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Topic Editors

Centre for Microsystems Technology (CMST), Department of Electronics and Information Systems (ELIS), Ghent University—imec, 9052 Ghent, Belgium
Prof. Dr. Geert Van Steenberge
Centre for Microsystems Technology (CMST), Department of Electronics and Information Systems (ELIS), Ghent University—imec, 9052 Ghent, Belgium

Advances in Optical Sensors

Abstract submission deadline
closed (31 December 2022)
Manuscript submission deadline
closed (31 May 2023)
Viewed by
78128

Topic Information

Dear Colleagues,

Optical sensors have gained increasing interest because of their immunity to electromagnetic interference, high performance, great potential for miniaturization, etc. Therefore, optical sensors are currently being used in a wide variety of applications, such as environmental monitoring (e.g., using spectroscopic techniques), structural health monitoring (e.g., using Fiber Bragg Grating sensors), biosensing (e.g., based on surface plasmon resonance), object detection (e.g., using LIDAR), etc.

There is also a trend towards miniaturization, and since optical sensors require light for their operation, it is often a challenge to deliver/collect light efficiently to/from the miniaturized sensors. The purpose of this Topic is to bring together state-of-the-art achievements on all aspects of optical sensors and their applications, and serve as a platform for colleagues to exchange novel ideas in this area.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). We encourage authors to submit original research articles, and reviews on (but not limited to) the following topics:

  • Novel optical sensors;
  • Optical sensor applications;
  • Biosensors;
  • Chemosensors;
  • Readout systems;
  • Fiber-based optical sensors;
  • Photonic Integrated Circuits;
  • Flexible optical sensors;
  • Sensor design;
  • Optical sensor fabrication technologies;
  • Integration, packaging and miniaturization technologies for optical sensors.

In this Topic, we are looking for submissions which are mainly dealing with (miniaturized or integrated) sensor realizations and design, and their applications. Articles dealing with algorithms, data processing are out of scope. Furthermore, metrology equipment and camera systems require a dedicated development strategy so that we consider those also out of scope for this Topic.

Prof. Dr. Jeroen Missinne
Prof. Dr. Geert Van Steenberge
Topic Editors

Keywords

  • fabrication technology
  • optical sensor
  • optical sensor applications
  • biosensor
  • chemosensor
  • fiber sensors
  • photonic integrated circuits
  • sensor design
  • optical integration
  • optical packaging

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Biosensors
biosensors
4.9 6.6 2011 17.1 Days CHF 2700
Chemosensors
chemosensors
3.7 5.0 2013 17.1 Days CHF 2700
Optics
optics
1.1 2.2 2020 19.6 Days CHF 1200
Photonics
photonics
2.1 2.6 2014 14.8 Days CHF 2400
Sensors
sensors
3.4 7.3 2001 16.8 Days CHF 2600

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Published Papers (34 papers)

