A high-sensitivity, low-cost, ultrathin, hollow fiber micro bubble structure was proposed; such a bubble can be used to develop a high-sensitivity strain sensor based on a Fabry–Perot interferometer (FPI). The micro bubble is fabricated at the fiber tip by splicing a glass tube to a single mode fiber (SMF) and then the glass tube is filled with gas in order to expand and form a micro bubble. The sensitivity of the strain sensor with a cavity length of about 155 μm and a bubble wall thickness of about 6 μm was measured to be up to 8.14 pm/μϵ.

In this work, a biosensing method based on in situ, fast, and sensitive measurements of ellipsometric parameters (Ψ, ∆) is proposed. Bare silicon wafer substrate is functionalized and used to bind biomolecules in the solution. Coupled with a 45° dual-drive symmetric photoelastic modulator-based ellipsometry, the parameters Ψ and ∆ of biolayer arising due to biomolecular interactions are determined directly, and the refractive index (RI) of the solution and the effective thickness and surface mass density of the biolayer for various interaction time can be further monitored simultaneously. To illustrate the performance of the biosensing method, immunosensing for immunoglobulin G (IgG) was taken as a case study. The experiment results show that the biosensor response of the limit of detection for IgG is 15 ng/mL, and the data collection time is in milliseconds. Moreover, the method demonstrates a good specificity. Such technique is a promising candidate in developing a novel sensor which can realize fast and sensitive, label-free, easy operation, and cost-effective biosensing.

The fast and full range measurements of ellipsometric parameters ψ and Δ using a 45° dual-drive symmetric photoelastic modulator (PEM) are proposed. The PEM operates in a pure traveling modulation mode with a constant retardation magnitude and the modulation axis performing circular motion. A field programmable gate array is used to control the PEM and fulfill the data processing. The parameters sin 2ψ sinΔ, sin 2ψ cosΔ, and sin 2ψ can be measured simultaneously, providing accurate measurements of ψ and Δ over the full range. The experimental results show that the repeatability and sensitivity of this system are at 10^-3°, and the data acquisition rate is 1 ms/point.

Wavelength selection is an important preprocessing issue in near-infrared (NIR) spectroscopy analysis and modeling. Swarm optimization algorithms (such as genetic algorithm, bat algorithm, etc.) have been successfully applied to select the most effective wavelengths in previous studies. However, these algorithms suffer from the problem of unrobustness, which means that the selected wavelengths of each optimization are different. To solve this problem, this paper proposes a novel wavelength selection method based on the binary dragonfly algorithm (BDA), which includes three typical frameworks: single-BDA, multi-BDA, ensemble learning-based BDA settings. The experimental results for the public gasoline NIR spectroscopy dataset showed that: (1) By using the multi-BDA and ensemble learning-based BDA methods, the stability of wavelength selection can improve; (2) With respect to the generalized performance of the quantitative analysis model, the model established with the wavelengths selected by using the multi-BDA and the ensemble learning-based BDA methods outperformed the single-BDA method. The results also indicated that the proposed method is not limited to the dragonfly algorithm but can also be combined with other swarm optimization algorithms. In addition, the ensemble learning idea can be applied to other feature selection areas to obtain more robust results.

A new fiber pressure sensor is proposed and analyzed in this paper. A commercial arc fusion splicer and pressure-assisted arc discharge technology are used here to fabricate a silica hollow microbubble from a common glass tube with the characteristics of a thin film. Then the single mode fiber is embedded into the microbubble to form a fiber Fabry–Perot interferometer by measuring the reflected interference spectrum from the fiber tip and microbubble end. As the wall thickness of the micro-bubble can reach up to several micrometers, it can then be used for measuring the outer pressure with high sensitivity. The fabrication method has the merits of being simple, low in cost, and is easy to control. Experimental results show that its pressure sensitivity can reach 164.56 pm/kPa and the temperature sensitivity can reach 4 pm/°C. Therefore, it also has the advantage of being insensitive to temperature fluctuation.

This paper proposes a spectropolarimetric detection method based on three photoelastic modulators (3PEMs) and an acousto-optic tunable filter (AOTF). Operating the 3PEMs at slightly resonant frequencies $({\omega }_1,{\omega }_2,{\omega }_3)$ generates a different frequency signal that modulates the polarized component of the incident light at a low-frequency (0, $2{\omega }_1-2{\omega }_3$, ${\omega }_2-{\omega }_3$). The frequency of the low-frequency modulation component is two to three orders of magnitude lower than the resonant frequency of any of the 3PEMs so the general area array detector can realize the detection. $I$, $Q$, and $U$ of the incident light’s Stokes parameters can be obtained in only one detection by extracting the low-frequency component from the detector’s signals, and then combining it with an AOTF to finally realize the spectropolarimetric imaging detection. The paper introduces the basic principle, preliminarily verifies feasibility through a corresponding numerical simulation and experiment, and makes an error analysis on the polarization detection results according to factors of difference frequency and phase delay amplitude. The theory has potential application value to spectropolarimetric technology.