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By combining the excellent surface-enhanced Raman scattering (SERS) activity of Ag nanoparticles (AgNPs), the well-separated pyramid arrays of the pyramidal silicon (PSi) and unique physical/chemical properties of molybdenum disulfide (MoS2), the MoS2@AgNPs@PSi substrate shows high performance in terms of sensitivity, uniformity, reproducibility and stability. By using rhodamine 6G (R6G) as probe molecule, the SERS results indicate that the MoS2@AgNPs@PSi substrate is superior to the AgNPs@PSi, AgA@PSi (the second annealing of the AgNPs@PSi) and the MoS2@AgNPs@flat-Si substrate. The MoS2@AgNPs@PSi substrate also shows the reasonable linear response between the Raman intensity and R6G concentration. The maximum deviations of SERS intensities from 20 positions on a same MoS2@AgNPs@PSi substrate and 10 MoS2@AgNPs@PSi substrates in different batches are less than 7.6% and 9%, respectively, revealing the excellent uniformity and reproducibility of the substrate. Besides, the SERS substrate has a good stability, the Raman intensity of the MoS2@AgNPs@PSi substrate only drop by 15% in a month. The corresponding experimental and theoretical results suggest that our proposed MoS2@AgNPs@PSi substrate is expected to offer a new and practical way to accelerate the development of label-free SERS detection.

A facile fabrication of high-quality and large-area tungsten disulfide (WS2) layers is demonstrated using a thermal decomposition of tetrathiotungstates ((NH4)2WS4) with two annealing process. During synthesis, the first annealing step is utilized to achieve lateral epitaxial growth of the WS2 and create seamless and large-area WS2 film. The second annealing step can offer an S-rich and high temperature condition, which is beneficial for the high quality of the WS2 film. Scanning electron microscopy, Raman spectroscopy and atomic force microscopy confirm the presence of large-area and high-quality WS2 film. The crucial role of the S, H2 and the effect of the temperature during the experiment are also investigated. Furthermore, the potential application of the prepared WS2 as a substrate for Raman enhancement is first discussed using R6G molecules as probe molecule.

In this work, we present a novel optical fiber SERS (OF-SERS) sensor based on a sandwich structure of GO/AgNPs/rGO. Rhodamine 6G (R6G) was selected as the probe molecule to compare the SERS ability of different films composed of the bare optical fiber, GO, AgNPs, rGO/AgNPs, GO/AgNPs and GO/AgNPs/rGO. Raman spectra, scanning electron microscopy (SEM), atomic force microscopy (AFM), energy dispersive spectroscopy (EDS) and X-ray photoelectron spectroscopy (XPS) were performed to characterize the sandwich structure hybrid films. Besides, the stability of GO/AgNPs and GO/AgNPs/rGO was compared on the optical fiber end face. The OF-SERS sensor based GO/AgNPs/rGO hybrid films had stable SERS performance even when exposed to ambient conditions for a prolonged time of 30 days. This work may provide a new strategy for an efficient stable OF-SERS sensor due to its simplicity, low-cost and long-term stability.

In this paper, we designed a 2D distance and rotation angle plasmon ruler based on Fano resonance of a trimer nanostructure, which consists of a concentric square nanoring–disk and an outside nanorod (CSRDR). The Fano dip energy and depth are fairly sensitive to the nanometer-scale displacements and rotations, when the nanodisk moves in all direction and rotates around its center. When the symmetry of the nanoring is broken, we can identify the moving and rotating direction of the nanodisk more accurately. We use the CSRDR nanostructure which supports a narrow line-width as a 2D plasmon ruler, which can enhance the sensitivity of a plasmon ruler significantly.

In our work, we directly synthesized few layer MoS2 on a pyramid-Si substrate to fabricate a surface-enhanced Raman scattering (SERS) substrate via thermally decomposing the precursor of ammonium thiomolybdate ((NH4)2MoS4). Scanning electron microscopy (SEM), atomic force microscopy (AFM), X-ray diffraction (XRD) and Raman spectra are employed to characterize the as-grown MoS2 layers. Adenosine and cytidine were selected as the probe molecules to investigate the SERS ability of the MoS2-pyramid-Si substrate, and have shown that the MoS2-pyramid-Si substrate can prominently suppress photobleaching and fluorescence of the probe molecule. Compared with the MoS2-flat-Si substrate (MoS2 layers synthesized on flat-Si substrate), the MoS2-pyramid-Si substrate has more significant SERS ability. The minimum detected concentration of both adenosine and cytidine on the MoS2-pyramid-Si substrate can reach 10−6 M. Importantly, the linear relationship between the Raman intensity and the concentration of adenosine or cytidine can apply to the bimolecular detection. This work may provide a new opportunity for the study of the chemistry mechanism (CM) and novel SERS substrate fabrication.

Aiming at the problem that the satellite navigation and positioning system can not cover the whole area and that the positioning accuracy of the existing ground-based reinforcement system decreases with the increase of the distance between the target and the ground station, a method for optimizing the positioning system of mobile ground station based on whale optimization algorithm is proposed. Based on the mobile ground station, the method identifies the positioning target with the optimal whale individual and the mobile ground station with other whale individuals, realizes that the position of the ground station varies with the position of the target point, and ensures the high precision positioning of the target in area with weak signals or without satellite navigation and without the support of the enhanced system. The feasibility of this method is proved by MATLAB, which provides a new way of thinking for solving the problem of regional target location.

Aiming at the problems of the difficulty to establish the model and the large data dimension for the traditional integrated navigation method, a method of using the wavelet neural network to directly predict the position and velocity error information is proposed. Get rid of the mathematical model establishment, void introducing new errors in the model establishment, and adopt multiple parallel networks to reduce the dimensionality of the data, which greatly reduces the amount of calculation. The Kalman filter is used as a reference for simulation experiment. The results show that the proposed method can effectively improve the accuracy and real-time performance of the integrated navigation system, and provides a new feasible path for combined navigation filtering.