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15 pages, 5733 KiB  
Article
Photonic Integrated Circuit Based Temperature Sensor for Out-of-Autoclave Composite Parts Production Monitoring
by Georgios Syriopoulos, Ioannis Poulopoulos, Charalampos Zervos, Evrydiki Kyriazi, Aggelos Poulimenos, Michal Szaj, Jeroen Missinne, Geert van Steenberge and Hercules Avramopoulos
Sensors 2023, 23(18), 7765; https://doi.org/10.3390/s23187765 - 8 Sep 2023
Cited by 7 | Viewed by 1149
Abstract
The use of composite materials has seen widespread adoption in modern aerospace industry. This has been facilitated due to their favourable mechanical characteristics, namely, low weight and high stiffness and strength. For broader implementation of those materials though, the out-of-autoclave production processes have [...] Read more.
The use of composite materials has seen widespread adoption in modern aerospace industry. This has been facilitated due to their favourable mechanical characteristics, namely, low weight and high stiffness and strength. For broader implementation of those materials though, the out-of-autoclave production processes have to be optimized, to allow for higher reliability of the parts produced as well as cost reduction and improved production speed. This optimization can be achieved by monitoring and controlling resin filling and curing cycles. Photonic Integrated Circuits (PICs), and, in particular, Silicon Photonics, owing to their fast response, small size, ability to operate at higher temperatures, immunity to electromagnetic interference, and compatibility with CMOS fabrication techniques, can offer sensing solutions fulfilling the requirements for composite material production using carbon fibres. In this paper, we demonstrate a passive optical temperature sensor, based on a 220 nm height Silicon-on-Insulator platform, embedded in a composite tool used for producing RTM-6 composite parts of high quality (for use in the aerospace industry). The design methodology of the photonic circuit as well as the experimental results and comparison with the industry standard thermocouples during a thermal cycling of the tool are presented. The optical sensor exhibits high sensitivity (85 pm/°C), high linearity (R2 = 0.944), and is compatible with the RTM-6 production process, operating up to 180 °C. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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<p>Schematic of the overall concept, with the sensor at the resin–tool interface.</p>
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<p>(<b>a</b>) The packaged sensor configuration (<b>left</b>), with the fibre-to-PIC interface (<b>right</b>). (<b>b</b>) The sensor build-up, with the PIC on top and the interface to an optical fibre at the bottom side. (<b>c</b>) The sensor inside the package tube, connected to an optical fibre.</p>
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<p>The composite tool, with the integrated sensors embedded, with their interfacing fibres visible.</p>
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<p>Conceptual top view of a Bragg grating showing the design variables.</p>
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<p>(<b>a</b>) Schematic of the experimental testbed. (<b>b</b>) The response of the optical sensor, raw data (blue) and filtered data (red), with respect to wavelength. (<b>c</b>) Matrix and punch of the composite tool. (<b>d</b>) Heating cycle, as recorded by the thermocouples.</p>
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<p>(<b>a</b>) Cross-section of the layer stack indicating the refractive indices for each material used; (<b>b</b>) the electrical field intensity profile for TE mode; (<b>c</b>) the electrical field intensity profile for TM mode, for the same silicon waveguide.</p>
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<p>Confinement factor as a function of grating corrugation width for both TE and TM polarizations.</p>
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<p>(<b>a</b>) The effective refractive index of the fundamental mode for TE polarization. (<b>b</b>) The grating pitch as a function of the corrugation width.</p>
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<p>Change in reflection spectra, caused by a variation in: (<b>a</b>) corrugation width; (<b>b</b>) number of periods.</p>
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<p>Reflection spectra for phase-shifted Bragg gratings with TE polarization, for configurations of dw = 20 nm and Λ = 324 nm, 326 nm, 328 nm.</p>
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<p>Reflection spectra for phase-shifted Bragg gratings with TE polarization, for configurations of Λ = 326 nm and dw = 10 nm, 20 nm, 30 nm.</p>
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<p>Reflection spectra for phase-shifted Bragg gratings with TE polarization, for configurations of Λ = 326 nm, dw = 20 nm, and periodicity of 100, 200, 300.</p>
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<p>(<b>a</b>) Reflection spectra at varying temperature, for phase-shifted Bragg grating, of Λ = 326 nm, dw = 20 nm, N = 200 for temperatures of: 23 °C, 80 °C, 180 °C; (<b>b</b>) temperature sensitivity of the same structure.</p>
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<p>(<b>a</b>) Reflection spectra, raw data, filtered data and dip in the reflection lobe for 30 °C. (<b>b</b>) Filtered spectrum data for 3 different temperature levels.</p>
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<p>(<b>a</b>) Linear regression models for the sensor in the lab, and inside the tool. (<b>b</b>) Heating cycle, as recorded by the thermocouple (blue), and the temperature as recorded by the optical sensors (red dots). The yellow bars provide a qualitative overview of the total error.</p>
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13 pages, 5176 KiB  
Essay
Integrated Encapsulation and Implementation of a Linear-Mode APD Detector for Single-Pixel Imaging Lidar
by Akang Lv, Kee Yuan, Jian Huang, Dongfeng Shi, Shiguo Zhang, Yafeng Chen and Zixin He
Photonics 2023, 10(9), 970; https://doi.org/10.3390/photonics10090970 - 24 Aug 2023
Viewed by 1382
Abstract
Single-pixel imaging lidar is a novel technology that leverages single-pixel detectors without spatial resolution and spatial light modulators to capture images by reconstruction. This technique has potential imaging capability in non-visible wavelengths compared with surface array detectors. An avalanche photodiode (APD) is a [...] Read more.
Single-pixel imaging lidar is a novel technology that leverages single-pixel detectors without spatial resolution and spatial light modulators to capture images by reconstruction. This technique has potential imaging capability in non-visible wavelengths compared with surface array detectors. An avalanche photodiode (APD) is a device in which the internal photoelectric effect and the avalanche multiplication effect are exploited to detect and amplify optical signals. An encapsulated APD detector, with an APD device as the core, is the preferred photodetector for lidar due to its high quantum efficiency in the near-infrared waveband. However, research into APD detectors in China is still in the exploratory period, when most of the work focuses on theoretical analysis and experimental verification. This is a far cry from foreign research levels in key technologies, and the required near-infrared APD detectors with high sensitivity and low noise have to be imported at a high price. In this present study, an encapsulated APD detector was designed in a linear mode by integrating a bare APD tube, a bias power circuit, a temperature control circuit and a signal processing circuit, and the corresponding theoretical analysis, circuit design, circuit simulation and experimental tests were carried out. Then, the APD detector was applied in the single-pixel imaging lidar system. The study showed that the bias power circuit could provide the APD with an operating voltage of DC 1.6 V to 300 V and a ripple voltage of less than 4.2 mV. Not only that, the temperature control circuit quickly changed the operating state of the Thermo Electric Cooler (TEC) to stabilize the ambient temperature of the APD and maintain it at 25 ± 0.3 °C within 5 h. The signal processing circuit was designed with a multi-stage amplification cascade structure, effectively raising the gain of signal amplification. By comparison, the trial also suggested that the encapsulated APD detector and the commercial Licel detector had a good agreement on the scattered signal, such as a repetition rate and pulse width response under the same lidar environment. Therefore, target objects in real atmospheric environments could be imaged by applying the encapsulated APD detector to the near-infrared single-pixel imaging lidar system. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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<p>Schematic diagram of the NIR active relational imaging lidar system.</p>
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<p>Block diagram of the hardware structure of the APD detector.</p>
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<p>Flyback bias power circuit based on LT3757.</p>
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<p>(<b>a</b>) On-state of MOSFET. (<b>b</b>) Off-state of MOSFET.</p>
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<p>The work principle diagram of temperature control.</p>
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<p>Signal processing topology.</p>
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<p>Simulation results of the bias power circuit.</p>
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<p>Transient voltage ripple of the bias power circuit at different outputs.</p>
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<p>APD ambient temperature curve.</p>
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<p>Experimental test of packaged APD detector and commercial Licel detector.</p>
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<p>Frequency response of encapsulated APD detector and commercial Licel detector.</p>
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<p>Impulse response of encapsulated APD detector and commercial Licel detector.</p>
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<p>(<b>a</b>) Experimental scene layout. (<b>b</b>) Imaging object. (<b>c</b>) The distribution of the echo signal obtained by the APD detector with distance after the laser has been scattered by the atmosphere and reflected by the target object. (<b>d</b>) Image recovered through relational calculation.</p>
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9 pages, 2452 KiB  
Communication
Dispersion Turning Attenuation Microfiber for Flowrate Sensing
by Yaqi Tang, Chao Wang, Xuefeng Wang, Meng Jiang, Junda Lao and Dongning Wang
Sensors 2023, 23(16), 7279; https://doi.org/10.3390/s23167279 - 20 Aug 2023
Cited by 3 | Viewed by 1170
Abstract
We demonstrated a new optical fiber modal interferometer (MI) for airflow sensing; the novelty of the proposed structure is that an MI is fabricated based on a piece of HAF, which makes the sensitive MI itself also a hotwire. The interferometer is made [...] Read more.
