A sensitivity-enhanced hot-wire anemometer based on a cladding-etched optical fiber Bragg grating (FBG) coated with a layer of silver film and optically heated by using a 1480 nm laser diode is demonstrated. The silver film absorbs the laser power to heat the FBG to a certain high temperature and the airflow cools down the FBG hot-wire with the cooling effect and hence the Bragg wavelength of the FBG is determined by the airflow velocity. Experimental measurement results show that the heating efficiency of the FBG hot wire is improved by 3.8 times in magnitude by etching the fiber cladding from 125 µm down to 73.4 µm, and the achieved airflow velocity sensitivities, under a laser power of 200 mW, are −3 180 pm/(m/s), −889 pm/(m/s), −268 pm/(m/s), and −8.7 pm/(m/s) at different airflow velocities of 0.1 m/s, 0.5 m/s, 1.5 m/s, and 17 m/s, respectively. In comparison, the sensitivities are only −2193 pm/(m/s), −567 pm/(m/s), −161 pm/(m/s), and −4.9 pm/(m/s) for the reference anemometer without cladding etching even at a much higher heating laser power of 530 mW. These results prove that the method by using a cladding-etched FBG to improve sensitivity of FBG-based hot-wire anemometers works and the sensitivity is improved significantly.
Virtual Shack-Hartmann wavefront sensing (vSHWS) has some significant advantages and is promising for aberration measurement in the field of biomedical optical imaging. The illumination sources used in vSHWS are almost broadband, but are treated as monochromatic sources (only using center wavelength) in current data processing, which may cause errors. This work proposed a data processing method to take into account the multiple wavelengths of the broadband spectrum, named multiple-wavelength centroid-weighting method. Its feasibility was demonstrated through a series of simulations. A wavefront generated with a set of statistical human ocular aberrations was used as the target wavefront to evaluate the performance of the proposed and current methods. The results showed that their performance was very close when used for the symmetrical, but the wavefront error of the proposed method was much smaller than that of the current method when used for the asymmetrical spectrum, especially for the broader spectrum. These results were also validated by using 20 sets of clinical human ocular aberrations including normal and diseased eyes. The proposed method and the obtained conclusions have important implications for the application of vSHWS.
To coordinate the resonant wavelength of the plasmonic nanoparticles (NPs), the emission band of the reduced graphene oxide (rGO) photodetector at the NIR-region is crucial for the optimal plasmon-enhanced luminescence in the device. In contrast to monometallic NPs, where limits the dimensions and extended resonant wavelength, we integrated an Au-Ag bimetallic NPs (BMNPs) to enable resonance tuning at the longer wavelength at the excitation source of 785 nm. These features showed an increase in radiative recombination rates as well as the quantum yield efficiency of the device. The BMNPs were produced from the dewetting process of 600 °C and 500 °C, both at 1 min after the deposition thickness layer of Au (8 nm) and Ag (10 nm) on the Si substrate using the electron-beam evaporation process. Our BMNPs-rGO photodetector exhibited the responsivity of 2.25 · A W−1, Jones of specific detectivity of 2.45×1011Jones, and external quantum efficiency (EQE) of 356%. The rise time and fall time for the photodetector were 32 ns and 186 ns, respectively. This work provided an essential information to enable the versatile plasmon-enhanced application in 2-dimensional (2D) material optoelectronic devices.
The inconsistent response curve of delicate micro/nanofiber (MNF) sensors during cycling measurement is one of the main factors which greatly limit their practical application. In this paper, we proposed a temperature sensor based on the copper rod-supported helical microfiber (HMF). The HMF sensors exhibited different light intensity-temperature response relationships in single-cycle measurements. Two neural networks, the deep belief network (DBN) and the backpropagation neural network (BPNN), were employed respectively to predict the temperature of the HMF sensor in different sensing processes. The input variables of the network were the sensor geometric parameters (the microfiber diameter, wrapped length, coiled turns, and helical angle) and the output optical intensity under different working processes. The root mean square error (RMSE) and Pearson correlation coefficient (R) were used to evaluate the predictive ability of the networks. The DBN with two restricted Boltzmann machines (RBMs) provided the best temperature prediction results (RMSE and R of the heating process are 0.9705 °C and 0.9969, while the values of RMSE and R of the cooling process are 0.786 6 °C and 0.997 7, respectively). The prediction results obtained by the optimal BPNN (five hidden layers, 10 neurons in each layer, RMSE=1.126 6 °C, R=0.995 7) were slightly inferior to those obtained by the DBN. The neural network could accurately and reliably predict the response of the HMF sensor in cycling operation, which provided the possibility for the flexible application of the complex MNF sensor in a wide sensing range.
