Heavy metal ions have drawn enough attention due to their harm to both humans and environments, and there has been an urgent need for stable and quick detection of them. Besides, the manganese ion is one of the most abundant ions in urban water systems, which needs to be monitored carefully. Hereby, a carbon dots (CDs) (the microwave method) based surface plasmon resonance (SPR) Mn2+ sensor has been proposed and discussed, which could achieve high detection sensitivity of 6.383 nm/lg(ppb) in the range of 0 ppb–200 ppb on manganese ions, with the detection limit of 0.3462 ppb. The proposed sensor also possesses high stability upon time and temperature, and it also has great ion selectivity against 9 other ions. Practical usage scenarios have been tested on the human serum, tap water, lake water, and river water, which confirm that the proposed sensor holds great potential for both blood tests and environmental monitoring.
This paper proposes a continuously tunable random lasers (RLs) based on the gain system of cellulose nanocrystals (CNCs)-doped hydrogels and the laser dye made of Rhodamine B (Rh B). Between them, the prepared CNCs-doped hydrogels have not only a weak scattering structure that can provide excellent multiple scattering, thus yielding a large gain, but also good mechanical properties that can provide great advantages in the tuning of RL. The experimental results indicate that the RL emission wavelength blue shifts with an increase in the stretching length. The continuous tuning range reaches up to 7.1 nm when the CNCs-doped hydrogels are stretched to 400%. In addition, the proposed CNCs-doped hydrogels effectively solve the problem of the structures of traditional hydrogels, which are easily destroyed during repeated stretching and ensure good stability of RL output and tuning. The RL error is tested and found to be less than 0.5 nm, when the same length is stretched during repeated stretching. Our results provide a new approach to obtain tunable and stable RLs. Simultaneously, in combination with the good biocompatibility of CNCs-doped hydrogels, the proposed RLs demonstrated great importance in the biological field.
We have numerically and experimentally investigated the flow rate measurement of the pipeline based on the optical fiber. Employing the large eddy simulation (LES) model, we have quantitatively analyzed the pressure fluctuation of the pipe wall caused by the turbulent flow in the pipeline. The simulation results have shown that the standard deviation of pressure fluctuation was quadratic with the flow rate. We have verified the theoretical model by using a distributed optical fiber acoustic sensing (DAS) system in the flow rate range from 0.61 m/s to 2.42 m/s. The experimental results were consistent with the simulation results very well. Furthermore, to improve the measuring error at the low flow rate, we have employed the composite adaptive denoising algorithm to eliminate the background noise and system noise. The final results have shown that the minimum goodness of fit was improved from 0.962 to 0.997, and the variation of the quadratic coefficient significantly decreased by 93.25%. The measured flow rate difference was only 0.84% between different sensing points in repeated experiments.