We demonstrated a new optical fiber modal interferometer (MI) for airflow sensing; the novelty of the proposed structure is that an MI is fabricated based on a piece of HAF, which makes the sensitive MI itself also a hotwire. The interferometer is made by applying arc-discharge tapering and then flame tapering on a 10 mm length high attenuation fiber (HAF, 2 dB/cm) with both ends spliced to a normal single mode fiber. When the diameter of the fiber in the processing region is reduced to about 2 μm, the near-infrared dispersion turning point (DTP) can be observed in the interferometer’s transmission spectrum. Due to the absorption of the HAF, the interferometer will have a large temperature increase under the action of a pump laser. At the same time, the spectrum of the interferometer with a DTP is very sensitive to the change in ambient temperature. Since airflow will significantly affect the temperature around the fiber, this thermosensitive interferometer with an integrated heat source is suitable for airflow sensing. Such an airflow sensor sample with a 31.2 mm length was made and pumped by a 980 nm laser with power up to 200 mW. In the comparative experiment with an electrical anemometer, this sensor exhibits a very high air-flow sensitivity of −2.69 nm/(m/s) at a flowrate of about 1.0 m/s. The sensitivity can be further improved by enlarging the waist length, increasing the pump power, etc. The optical anemometer with an extremely high sensitivity and a compact size has the potential to measure a low flowrate in constrained microfluidic channels. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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<p>(<b>a</b>) Schematic diagram of the dispersion turning attenuation microfiber, (<b>b</b>) simulation results of dispersion turning attenuation microfiber for flowrate measurement.</p>
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<p>(<b>a</b>) Micrographs of fabricated attenuation microfiber and its transmission spectra, (<b>b</b>) fabrication process of attenuation microfiber, and (<b>c</b>) diagram of the sensing system.</p>
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<p>(<b>a</b>) Wavelength shift in different dips with different pump power, and Si means the sensitivity of the interference dips. (<b>b</b>) Wavelength shifts in interference dips A and A’ of attenuation microfiber and micro SMF with different temperatures.</p>
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<p>(<b>a</b>) Variation in the transmission spectrum of an attenuation microfiber with different flowrates. (<b>b</b>) Wavelength shifts in interference dips with different flowrates.</p>
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<p>(<b>a</b>) Variation in the transmission spectrum of an attenuation microfiber with different flowrates. (<b>b</b>) Wavelength shifts in interference dips with different total lengths of an attenuation microfiber.</p>
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13 pages, 9308 KiB  
Article
Spatial Spectral Characteristics of Partial Discharge with Different Electrode Models
by Taiqi Wang, Yongkang Cheng, Chao Xu, Haoyu Li, Jiayao Cheng, Gangding Peng and Qiang Guo
Photonics 2023, 10(7), 788; https://doi.org/10.3390/photonics10070788 - 7 Jul 2023
Cited by 3 | Viewed by 1137
Abstract
In this paper, the spatial spectral characteristics of partial discharge (PD) under different electrode models are mainly studied. In the initial corona discharge stage, the emission spectrum is mainly emitted by the N2(C3IIuB3II [...] Read more.
In this paper, the spatial spectral characteristics of partial discharge (PD) under different electrode models are mainly studied. In the initial corona discharge stage, the emission spectrum is mainly emitted by the N2(C3IIuB3IIg) energy level transition of the N2 second positive band system. The spectrum is in the ultraviolet range of 294–436 nm, and its main peak is at 337 nm. The streamer discharge stage spectrum is mainly emitted by the energy level transition of the second positive band system of N2, N+, NO, and O+ and the first positive band system of N2(B3IIgA3Σu+). In the gap of different polarity electrodes, the ultraviolet spectrum content near the positive polarity is more abundant. The UV spectra ranges are 202–225 nm and 229–292 nm, respectively. The discharge of the needle–sphere system is more intense in visible light and near-infrared light, with peaks at 500 nm and 777 nm, respectively. In addition, the PD process based on the finite element method is simulated by COMSOL Multiphysics software. The simulation results show that the distribution of high-energy electron density varies with the electrode spacing and discharge model. The influence of particle energy level transition on the spatial spectral characteristics of PD is verified. This work provides important insights and possibilities for future fluorescent fiberoptic sensing and positioning for spatial PD detection and positioning using spectral characteristic peaks as detection quantities or excitations. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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<p>System schematic diagram of the PD spectrum experimental device. (<b>a</b>) Sphere-Sphere; (<b>b</b>) Needle-Sphere.</p>
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<p>Corona and electrical breakdown in the experiment: (<b>a</b>) the phenomenon of purple corona layer, (<b>b</b>) bright electrical breakdown channel.</p>
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<p>Two-dimensional axisymmetric grid generation and boundary: (<b>a</b>) SSED simulation model, (<b>b</b>) NSED simulation model.</p>
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<p>Spectrum near the needle electrode in corona discharge stage in NSED.</p>
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<p>(<b>a</b>) Spatial spectrum between electrodes in the SSED breakdown stage. (<b>b</b>) Spectra at two electric extremes.</p>
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<p>(<b>a</b>) Spatial spectrum between electrodes in the NSED breakdown stage. (<b>b</b>) Spectra at two electric extremes.</p>
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<p>Spatial distribution of electron density with time under SSED simulation.</p>
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<p>Spatial distribution of electron density with time under NSED simulation.</p>
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<p>(<b>a</b>) The axial electron density distribution curve with time under SSED simulation. (<b>b</b>) Distribution curve of axial electron density with time under NSED simulation.</p>
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<p>(<b>a</b>) The anti-axial electron potential variation with time under SSED simulation. (<b>b</b>) Variation curves of anti-axial electron potential with time under NSED simulation.</p>
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15 pages, 4194 KiB  
Article
Effects of Measurement Temperature on Radioluminescence Processes in Cerium-Activated Silica Glasses for Dosimetry Applications
by Ismail Zghari, Hicham El Hamzaoui, Bruno Capoen, Franck Mady, Mourad Benabdesselam, Géraud Bouwmans, Damien Labat, Youcef Ouerdane, Adriana Morana, Sylvain Girard, Aziz Boukenter and Mohamed Bouazaoui
Sensors 2023, 23(10), 4785; https://doi.org/10.3390/s23104785 - 16 May 2023
Cited by 3 | Viewed by 1375
Abstract
Cerium-doped-silica glasses are widely used as ionizing radiation sensing materials. However, their response needs to be characterized as a function of measurement temperature for application in various environments, such as in vivo dosimetry, space and particle accelerators. In this paper, the temperature effect [...] Read more.
Cerium-doped-silica glasses are widely used as ionizing radiation sensing materials. However, their response needs to be characterized as a function of measurement temperature for application in various environments, such as in vivo dosimetry, space and particle accelerators. In this paper, the temperature effect on the radioluminescence (RL) response of Cerium-doped glassy rods was investigated in the 193–353 K range under different X-ray dose rates. The doped silica rods were prepared using the sol-gel technique and spliced into an optical fiber to guide the RL signal to a detector. Then, the experimental RL levels and kinetics measurements during and after irradiation were compared with their simulation counterparts. This simulation is based on a standard system of coupled non-linear differential equations to describe the processes of electron-hole pairs generation, trapping-detrapping and recombination in order to shed light on the temperature effect on the RL signal dynamics and intensity. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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<p>Illustration of the experimental setup used to characterize the RL response of the Ce<sup>3+</sup>-doped cane exposed to X-ray beam. The inset shows a photograph of the sample connected to the transport fiber.</p>
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<p>RL signal response of the cerium-doped silica cane spliced to a transport fiber for different X-ray dose rates and at temperature ranging from 193 K to 353 K.</p>
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<p>Dose rate dependence of the RL response of the cerium-doped silica cane exposed to irradiation at different X-ray dose rates obtained at different temperatures ranging from 193 K to 353 K. Each point represents the average RL signal in the pseudo-plateau region.</p>
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<p>Example of normalized RL signal dynamics recorded from the cerium-doped silica sample at a dose rate of 50 mGy/s at different measurement temperatures. The dotted circles show the pseudo-plateau zones.</p>
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<p>Integrated phosphorescence signal response of the cerium-doped silica cane, 60 s after the end of irradiation, as a function of the temperature ranging from 193 K to 353 K at a dose rate of 50 mGy/s.</p>
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<p>Normalized RL spectra of the cerium-doped silica cane spliced to a transport fiber obtained at different temperatures, ranging from 193 K to 353 K, under 50 mGy/s dose rate.</p>
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<p>Schematic representation of the levels and processes used in the radioluminescence modeling with <span class="html-italic">k</span> electron traps and one recombination center.</p>
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<p>Comparisons of RL signals, measured under X-rays (50 mGy/s) with phosphorescence after the end of irradiation, at different temperature conditions, and simulation results.</p>
Full article ">Figure 8 Cont.
<p>Comparisons of RL signals, measured under X-rays (50 mGy/s) with phosphorescence after the end of irradiation, at different temperature conditions, and simulation results.</p>
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<p>Comparison of the trap charge carriers’ concentrations at different energy levels resulting from the simulation at two measurement temperatures, during and after stopping the irradiation at a dose rate of 50 mGy/s. The multiplying factors applied to the 233 K curves have been chosen to facilitate comparison with temperature 193 K.</p>
Full article ">Figure 9 Cont.
<p>Comparison of the trap charge carriers’ concentrations at different energy levels resulting from the simulation at two measurement temperatures, during and after stopping the irradiation at a dose rate of 50 mGy/s. The multiplying factors applied to the 233 K curves have been chosen to facilitate comparison with temperature 193 K.</p>
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<p>Evolution of the simulated RL signal, for 50 mGy/s X-ray dose rate, at temperature ranging from 193 K to 353 K.</p>