The micro-electromechanical system (MEMS) infrared thermopile is the core working device of modern information detection systems such as spectrometers, gas sensors, and remote temperature sensors. We presented two different structures of MEMS infrared thermopiles based on suspended film structures. They both deposited silicon nitride over the entire surface as a passivated absorber layer in place of a separate absorber zone, and the thermocouple strip was oriented in the same direction as the temperature gradient. The same MEMS preparation process was used and finally two different structures of the thermopile were characterized separately for testing to verify the impact of our design on the detector. The test results show that the circular and double-ended symmetrical thermopile detectors have responsivities of 27.932 V/W and 23.205 V/W, specific detectivities of 12.1×107 cm·Hz1/2·W−1 and 10.1×107 cm·Hz1/2·W−1, and response time of 26.2 ms and 27.06 ms, respectively. In addition, rectangular double-ended symmetric thermopile has a larger field of view than a circular thermopile detector, but is not as mechanically stable as a circular thermopile.
A vector bending fiber sensor based on core-by-core inscribed fiber Bragg gratings in a twin-core fiber has been proposed and experimentally demonstrated. An in-fiber integrated vector bending sensor is realized by using the thermal diffusion technique to fabricate the coupler. The characteristics of the coupler fabricated by thermal diffusion are simulated and experimented. By inscribing fiber Bragg gratings with different reflection wavelengths in the two cores of a symmetrical twin-core fiber, the curvature sensitivity can be enhanced by tracking the wavelength difference between the fiber Bragg gratings of the two cores. The measured bending sensitivity of the fiber Bragg grating ranges from −161.6 pm/m−1 to +165.5 pm/m−1. The differential sensitivity of the two cores is twice that of a conventional single grating, and the temperature-induced crosstalk is also reduced. The bending sensor proposed in this paper has the advantages of high integration, enhancing the sensitivity and two-dimensional orientation recognizability, and reducing temperature crosstalk, which can be a promising candidate for structural health monitoring or wearable artificial electronics applications.
We demonstrate a method for quickly and automatically detecting all three components of a remanent magnetic field around a shielded spin-exchange relaxation-free (SERF) atomic magnetometer (AM) using the trisection algorithm (TSA) for zero-field resonance (ZFR). To satisfy the measurement of AMs, a resonance light of the 87Rb D1 line with a spectral width of less than 1MHz is converted to circular polarization by a linear polarizer and a quarter-wave plate. After the light beam has passed through the alkali metal vapor cell, the residual magnetic field can be measured by searching for triaxial ZFR optical peaks. The TSA stably reduces the measurement time to 2.41 s on average and improves the measurement accuracy, significantly outpacing existing methods. The weighted averages of all measurements with corresponding uncertainties are (−15.437 ± 0.022)nT, (6.062 ± 0.021)nT, and (−14.158 ± 0.052)nT on the x-, y-, and z-axes, respectively. These improvements could facilitate more extremely weak magnetic studies in real time, such as magnetoencephalography (MEG) and magnetocardiography (MCG) measurements.
In this study, we design a refractive index (RI) sensor using a novel cadmium telluride photonic crystal fiber (TPCF). Based on four-wave mixing (FWM), the changes in RI can be accurately detected, and RI sensing in the mid-infrared region (MIR) can be achieved by detecting wavelength shifts in the Stokes and anti-Stokes spectra caused by the changes in RI of the liquid to be measured. When the pump wavelength of FWM lies in the normal and abnormal dispersion regions of the TPCF, the RI response of the idler frequency wave and the signal wave are analyzed by numerical simulation methods. The simulation results show that the RI sensitivity of the sensor can be as high as 7692 nm/RIU with a linearity is up to 99.9% at the pump wavelength of 3380 nm. To our knowledge, the RI sensing sensitivity of the MIR is presented for the first time in this study by using FWM in the non-silicon PCF.