Abstract:A theoretical model concerning active Q-switching of an Fe:ZnSe laser pumped by a continuous-wave (CW) 2.8 μm fiber laser is developed. Calculations are compared with the recently reported experiment results, and good agreement is achieved. Effects of principal parameters, including pump power, output reflectivity, ion concentration and temperature of crystal, on the laser output performance are investigated and analyzed. Numerical results demonstrate that similar to highly efficient CW Fe:ZnSe laser, low temperature of the crystal is significant to obtain high peak power Q-switched pulses. The numerical simulation results are useful for optimizing the design of actively Q-switched Fe:ZnSe laser.

Abstract:In this paper, a lifted Haar transform (LHT) image compression optical chip has been researched to achieve rapid image compression. The chip comprises 32 same image compression optical circuits, and each circuit contains a 2×2 multimode interference (MMI) coupler and a π/2 delay line phase shifter as the key components. The chip uses highly borosilicate glass as the substrate, Su8 negative photoresist as the core layer, and air as the cladding layer. Its horizontal and longitudinal dimensions are 8 011 μm×10 000 μm. Simulation results present that the designed optical circuit has a coupling ratio (CR) of 0:100 and an insertion loss (IL) of 0.001 548 dB. Then the chip is fabricated by femtosecond laser and testing results illustrate that the chip has a CR of 6:94 and an IL of 0.518 dB. So, the prepared chip possesses good image compression performance.

Abstract:A numerical simulation model of plenoptic sensor aberration wavefront detection is established to simulate and analyze the detection performance of plenoptic sensor aberration wavefront for different turbulence intensities. The results show that the plenoptic sensor can achieve better distortion wavefront detection, and its wavefront detection accuracy improves with turbulence intensity. The unique optical structure design of the plenoptic sensor makes it more suitable for aberration wavefront detection in strong turbulent conditions. The wavefront detection performance of the plenoptic sensor is not only related to its wavefront reconstruction algorithm but also closely related to its structural parameter settings. The influence of structural parameters on the wavefront detection accuracy of plenoptic sensors under different turbulence intensities is simulated and analyzed. The variation law of wavefront detection accuracy and structural parameters under different turbulence intensities is summarized to provide a reference for the structural design and parameter optimization of plenoptic sensors.

Abstract:Copper antimony selenium (CuSbSe2) has advantages of adjustable band gaps from 1.09 eV to 1.2 eV, high light absorption coefficient (>105 cm-1), and low grain generation temperature (300—400 °C), which is suitable for the preparation of solar cells. However, the stable range of CuSbSe2 (CASe) phase is narrow, which is inevitable to form Sb2Se3 and Cu3SbSe4 second phase during the preparation process. In this work, selenization annealing of Sb/Cu metal layer to prepare CASe thin films with pulse electrodeposition process was studied, and the growth mechanism of CASe film was analyzed. Cu and Sb reacted with Se to form Cu2Se and Sb2Se3, respectively. Then Cu2Se and Sb2Se3 further reacted to generate CASe. Since the formation temperature of Cu3SbSe4 was lower than that of CASe, the preferential formation of Cu3SbSe4 led to layer separation. When the annealing temperature was too high, CASe decomposed to form Cu3SbSe3 and Sb2Se3. Additionally, by increasing the heating rate, the separation of CASe thin films was effectively improved, and the CASe thin films with relatively high crystallinity were obtained at 360 °C with heating rate of 30 °C/min and selenization time of 20 min.

Abstract:Ultrafast optical nonlinearities of N,N-dimethylformamide (DMF) are studied by using polarized light at 400 nm. Both nonlinear refraction (NLR) and stimulated Rayleigh-wing scattering (SRWS) depend on the polarization state of incident beam, while two-photon absorption (TPA) changes negligibly with polarization state. The polarization dependence of SRWS originates from that of NLR via self-focusing effect. Third-order susceptibility elements of DMF were determined, and a method to distinguish the multi-photon absorption signal from SRWS in Z-scan is provided. These results are helpful for the nonlinear optical research of the novel materials dissolved in DMF.

Abstract:LiNi0.8Co0.1Mn0.1O2 cathode material is prepared by sol-gel method and the effects of Nb5+ doping and different calcination temperatures on cathode materials were deeply investigated. Structural and morphological characterizations revealed that the optimal content of 1 mol% Nb5+ can stabilize layered structures, mitigate Ni2+ migration to Li layers, improve lithium diffusion capacity, and reduce lattice expansion/shrinkage while cycling. And calcination temperature at 800 °C can not only ensure good morphology, but also suppress the mixed discharge of lithium and nickel in the internal structure. Electrochemical performance evaluation revealed that Nb5+ doping improves the discharge-specific capacity of the material, which is conducive to ameliorating its rate capability and cycle performance. And the material at 800 °C exhibits the highest discharge specific capacity, the best magnification performance, low polarizability, and the best cycle reversibility.

Abstract:Phase unwrapping is one of the key roles in fringe projection three-dimensional (3D) measurement technology. We propose a new method to achieve phase unwrapping in camera array light filed fringe projection 3D measurement based on deep learning. A multi-stream convolutional neural network (CNN) is proposed to learn the mapping relationship between camera array light filed wrapped phases and fringe orders of the expected central view, and is used to predict the fringe order to achieve the phase unwrapping. Experiments are performed on the light field fringe projection data generated by the simulated camera array fringe projection measurement system in Blender and by the experimental 3×3 camera array light field fringe projection system. The performance of the proposed network with light field wrapped phases using multiple directions as network input data is studied, and the advantages of phase unwrapping based on deep learning in light filed fringe projection are demonstrated.

Abstract:Aiming at the approximate measurement of magnetic rotation angle in optical current sensor based on light intensity detection mode, this paper proposes a current measurement method based on triangular constant transformation to reconstruct magnetic rotation angle, so as to avoid the large current measurement error caused by the approximate measurement of the magnetic rotation angle. By extracting the direct current (DC) component and the alternating current (AC) component of the light intensity signal detected by the photoelectric detector (PD), the sine signal containing the magnetic rotation angle is directly obtained by dividing the two components, and then the triangular identity transformation method is used to linearly demodulate the magnetic rotation angle and reconstruct the current waveform. The experimental results show that the relative error of current measurement does not exceed 1.40% in the current range of 0.05—0.50 A, which is less than the approximate linear measurement (ALM) method, and the magnetic rotation angle and the current have a good linear relationship.

Abstract:Video summarization aims at selecting valuable clips for browsing videos with high efficiency. Previous approaches typically focus on aggregating temporal features while ignoring the potential role of visual representations in summarizing videos. In this paper, we present a global difference-aware network (GDANet) that exploits the feature difference across frame and video as guidance to enhance visual features. Initially, a difference optimization module (DOM) is devised to enhance the discriminability of visual features, bringing gains in accurately aggregating temporal cues. Subsequently, a dual-scale attention module (DSAM) is introduced to capture informative contextual information. Eventually, we design an adaptive feature fusion module (AFFM) to make the network adaptively learn context representations and perform feature fusion effectively. We have conducted experiments on benchmark datasets, and the empirical results demonstrate the effectiveness of the proposed framework.