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<p>Comparison of experimental and simulated RL signal intensities, after 100 s of irradiation, for a dose rate of 50 mGy/s at different measurement temperatures. These intensities have been normalized to their values at 353 K.</p>
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10 pages, 3674 KiB  
Article
Self-Contained Reference Sensors to Reduce Nuisance Alarm Rate in φ-OTDR-Based Fence Intrusion Detection System
by Hailiang Zhang, Hui Dong, Dora Juan Juan Hu and Jun Hong Ng
Optics 2023, 4(2), 330-339; https://doi.org/10.3390/opt4020024 - 15 May 2023
Viewed by 1504
Abstract
Nuisance alarm rate (NAR) is one of the key performance parameters in a phase-sensitive optical time domain reflectometry (φ-OTDR)-based fence intrusion detection system. Typically, the vibrations caused by ambient environmental conditions, such as heavy rain, strong wind, and passing vehicles, easily result in [...] Read more.
Nuisance alarm rate (NAR) is one of the key performance parameters in a phase-sensitive optical time domain reflectometry (φ-OTDR)-based fence intrusion detection system. Typically, the vibrations caused by ambient environmental conditions, such as heavy rain, strong wind, and passing vehicles, easily result in many nuisance alarms. Significant research efforts have been undertaken to suppress the NAR. In this paper, we propose to utilize short segments of the sensing fiber as reference sensors for significant reduction in the NAR in φ-OTDR for the first time, to the best of our knowledge. According to our field trial results, the proposed approach can reduce the NAR by more than 90%. The proposed approach is very simple, practical, and cost-effective, which can be easily integrated with the existing methods of reducing NAR and act as an additional level of decision-making algorithm for triggering alarms. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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<p>(<bold>a</bold>) The schematic diagram of the φ-OTDR system with a reference sensor for fence intrusion detection. (<bold>b</bold>) The schematic diagram of the developed φ-OTDR interrogator. AOM: acousto-optic modulator; CIR: circulator; FUT: fiber under test; PD: photodetector; DAQ: data acquisition card; PC: computer.</p>
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<p>The working principle of the φ-OTDR interrogator with a reference sensor. (<bold>a</bold>) Without strong background vibrations caused by heavy rain or wind, the reference sensor is not triggered; the system alarm threshold is <italic>TH</italic><sub>1</sub>. (<bold>b</bold>) With strong background vibrations, the reference sensor is triggered, and the system alarm threshold will be multiplied by <italic>N</italic>, increasing from <italic>TH</italic><sub>1</sub> to <italic>TH</italic><sub>2</sub>. (<bold>c</bold>) Algorithm flow chart of the reference sensor working principle. In real-world applications, the proposed approach can be combined with other methods of reducing the NAR.</p>
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<p>(<bold>a</bold>) The fiber cable installation layout on the fences. (<bold>b</bold>) Picture of the sensing fiber cable.</p>
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<p>Waterfall plots of the filtered RB signal for background on a sunny day, three different intrusion events, and background in heavy rain. (<bold>a</bold>) Background on a sunny day; (<bold>b</bold>) fence cutting on a sunny day; (<bold>c</bold>) aided climbing on fence on a sunny day; (<bold>d</bold>) unaided climbing on fence in moderate rain; (<bold>e</bold>) background in heavy rain.</p>
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<p>The RMS values of the alarms for the three types of events. (<bold>a</bold>) Fence cutting on a sunny day; (<bold>b</bold>) aided climbing on fence on a sunny day; (<bold>c</bold>) unaided climbing on fence in moderate rain.</p>
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<p>Alarm records of the field trial without using the reference sensor for 137.5 h. (<bold>a</bold>) The recorded RMS values and times of the alarms generated during the field trial period; the threshold was 150. (<bold>b</bold>) Zoom in of the alarm records induced by heavy rain in the duration from 7:40 to 8:04 on 24 June 2020. (<bold>c</bold>) Probability histogram of the RMS values of the alarms.</p>
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<p>Alarm records of the field trial with using the reference sensor for 294 h. (<bold>a</bold>) All the recorded alarms generated during the field trial period; the threshold <italic>TH</italic><sub>1</sub> was 150, <italic>N</italic> = 2, and the reference sensor threshold <italic>TH<sub>R</sub></italic> was 110. The red asterisks represent the recorded RMS values of the alarms generated by the fiber mounted on the fences; green curve represents the RMS values of the reference sensor. (<bold>b</bold>) Zoom in of the alarm records in the duration from 7:00 to 13:00 on 12 August 2020.</p>
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<p>RMS values distribution of the alarms in lab tests. (<bold>a</bold>) FUT was 1.9 km SMF. (<bold>b</bold>) FUT was 150 m sensing cable used in the field trials.</p>
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10 pages, 1031 KiB  
Communication
Single Photon Approach for Chirality Sensing
by Fabrizio Sgobba, Arianna Elefante, Stefano Dello Russo, Mario Siciliani de Cumis and Luigi Santamaria Amato
Photonics 2023, 10(5), 512; https://doi.org/10.3390/photonics10050512 - 28 Apr 2023
Viewed by 1684
Abstract
We developed a high sensitivity optical sensor for circular birefringence using a heralded photon source. The sensor can be employed for chirality measurements and, being based on single photons, can be exploited for fragile biological sample or in metrological applications where the light [...] Read more.
We developed a high sensitivity optical sensor for circular birefringence using a heralded photon source. The sensor can be employed for chirality measurements and, being based on single photons, can be exploited for fragile biological sample or in metrological applications where the light intensity must be kept as low as possible. We found the best operational condition; then, we calibrated the sensor and tested its performance up to a very long acquisition time, obtaining excellent stability and a sub-ppm birefringence detection limit (for a 100 μm sample), thus paving the way for fundamental physics test as well. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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<p>Pictorial 3D representation of the polarisation rotation sensor. (<b>1.</b>) Twin photon source, (<b>2.</b>) balanced beam splitter, (<b>3.</b>) gold-coated plane mirror, (<b>4.</b>) half-wave plate (HWP) mounted on motorized rotational stage, acting as polarisation tilting sample, (<b>5.</b>) linear polarisers, (<b>6.</b>) single photon avalanche diodes detectors (SPADs). (<b>7.</b>) Time tagger for coincidence detection. This figure was obtained via Fusion 360.</p>
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<p>Contour map employed to infer sensor’s best operative range. Coincidence counts are mapped as function of polarisation angle of each polariser with respect to horizontal axes, namely <math display="inline"><semantics> <msub> <mi>θ</mi> <mn>1</mn> </msub> </semantics></math>, <math display="inline"><semantics> <msub> <mi>θ</mi> <mn>2</mn> </msub> </semantics></math>.</p>
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<p>Averaged value of <math display="inline"><semantics> <mrow> <mi>C</mi> <mo>(</mo> <msub> <mi>θ</mi> <mi>E</mi> </msub> <mo>)</mo> </mrow> </semantics></math> (black dots) and its uncertainty. The polynomial function employed for calibration is also resported (red curve).</p>
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<p>Plot of the statistical error on the estimation parameter <math display="inline"><semantics> <mrow> <msub> <mi>σ</mi> <mi>θ</mi> </msub> <mrow> <mo>(</mo> <mn>2</mn> <mi>s</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> (black dots) as a function of the actual angles reproduced with the rotational mount (<math display="inline"><semantics> <msub> <mi>θ</mi> <mi>E</mi> </msub> </semantics></math>).</p>
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<p>Integral average of <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="sans-serif">Θ</mi> <mrow> <mi>E</mi> <mn>1</mn> </mrow> </msub> <mrow> <mo>(</mo> <mi>T</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> (blue dots), <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="sans-serif">Θ</mi> <mrow> <mi>E</mi> <mn>2</mn> </mrow> </msub> <mrow> <mo>(</mo> <mi>T</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> (dark yellow dots), and their difference <math display="inline"><semantics> <mrow> <mo>Δ</mo> <msub> <mi mathvariant="sans-serif">Θ</mi> <mi>E</mi> </msub> <mrow> <mo>(</mo> <mi>T</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> (black dots) as a function of integration time, expressed in logarithmic scale.</p>
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<p>OADL per unit length as a function of the average coincidence events (black curve). The Allan deviation of the single <math display="inline"><semantics> <msub> <mi mathvariant="sans-serif">Θ</mi> <mi>E</mi> </msub> </semantics></math> is also reported for comparison, respecting the same legend as in <a href="#photonics-10-00512-f005" class="html-fig">Figure 5</a>.</p>
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11 pages, 3737 KiB  
Article
Hard-Templated Porous Niobia Films for Optical Sensing Applications
by Venelin Pavlov, Rosen Georgiev, Katerina Lazarova, Biliana Georgieva and Tsvetanka Babeva
Photonics 2023, 10(2), 167; https://doi.org/10.3390/photonics10020167 - 4 Feb 2023
Viewed by 1451
Abstract
Porous Nb2O5 films obtained by a modified hard-template method were studied and their optical and sensing properties were optimized in order to find applications in chemo-optical sensing. Porous films were prepared by following three steps: liquid mixing of niobium sol [...] Read more.
Porous Nb2O5 films obtained by a modified hard-template method were studied and their optical and sensing properties were optimized in order to find applications in chemo-optical sensing. Porous films were prepared by following three steps: liquid mixing of niobium sol and SiO2 colloids in different volume fractions, thermal annealing of spin-coated films for formation of a rigid niobia matrix, and selective removal of silica phase by wet etching thus generating free volume in the films. The morphology and structure of the films were studied using transmission electron microscopy and selected area electron diffraction, while their optical and sensing properties were estimated using UV-VIS-NIR reflectance measurements in different ambiences such as air, argon and acetone vapors and nonlinear curve fitting of the measured reflectance spectra. Bruggeman effective medium approximation was applied for determination of the volume fraction of silica and air in the films, thus revealing the formation of porosity inside the films. For further characterization of composite films, their water contact angles were measured and finally conclusions about the impact of initial chemical composition and etching duration on properties of the films were drawn. Full article
(This article belongs to the Topic Advances in Optical Sensors)
Show Figures

