Monodispersed, biocompatible, and readily-functionalized hybrid reporter-embedded core-shell nanopartilces (NPs) have been prepared in a simple route. This composite offers a potential platform for immunochemical detection using surface-enhanced Raman scattering (SERS) due to their high sensitivity, good stability and biocompatiblity. This also provides a new platform for insight into SERS enhancement mechanism.
We propose an in-fiber Michelson-Fabry-Perrot (M-FP) hybrid interferometer for the simultaneous measurement of seawater temperature and salinity. The sensor head consists of two parallel hetero Fabry-Perot (FP) cavities fabricated on the end face of the twin core fiber (TCF). A fiber fusion taper is used to split and recouple the light in the two cores. In this case, the Vernier effect can be obtained which can greatly enhance the sensitivity and solve the problem of temperature cross-sensitivity. Different from the traditional demodulation method based on envelop detection, we employed frequency domain decomposition method (FDDM) to demodulate the sensing signal. The simulation results indicate that the proposed sensor has high sensitivity to salinity and temperature. Thanks to the merits of high sensitivity, ease of fabrication and small footprint, the proposed seawater temperature and salinity sensor would have potential applications in marine science, food industry and ocean ranching.
In this investigation, all-optical Toggle flip-flop event-driven memory is explored with data rate of 16 Gbit/s. Single mode optical fiber model is used as a nonlinear medium to generate the output set and reset pulses of a Toggle flip-flop, and the model is based on the bidirectional optical transmission principle, considering the fundamental effects of cross phase modulation and self-phase modulation with change in polarization state. The performance of a flip-flop is evaluated using truth table conditions and performance parameters such as Q factor, which is obtained as 380.92 dB for Q and 272.9 dB for , and rising and falling times of 7.304 ps and 5.79 ps, respectively are obtained, which makes flip-flop design fast as compared to earlier design techniques.
One of the essential parts of a wind power generator that captures wind energy is the wind turbine blade. The safety of the blades rapidly declines as a wind turbine’s operating period grows. For real-time monitoring, a chip-type pre-stressed fiber Bragg grating (FBG) strain sensor was fabricated. The sensor’s structure was improved using simulation analysis along with optimization. It was discovered through calibration trials that the pre-stressing method expanded the sensor’s range of measurement, guaranteed overall linearity, and prevented the potential hysteresis phenomena during compression. The sensor’s final sensitivity was calculated to be 1.970 pm/µε, and its linear fitting coefficient was 0.999. Finally, the sensor was used to monitor the wind turbine blades and the strain change curve of the root of a normally functioning blade is found to be a sine curve, which provides a certain reference value for judging whether the blade is damaged in the future.
To improve the internal quantum efficiency (IQE) and light output power of InGaN light-emitting diodes (LEDs), we proposed an In-composition gradient increase and decrease InGaN quantum barrier structure. Through analysis of its P-I graph, carrier concentration, and energy band diagram, the results showed that when the current was 100 mA, the In-composition gradient decrease quantum barrier (QB) structure could effectively suppress electron leakage while improving hole injection efficiency, resulting in an increase in carrier concentration in the active region and an improvement in the effective recombination rate in the quantum well (QW). As a result, the IQE and output power of the LED were effectively improved.
We have experimentally observed a new operating state of a regular pulse train in a narrow-band optoelectronic oscillator (OEO) system, where the direct-current (DC) bias of the Mach-Zehnder modulator is set at the maximum value of the transmission transfer function instead of the usual quadrature point. The observed quasi-steady-state pulse train is distinctly periodic, with a period of 10.5 µs and a center frequency of 10 GHz, and resembles a mode-locked OEO in its waveform. The formation of regular pulses here may arise from the dynamic balance of nonlinearity and narrow-band filter effects, with the transient characteristics of the pulses arising mainly from instabilities between the gain and cavity loss. Our results are of great importance for deepening the understanding of the nonlinear dynamical processes in OEO systems.
To evaluate the impact of zinc sulfate (ZnSO4) concentration on the structural properties of the films, Cd1−xZn xS thin films were formed on glass substrates using chemical bath deposition (CBD) in this study. The effect of ZnSO4 precursor concentration on the surface morphology, optical properties, and morphological structure of the Cd1−xZn xS films was investigated. To study the impact of zinc doping content on the performance metrics of Cu(In1−xGa x)Se2 (CIGS) cells in the experimental group and to improve the buffer layer thickness, simulations were run using one-dimensional solar cell capacitance simulator (SCAPS-1D) software.
An improved ensemble empirical mode decomposition (IEEMD) is suggested to process water quality spectral signals in order to address the issue that noise interference makes it difficult to extract and evaluate water quality spectral signals. This algorithm effectively solves the problems of modal mixing, poor reconstruction accuracy in the empirical mode decomposition (EMD), and a large amount of calculation in the ensemble empirical mode decomposition (EEMD). Based on EEMD, IEEMD firstly preprocesses the original water quality spectral signals, then performs Savitzky-Golay (S-G) smoothing on the decomposed effective intrinsic mode function (IMF) components, and finally reconstructs them to obtain the denoised signals. Water sample data at different concentrations can be accurately analyzed based on the noise-reduced spectral signals. In this paper, three water quality parameters are used as research objects: benzene (C6H6), benzo(b)fluoranthene (C20H12), and chemical oxygen demand (COD). The original water quality multi-parameter (C6H6, C20H12, COD) spectral signals were subjected to denoising based on the IEEMD and the water quality multi-parameter joint detection technology. The signal-to-noise ratio (SNR) and the correlation coefficient (R 2) of the fitted curves obtained from the processing of the IEEMD were compared and analyzed with those obtained from the processing of the EMD and the EEMD. The experimental results show that the SNR of the spectral signals and the R 2 of the fitting curve in three water quality parameters have been significantly improved. Therefore, the IEEMD effectively improves the phenomenon of modal mixing, reduces the amount of calculation, improves the reconstruction accuracy, and provides an important guarantee for the effective extraction of multi-parameter spectral signals of water quality.
In this work, laser-induced breakdown spectroscopy (LIBS) was applied for the detection of Pb in Tieguanyin tea and ash. Firstly, the Tieguanyin tea and ash containing Pb were prepared, and the difference of intensities of Pb I spectral lines before and after the ashing treatment was studied. It was found that the intensities of Pb I lines increased by 30 times and the standard deviation of background signal decreased by 41% after the ashing treatment. Therefore, the enrichment of Pb element by ashing treatment was used to detect Pb in tea with high sensitivity. Then, the calibration curve of Pb was established using spectral lines without self-absorption, and the determination coefficient (R 2) for the linear fitting of calibration curve was 0.979 9. Finally, it was found that the limit of detection of Pb was 233.8 ppb. Compared with the results of other works which detect Pb directly, the enrichment of Pb by ashing treatment improved the detection sensitivity of Pb by about 200 times. In addition, this method can be applied to the high sensitivity detection of other heavy metals, such as Cr, Cd, Hg, etc in plants, Chinese herbal medicine, flour, rice, coal and other solid materials.
In response to the high complexity and low accuracy of current facial expression recognition networks, this paper proposes an E-MobileNeXt network for facial expression recognition. E-MobileNeXt is built based on our proposed E-SandGlass block. In addition, we also improve the overall performance of the network through RepConv and SGE attention mechanisms. The experimental results show that the network model improves the expression recognition accuracy by 6.5% and 7.15% in RAF-DB and CK+ datasets, respectively, while the parameter and floating-point operations decreased by 0.79 M and 4.2 M compared with MobileNeXt.