and simulation of high-performance back-illuminated AlGaN-based solar-blind ultraviolet (UV) photodetectors. Based on the photodetectors, a low-noise, high-gain UV detection system circuit is designed and fabricated, enabling the detection, acquisition, and calibration of weak solar-blind UV signals. Experimental results demonstrate that under zero bias conditions, with a UV light power density of 3.45 μW/cm2 at 260 nm, the sample achieves a peak responsivity (R) of 0.085 A∙W-1, an external quantum efficiency (EQE) of 40.7%, and a detectivity (D) of 7.46×1012 cm.Hz1/2.W-1. The system exhibits a bandpass characteristic within the 240—280 nm wavelength range, coupled with a high signal-to-noise ratio (SNR) of 39.74 dB.

Abstract:The semiconductor bridge (SCB) ignites through bridge film discharge, offering advantages such as low ignition energy, high safety, and compatibility with digital logic circuits. The study uses laser interferometry to investigate the gas dynamics of the bridge film after SCB plasma extinction. Interferometric images of the SCB film gas were obtained through a laser interferometry optical path. After the degradation model of digital image processing, clearer images were produced to facilitate analysis and calculation. The results show that the gas temperature at the center of the SCB film reaches a maximum of 1 000 K, and the temperature rapidly decreases along the axial direction of the bridge surface to room temperature at 300 K. The maximum diffusion velocity of the plasma is 1.8 km/s. These findings provide critical insights for SCB design and ignition control.

Abstract:Quantum dots (QDs) can modulate the solar spectrum through the down-conversion mechanism to better match the spectral response of solar cells. Following previous work, this paper first tested the response of QD solar cells to specific monochromatic light, and found that QDs can effectively improve the photoelectric conversion efficiency (PCE) in the ultraviolet (UV) band by comparison. Then the photoelectric properties of the QD solar cells are tested under the air-mass 1.5 (AM1.5) and air-mass 0 (AM0) spectra. The experimental results show that because the absorption band of QDs is in the UV region, the space solar cells in the AM0 spectrum can obtain better PCE after coating QDs. The research results show the technical route of space solar cells with down-conversion mechanism, and put forward an important direction for the application of space solar photovoltaic (PV) technology, and have a good application prospect.

Abstract:This paper presents a photonic crystal (PhC) line-defect slow-light waveguide modified by resonant rings. We introduce resonant rings into the line defect, constructing a slow-light waveguide with high normalized delay bandwidth product (NDBP) and low group velocity dispersion (GVD). We simulate, analyze, and optimize the structural parameters of this slow-light waveguide using the finite difference time domain (FDTD) method, theoretically achieving a maximum group index of 3.7, maximum bandwidth of 15.6 nm, and maximum NDBP of 0.441 6 for slow-light effect. The resonant ring-modified PhC slow-light waveguide designed in this paper exhibits GVD lower than the order of 10-20 s2/m over a normalized frequency range from 0.355 4 to 0.417 5. This study is expected to provide theoretical references for the study of slow-light buffering devices based on PhCs with high NDBP values.

Abstract:Aiming at the problem that the bit error rate (BER) of asymmetrically clipped optical orthogonal frequency division multiplexing (ACO-OFDM) space optical communication system is significantly affected by different turbulence intensities, the deep learning technique is proposed to the polarization code decoding in ACO-OFDM space optical communication system. Moreover, this system realizes the polarization code decoding and signal demodulation without frequency conduction with superior performance and robustness compared with the performance of traditional decoder. Simulations under different turbulence intensities as well as different mapping orders show that the convolutional neural network (CNN) decoder trained under weak-medium-strong turbulence atmospheric channels achieves a performance improvement of about 102 compared to the conventional decoder at 4-quadrature amplitude modulation (4QAM), and the BERs for both 16QAM and 64QAM are in between those of the conventional decoder.

Abstract:Convolutional neural networks (CNNs) exhibit superior performance in image feature extraction, making them extensively used in the area of traffic sign recognition. However, the design of existing traffic sign recognition algorithms often relies on expert knowledge to enhance the image feature extraction networks, necessitating image preprocessing and model parameter tuning. This increases the complexity of the model design process. This study introduces an evolutionary neural architecture search (ENAS) algorithm for the automatic design of neural network models tailored for traffic sign recognition. By integrating the construction parameters of residual network (ResNet) into evolutionary algorithms (EAs), we automatically generate lightweight networks for traffic sign recognition, utilizing blocks as the fundamental building units. Experimental evaluations on the German traffic sign recognition benchmark (GTSRB) dataset reveal that the algorithm attains a recognition accuracy of 99.32%, with a mere 2.8×106 parameters. Experimental results comparing the proposed method with other traffic sign recognition algorithms demonstrate that the method can more efficiently discover neural network architectures, significantly reducing the number of network parameters while maintaining recognition accuracy.

Abstract:To enhance the denoising performance of event-based sensors, we introduce a clustering-based temporal deep neural network denoising method (CBTDNN). Firstly, to cluster the sensor output data and obtain the respective cluster centers, a combination of density-based spatial clustering of applications with noise (DBSCAN) and Kmeans++ is utilized. Subsequently, long short-term memory (LSTM) is employed to fit and yield optimized cluster centers with temporal information. Lastly, based on the new cluster centers and denoising ratio, a radius threshold is set, and noise points beyond this threshold are removed. The comprehensive denoising metrics F1_score of CBTDNN have achieved 0.893 1, 0.773 5, and 0.921 5 on the traffic sequences dataset, pedestrian detection dataset, and turntable dataset, respectively. And these metrics demonstrate improvements of 49.90%, 33.07%, 19.31%, and 22.97% compared to four contrastive algorithms, namely nearest neighbor (NNb), nearest neighbor with polarity (NNp), Autoencoder, and multilayer perceptron denoising filter (MLPF). These results demonstrate that the proposed method enhances the denoising performance of event-based sensors.