Figure 1

Figure 1
<p>TEM pictures of SiO<sub>2</sub> particles in Ludox<sup>®</sup> (<b>a</b>) and histogram distribution of their size (<b>b</b>).</p>
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<p>TEM images of porous films of Nb<sub>2</sub>O<sub>5</sub> prepared by mixing Nb sol and a colloidal solution of nanoparticles of SiO<sub>2</sub> (commercially available LUDOX<sup>®</sup>) in different volume fractions: 50:1 (<b>a</b>), 20:1 (<b>b</b>), 10:1 (<b>c</b>) and 5:1 (<b>d</b>); Typical selected area electron diffraction (SAED) pattern is shown as an inset.</p>
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<p>Dispersion of refractive index of Nb<sub>2</sub>O<sub>5</sub> films prepared by mixing of Nb sol and colloidal solution of nanoparticles of SiO<sub>2</sub> in different volume fractions indicated in the figure.</p>
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<p>Reflectance spectra of hard-templated Nb<sub>2</sub>O<sub>5</sub> obtained by liquid-phase mixing of Nb sol and silica colloids in volume ratios of 50:1 (<b>a</b>), 20:1 (<b>b</b>), 10:1 (<b>c</b>) and 5:1 (<b>d</b>) during selective removal of SiO<sub>2</sub> phase by wet-etching.</p>
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<p>Refractive index change as a function of etching time of porous Nb<sub>2</sub>O<sub>5</sub> layers obtained by liquid phase mixing of niobium sol and colloidal solution of SiO<sub>2</sub> nanoparticles in different volume ratios indicated in the figure.</p>
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<p>Water contact angles of hard-templated Nb<sub>2</sub>O<sub>5</sub> films obtained by liquid phase mixing of Nb sol and silica colloids in different volume ratios indicated in the figure.</p>
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<p>Water contact angles as a function of etching time of hard-templated porous Nb<sub>2</sub>O<sub>5</sub> films obtained by liquid phase mixing of Nb sol and silica colloids in different volume ratios indicated in the figure. Water contact angles of pure Ludox<sup>®</sup> and niobia films are represented by the two dashed horizontal lines.</p>
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<p>Refractive index change due to acetone vapor absorption prior to and after selective removal of silica in hard-templated films of Nb<sub>2</sub>O<sub>5</sub> obtained by liquid phase mixing of Nb sol and silica colloids in different volume ratios indicated in the figure. The films were etched in a standard SiO<sub>2</sub> etcher for different times: 240 s for the 50:1 and 20:1 films, 210 s for the 10:1 film and 120 s for the 5:1 film.</p>
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<p>Refractive index change as a function of etching time of hard-templated films of Nb<sub>2</sub>O<sub>5</sub> obtained by liquid phase mixing of Nb sol and silica colloids in different volume ratios indicated in the figure.</p>
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10 pages, 3886 KiB  
Communication
An Ultracompact Angular Displacement Sensor Based on the Talbot Effect of Optical Microgratings
by Zhiyong Yang, Xiaochen Ma, Daguo Yu, Bin Cao, Qianqi Niu, Mengwei Li and Chenguang Xin
Sensors 2023, 23(3), 1091; https://doi.org/10.3390/s23031091 - 17 Jan 2023
Cited by 4 | Viewed by 1800
Abstract
Here, we report an ultracompact angular displacement sensor based on the Talbot effect of optical microgratings. Periodic Talbot interference patterns were obtained behind an upper optical grating. By putting another grating within the Talbot region, the total transmission of the two-grating structure was [...] Read more.
Here, we report an ultracompact angular displacement sensor based on the Talbot effect of optical microgratings. Periodic Talbot interference patterns were obtained behind an upper optical grating. By putting another grating within the Talbot region, the total transmission of the two-grating structure was found to be approximatively in a linear relationship with the relative pitch angle between the two gratings, which was explained by a transversal shift of the Talbot interference patterns. The influence of the grating parameters (e.g., the grating period, the number of grating lines and the gap between the two gratings) was also studied in both a simulation and an experiment, showing a tunable sensitivity and range by simply changing the grating parameters. A sensitivity of 0.19 mV/arcsec was experimentally obtained, leading to a relative sensitivity of 0.27%/arcsec within a linear range of ±396 arcsec with the 2 μm-period optical gratings. Benefitting from tunable properties and an ultracompact structure, we believe that the proposed sensor shows great potential in applications such as aviation, navigation, robotics and manufacturing engineering. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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Figure 1
<p>Schematic of the two-grating structure. G1 is the upper grating. G2 is the lower grating. G1 twisted around the x<sub>0</sub> axis with a pitch angle of <span class="html-italic">θ</span>.</p>
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<p>Simulated normalized intensity field of Talbot images behind G1. Simulations of Talbot images with <span class="html-italic">θ</span> of 0°, 1° and 2°, respectively.</p>
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<p>The relationship between the pitch angle and the shift of the Talbot image. The black dots indicate the simulated value of the transversal shift of the Talbot image. The red line indicates the linear fitting straight line (R<sup>2</sup> &gt; 99%). In the simulation, the number of grating lines was 10 and the distance from the center of the Talbot image to G1 was L<sub>1</sub> = 4 μm.</p>
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<p>(<b>a</b>) Schematic diagrams of the simulated figures with <span class="html-italic">θ</span> = 0° and <span class="html-italic">θ</span> = 2°, respectively. (<b>b</b>) Transmission light of a two-grating structure consisting of two optical microgratings with a different <span class="html-italic">θ</span> of G1. The positions of the two gratings are indicated by the red arrows.</p>
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<p>Simulated transmission intensity with different distances between the two gratings in which <span class="html-italic">Z</span> = 2.58 µm, 5.16 µm, 9.03 µm and 10.32 µm, respectively.</p>
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<p>Simulated transmission intensity with different numbers of grating lines in which <span class="html-italic">N</span> was 100, 150 and 200, respectively.</p>
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<p>Simulated transmission intensity with different grating periods in which <span class="html-italic">d</span> = 2 µm, 3 µm and 4 µm, respectively.</p>
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<p>(<b>a</b>) Optical image of the experimental setup. (<b>b</b>) Schematic diagram of the proposed sensor. (<b>c</b>) Image of the micrograting used in the experiment from an optical microscope. (<b>d</b>) Image of the micrograting from a scanning electron microscope.</p>
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<p>The output of the photodetector at <span class="html-italic">Z</span> = 400 μm and 410 μm, respectively.</p>
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<p>The output of the photodetector with <span class="html-italic">d</span> = 2 μm and 3 μm.</p>
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<p>Linear fitting between transmitted intensity and the input pitch angle within a range from 0.04° to 0.15°. The experiment was repeated three times. The black dots show the average value of experimental results.</p>
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18 pages, 2143 KiB  
Article
Remote Non-Invasive Fabry-Pérot Cavity Spectroscopy for Label-Free Sensing
by Abeer Al Ghamdi, Benjamin Dawson, Gin Jose and Almut Beige
Sensors 2023, 23(1), 385; https://doi.org/10.3390/s23010385 - 29 Dec 2022
Cited by 2 | Viewed by 2245
Abstract
One way of optically monitoring molecule concentrations is to utilise the high sensitivity of the transmission and reflection rates of Fabry-Pérot cavities to changes of their optical properties. Up to now, intrinsic and extrinsic Fabry-Pérot cavity sensors have been considered with analytes either [...] Read more.
One way of optically monitoring molecule concentrations is to utilise the high sensitivity of the transmission and reflection rates of Fabry-Pérot cavities to changes of their optical properties. Up to now, intrinsic and extrinsic Fabry-Pérot cavity sensors have been considered with analytes either being placed inside the resonator or coupled to evanescent fields on the outside. Here we demonstrate that Fabry-Pérot cavities can also be used to monitor molecule concentrations non-invasively and remotely, since the reflection of light from the target molecules back into the Fabry-Pérot cavity adds upwards peaks to the minima of its overall reflection rate. Detecting the amplitude of these peaks reveals information about molecule concentrations. By using an array of optical cavities, a wide range of frequencies can be probed at once and a unique optical fingerprint can be obtained. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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Figure 1
<p>Current Fabry-Pérot cavity sensors can be divided into two main categories. (<b>a</b>) In the case of intrinsic sensors, the target molecules are placed on the inside, where they alter the effective cavity length via a change in refractive index. When driven by a laser field, the resonance frequency of the cavity shifts and the line width of the signal can broaden. (<b>b</b>) In the case of extrinsic sensors, the target molecules are placed on the outside of one of the cavity mirrors in order to alter its reflection rate, thereby also changing the optical properties of the cavity.</p>
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<p>In this paper, we propose an alternative way of using Fabry-Pérot cavities in sensing applications. Here, the substance which we want to analyse is some distance away from the resonator. Hence, we refer to this type of sensor in the following as a remote Fabry-Pérot cavity sensor. If the sample contains atomic particles with optical transitions near the resonance frequency of the sensor, the coherent back reflection of light affects the overall transmission rate of the system. The above experimental setup effectively consists of many mirrors. The measurement signal is an effective frequency-dependent reflection rate of the molecules and, as we shall see below, provides information about their concentration.</p>
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<p>Alternative design of a remote sensor with increased selectivity, which allows for different resonant frequencies to be probed at once. The sensor contains a bundle of optical fibres encased in a protective sheath and embedded with cavities of different lengths <math display="inline"><semantics> <msub> <mi>L</mi> <mn>0</mn> </msub> </semantics></math>. By measuring the resultant change for each resonance frequency from a known baseline, the type and concentration of the sample to be measured can be determined more easily.</p>
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<p>Schematic view of an asymmetric mirror interface with coherent light absorption. The mirror consists of a reflecting layer which may be covered on both sides by thin layers of absorbing material. On the right-hand side, it is attached to a dielectric medium with a refractive index <math display="inline"><semantics> <mrow> <msub> <mi>n</mi> <mn>1</mn> </msub> <mo>≠</mo> <mn>1</mn> </mrow> </semantics></math>. On the left, the mirror interface borders on air with a refractive index <math display="inline"><semantics> <mrow> <msub> <mi>n</mi> <mn>0</mn> </msub> <mo>=</mo> <mn>1</mn> </mrow> </semantics></math>. Since light approaching the mirror from different sides might experience different absorption rates, the overall reflection and transmission rates of the mirror interface, <math display="inline"><semantics> <msubsup> <mi>r</mi> <mi>a</mi> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </msubsup> </semantics></math>, <math display="inline"><semantics> <msubsup> <mi>r</mi> <mi>b</mi> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </msubsup> </semantics></math>, <math display="inline"><semantics> <msubsup> <mi>t</mi> <mi>a</mi> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </msubsup> </semantics></math> and <math display="inline"><semantics> <msubsup> <mi>t</mi> <mi>b</mi> <mrow> <mo>(</mo> <mn>1</mn> <mo>)</mo> </mrow> </msubsup> </semantics></math>, are in general not the same, even when referring to the case with the mirror being placed in air.</p>
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<p>Schematic view of a Fabry-Pérot cavity, which consists of two mirrors, M1 and M2, with a distance <math display="inline"><semantics> <msub> <mi>L</mi> <mn>0</mn> </msub> </semantics></math> between them. On its right-hand side, the cavity borders with a medium with a refractive index <math display="inline"><semantics> <mrow> <msub> <mi>n</mi> <mn>1</mn> </msub> <mo>≠</mo> <mn>1</mn> </mrow> </semantics></math>. All other spaces are filled with air. As in <a href="#sensors-23-00385-f004" class="html-fig">Figure 4</a>, the <math display="inline"><semantics> <msubsup> <mi>r</mi> <mi>i</mi> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </msubsup> </semantics></math> and <math display="inline"><semantics> <msubsup> <mi>t</mi> <mi>i</mi> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </msubsup> </semantics></math> denote transmission and reflection rates, while the <math display="inline"><semantics> <msubsup> <mi>E</mi> <mi>i</mi> <mi>in</mi> </msubsup> </semantics></math> and <math display="inline"><semantics> <msubsup> <mi>E</mi> <mi>i</mi> <mi>out</mi> </msubsup> </semantics></math> with <math display="inline"><semantics> <mrow> <mi>i</mi> <mo>=</mo> <mi>a</mi> <mo>,</mo> <mi>b</mi> <mo>,</mo> <mi>c</mi> <mo>,</mo> <mi>d</mi> </mrow> </semantics></math> denote complex electric field amplitudes.</p>
Full article ">Figure 6
<p>The dependence of the overall reflection rate <math display="inline"><semantics> <mrow> <msup> <mi>R</mi> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </msup> <mrow> <mo>(</mo> <mi>ω</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> in Equation (<a href="#FD23-sensors-23-00385" class="html-disp-formula">23</a>) on the on the frequency <math display="inline"><semantics> <mi>ω</mi> </semantics></math> of the incoming light. Here, we consider symmetric mirrors without absorption and choose all reflection and transmission rates as suggested in Equation (<a href="#FD22-sensors-23-00385" class="html-disp-formula">22</a>). In addition, we assume that <math display="inline"><semantics> <mrow> <mrow> <mo stretchy="false">|</mo> </mrow> <msubsup> <mi>r</mi> <mi>a</mi> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </msubsup> <msup> <mrow> <mo stretchy="false">|</mo> </mrow> <mn>2</mn> </msup> <mo>=</mo> <msup> <mrow> <mo stretchy="false">|</mo> <msubsup> <mi>r</mi> <mi>c</mi> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </msubsup> <mo stretchy="false">|</mo> </mrow> <mn>2</mn> </msup> <mo>=</mo> <mn>0.36</mn> </mrow> </semantics></math> (blue), 0.49 (red), 0.64 (yellow) and 0.81 (purple). The figure shows the typical reflection spectrum of a Fabry-Pérot cavity. At the resonance frequency of the resonator, <math display="inline"><semantics> <mrow> <msup> <mi>R</mi> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </msup> <mrow> <mo>(</mo> <mi>ω</mi> <mo>)</mo> </mrow> <mo>=</mo> <mn>0</mn> </mrow> </semantics></math>, independent of the reflection rates of the two mirrors. Increasing the mirror reflection rates, increases the quality factor <span class="html-italic">Q</span> of the cavity and results in a narrower downwards peak in the cavity resonance fluorescence spectrum <math display="inline"><semantics> <mrow> <mi>R</mi> <mo>(</mo> <mi>ω</mi> <mo>)</mo> </mrow> </semantics></math>.</p>
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<p>Schematic view of a three-mirror system, which contains two mirrors <math display="inline"><semantics> <msub> <mi>M</mi> <mn>1</mn> </msub> </semantics></math> and <math display="inline"><semantics> <msub> <mi>M</mi> <mn>2</mn> </msub> </semantics></math>, separated by a distance of <math display="inline"><semantics> <msub> <mi>L</mi> <mn>0</mn> </msub> </semantics></math> and a third mirror, <math display="inline"><semantics> <msub> <mi>M</mi> <mn>3</mn> </msub> </semantics></math>, a distance of <math display="inline"><semantics> <msub> <mi>L</mi> <mn>1</mn> </msub> </semantics></math> away from the <math display="inline"><semantics> <msub> <mi>M</mi> <mn>1</mn> </msub> </semantics></math>–<math display="inline"><semantics> <msub> <mi>M</mi> <mn>2</mn> </msub> </semantics></math> cavity. In a realistic scenario, the setup might be attached to a dielectric medium with a refractive index <math display="inline"><semantics> <mrow> <mi>n</mi> <mo>≠</mo> <mn>1</mn> </mrow> </semantics></math>. The figure also shows the relevant electric field amplitudes <math display="inline"><semantics> <msubsup> <mi>E</mi> <mi>i</mi> <mi>in</mi> </msubsup> </semantics></math> and <math display="inline"><semantics> <msubsup> <mi>E</mi> <mi>i</mi> <mi>out</mi> </msubsup> </semantics></math> with <math display="inline"><semantics> <mrow> <mi>i</mi> <mo>=</mo> <mi>a</mi> <mo>,</mo> <mi>b</mi> <mo>,</mo> <mi>c</mi> <mo>,</mo> <mi>d</mi> </mrow> </semantics></math> near the relevant mirror interfaces. However, notice that these reflect the case where the medium is replaced by air, as described in <a href="#sec2dot1-sensors-23-00385" class="html-sec">Section 2.1</a>.</p>
Full article ">Figure 8
<p>To illustrate the effect of randomly-positioned mirrors on the overall reflection rate of a Fabry-Pérot cavity, the figure shows the dependence of <math display="inline"><semantics> <mrow> <mover> <mrow> <msup> <mi>R</mi> <mrow> <mo>(</mo> <mn>3</mn> <mo>)</mo> </mrow> </msup> <mrow> <mo>(</mo> <mi>ω</mi> <mo>)</mo> </mrow> </mrow> <mo>¯</mo> </mover> <mo>−</mo> <msup> <mi>R</mi> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </msup> <mrow> <mo>(</mo> <mi>ω</mi> <mo>)</mo> </mrow> </mrow> </semantics></math> in Equation (<a href="#FD32-sensors-23-00385" class="html-disp-formula">32</a>) on the frequency <math display="inline"><semantics> <mi>ω</mi> </semantics></math> of the incoming light. Here, <math display="inline"><semantics> <mrow> <mrow> <mo stretchy="false">|</mo> </mrow> <msubsup> <mi>r</mi> <mi>a</mi> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </msubsup> <msup> <mrow> <mo stretchy="false">|</mo> </mrow> <mn>2</mn> </msup> <mo>=</mo> <msup> <mrow> <mo stretchy="false">|</mo> <msubsup> <mi>r</mi> <mi>c</mi> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </msubsup> <mo stretchy="false">|</mo> </mrow> <mn>2</mn> </msup> <mo>=</mo> <mn>0.81</mn> </mrow> </semantics></math>, while <math display="inline"><semantics> <mrow> <mrow> <mo stretchy="false">|</mo> </mrow> <msubsup> <mi>r</mi> <mi>c</mi> <mrow> <mo>(</mo> <mn>3</mn> <mo>)</mo> </mrow> </msubsup> <msup> <mrow> <mo stretchy="false">|</mo> </mrow> <mn>2</mn> </msup> <mo>=</mo> <mn>0.01</mn> </mrow> </semantics></math> (blue), 0.04 (red), 0.07 (yellow) and 0.1 (purple). The difference is a small and narrow upwards peak of a certain <span class="html-italic">full width at half the maximum</span> (FWHM) and with an amplitude given by <math display="inline"><semantics> <mrow> <mrow> <mo stretchy="false">|</mo> </mrow> <msubsup> <mi>r</mi> <mi>c</mi> <mrow> <mo>(</mo> <mn>3</mn> <mo>)</mo> </mrow> </msubsup> <msup> <mrow> <mo stretchy="false">|</mo> </mrow> <mn>2</mn> </msup> </mrow> </semantics></math>.</p>
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<p>Schematic view of an experimental setup, which contains a Fabry-Pérot cavity as well as a group of tiny mirrors, which are randomly positioned in a medium with refractive index <math display="inline"><semantics> <mrow> <mi>n</mi> <mo>≠</mo> <mn>1</mn> </mrow> </semantics></math>. These additional mirrors occupy a volume of length <math display="inline"><semantics> <mrow> <mo>Δ</mo> <mi>L</mi> </mrow> </semantics></math> and covering an area <math display="inline"><semantics> <mi>α</mi> </semantics></math>, which is placed some distance <math display="inline"><semantics> <msub> <mi>L</mi> <mn>1</mn> </msub> </semantics></math> away from the cavity. An incoming laser with its cross section given by <math display="inline"><semantics> <mi>α</mi> </semantics></math> approaches the cavity and the additional mirrors from a perpendicular direction. For simplicity, we assume here that the additional mirrors only cover a relatively small percentage of the area such that each one of them is likely to be observed by the incoming laser light.</p>
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<p>The dependence of the overall reflection rate <math display="inline"><semantics> <mrow> <mi>R</mi> <mo>(</mo> <mi>ω</mi> <mo>)</mo> </mrow> </semantics></math> in Equation (<a href="#FD37-sensors-23-00385" class="html-disp-formula">37</a>) of the Fabry-Pérot cavity in <a href="#sensors-23-00385-f009" class="html-fig">Figure 9</a> on the frequency <math display="inline"><semantics> <mi>ω</mi> </semantics></math> of the incoming light. Here the mirror parameters are <math display="inline"><semantics> <mrow> <mrow> <mo stretchy="false">|</mo> </mrow> <msubsup> <mi>r</mi> <mi>a</mi> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </msubsup> <msup> <mrow> <mo stretchy="false">|</mo> </mrow> <mn>2</mn> </msup> <mo>=</mo> <msup> <mrow> <mo stretchy="false">|</mo> <msubsup> <mi>r</mi> <mi>c</mi> <mrow> <mo>(</mo> <mn>2</mn> <mo>)</mo> </mrow> </msubsup> <mo stretchy="false">|</mo> </mrow> <mn>2</mn> </msup> <mo>=</mo> <mn>0.81</mn> </mrow> </semantics></math>, while <math display="inline"><semantics> <mrow> <mrow> <mo stretchy="false">|</mo> </mrow> <msubsup> <mi>r</mi> <mi>c</mi> <mrow> <mo>(</mo> <mn>3</mn> <mo>)</mo> </mrow> </msubsup> <msup> <mrow> <mo stretchy="false">|</mo> </mrow> <mn>2</mn> </msup> <mo>=</mo> <mn>0.1</mn> </mrow> </semantics></math>. In addition, <math display="inline"><semantics> <mrow> <msub> <mi>P</mi> <mi>N</mi> </msub> <mrow> <mo>(</mo> <mo>≥</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow> </semantics></math> equals 0.6 (blue), 0.7 (red), 0.8 (yellow) and 0.9 (purple). The graphs have again been calculated using Equations (<a href="#FD23-sensors-23-00385" class="html-disp-formula">23</a>) and (<a href="#FD32-sensors-23-00385" class="html-disp-formula">32</a>) and shows that the presence of a relatively large number of tiny, randomly-positioned mirrors increases the minimum of the reflection rate <math display="inline"><semantics> <mrow> <mi>R</mi> <mo>(</mo> <mi>ω</mi> <mo>)</mo> </mrow> </semantics></math> of the Fabry-Pérot cavity. Instead of zero, the minimum now equals <math display="inline"><semantics> <msub> <mi>R</mi> <mi>min</mi> </msub> </semantics></math> in Equation (<a href="#FD38-sensors-23-00385" class="html-disp-formula">38</a>).</p>
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<p>An alternative view on the remote Fabry-Pérot cavity sensor in <a href="#sensors-23-00385-f002" class="html-fig">Figure 2</a>. Here, the target molecules are randomly distributed within a volume <span class="html-italic">V</span> of length <math display="inline"><semantics> <mrow> <mo>Δ</mo> <mi>L</mi> </mrow> </semantics></math> a distance <math display="inline"><semantics> <msub> <mi>L</mi> <mn>1</mn> </msub> </semantics></math> away from the resonator. Moreover, <math display="inline"><semantics> <mrow> <mo>Δ</mo> <mi>A</mi> </mrow> </semantics></math> and <math display="inline"><semantics> <mi>α</mi> </semantics></math> denote the cross section of a single molecule and <math display="inline"><semantics> <mi>α</mi> </semantics></math> is the area that the incoming laser light excites. Our hypothesis here is that the molecules closely resemble tiny semitransparent mirrors, which suggest the same optical response of the above experimental setup and the experimental setup shown in <a href="#sensors-23-00385-f009" class="html-fig">Figure 9</a>.</p>
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12 pages, 4709 KiB  
Communication
Fossil Plant Remains Diagnostics by Laser-Induced Fluorescence and Raman Spectroscopies
by Alexey F. Bunkin, Sergey M. Pershin, Diana G. Artemova, Sergey V. Gudkov, Alexey V. Gomankov, Pavel A. Sdvizhenskii, Mikhail Ya. Grishin and Vasily N. Lednev
Photonics 2023, 10(1), 15; https://doi.org/10.3390/photonics10010015 - 24 Dec 2022
Cited by 2 | Viewed by 1952
Abstract
Fossilized plant remains have been studied simultaneously by laser induced fluorescence and Raman spectroscopies, to reveal the prospective methods for onsite or/and laser remote sensing in future extraterrestrial missions. A multiwavelength instrument, capable of fluorescence and Raman measurements, has been utilized for the [...] Read more.
Fossilized plant remains have been studied simultaneously by laser induced fluorescence and Raman spectroscopies, to reveal the prospective methods for onsite or/and laser remote sensing in future extraterrestrial missions. A multiwavelength instrument, capable of fluorescence and Raman measurements, has been utilized for the study of isolated plant fossils, as well as fossils associated with sedimentary rocks. Laser-induced fluorescence spectroscopy revealed that plant fossils and rocks’ luminosity differed significantly due to chlorophyll derivatives (chlorin, porphyrins, lignin components etc.); therefore, fossilized plants can be easily detected at rock surfaces onsite. Raman spectroscopy highly altered the fossilized graphitic material via the carbon D and G bands. Our results demonstrated that combined laser-induced fluorescence and Raman spectroscopy measurements can provide new insights into the detection of samples with biogenicity indicators such as chlorophyll and its derivatives, as well as kerogenous materials. The prospects of multiwavelength LIDAR instrument studies under fieldwork conditions are discussed for fossils diagnostics. The method of laser remote sensing can be useful in geological exploration in the search for oil, coal-bearing rocks, and rocks with a high content of organic matter. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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<p>(<b>a</b>)—Fluorescence spectra map for isolated plant fossil sample No 1865/3; (<b>b</b>)—fossil sample No 1865/3 and Spectralon<sup>®</sup> fluorescence spectra comparison with the 305 nm excitation.</p>
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<p>Laser-induced fluorescence spectra of (1) <span class="html-italic">Ginkgo biloba</span> cuticle, (2) rock sample No 4552/18, and (3) rock sample No 4388/563.</p>
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<p>Laser fluorescence spectra of (1) <span class="html-italic">Ginkgo biloba</span> leaf cuticle, (2) <span class="html-italic">Phylladoderma</span> (<span class="html-italic">Aequistomia</span>) <span class="html-italic">annulata</span> cuticle (sample No 4552/700-B), and (3) dry untreated leaf of <span class="html-italic">Ginkgo biloba</span>.</p>
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<p>Laser fluorescence spectra of (1) rock sample No 4552/18 and (2) fossilized material of <span class="html-italic">Tatarina conspicua</span> leaf (the same sample No 4552/18).</p>
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<p>Laser fluorescence spectra of (1) rock sample No 4388/563 and (2) Tatarina conspicua leaf impression with fossilized material residues (the same sample No 4388/563).</p>
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<p>Pulsed Raman spectra of fossilized sample 1865/3 and 1864_29 samples measured by LIDAR with 532 nm excitation. Spectra are summed for 1000 laser pulses to improve signal-to-noise ratio.</p>
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<p>Continuous wave Raman spectra of isolated fossilized material 1865/3 (<b>a</b>) and 1864_29 samples at the mudstone (<b>b</b>) measured by Enspectra R532 with 532 nm. (The mudstone rock Raman spectrum was multiplied 2-fold for better view). Spectra were acquired with the 180 s gate and were corrected on background emission.</p>
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13 pages, 6891 KiB  
Article
Carbon Monoxide Detection Based on the Carbon Nanotube-Coated Fiber Gas Sensor
by Yin Zhang, Wenwen Yu, Dibo Wang, Ran Zhuo, Mingli Fu and Xiaoxing Zhang
Photonics 2022, 9(12), 1001; https://doi.org/10.3390/photonics9121001 - 19 Dec 2022
Cited by 3 | Viewed by 2274
Abstract
Accurate detection of the internal decomposition components of SF6 electrical equipment plays an important role in the evaluation of equipment status. However, gas samples are usually taken out for detection at present, which makes it difficult to understand the real situation inside [...] Read more.
Accurate detection of the internal decomposition components of SF6 electrical equipment plays an important role in the evaluation of equipment status. However, gas samples are usually taken out for detection at present, which makes it difficult to understand the real situation inside the equipment. In this paper, a carbon nanotube-coated fiber gas sensor is proposed, which has the potential to be applied as a built-in gas sensor. The fiber loop ring-down (FLRD) gas detection system based on the carbon nanotube-coated fiber gas sensor was built, and the detectable decomposition components among the four typical SF6 decomposition components of SO2, SO2F2 and SOF2 and CO were analyzed. The results showed that the fiber gas sensor was most sensitive to CO. Based on density functional theory, it was found that single-walled carbon nanotubes had the best adsorption effect on CO molecules under the same conditions, with the adsorption energy reaching −0.150 Ha. The detection performance of the system for CO was studied, and the results showed that there was a good linear relationship between CO concentration and ring-down time: R2 was 0.984, the maximum inversion error of 0~200 ppm CO was 1.916 ppm, and the relative error was 4.10%. The sensitivity of the system was 0.183 ns/ppm, and the detection limit of the system was 19.951 ppm. The system had good stability, with the standard deviation of single-point repeatability being 0.00356, and the standard deviation of the long period of the experiment being 0.00606. The research results provide a new idea for the detection of SF6 decomposition components, and lay the foundation for the component detection method of built-in fiber sensor of SF6 electrical equipment. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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<p>Gas detection cell.</p>
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<p>The FLRD system for gas detection.</p>
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<p>The attenuated pulse waveforms under different collocations of the couplers.</p>
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<p>The attenuated pulse waveforms under different collocations of the couplers.</p>
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<p>The relationship between gas concentration and ring-down time.</p>
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<p>Adsorption structures of four gas molecules on single-walled carbon nanotubes.</p>
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<p>Original waveform under N<sub>2</sub> background gas.</p>
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<p>Fitting curve of exponential function corresponding to different CO concentrations.</p>
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<p>The relationship between the ring-down time and the gas concentration.</p>
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<p>Ring-down curves under the different sensor optical losses.</p>
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<p>The curve of the voltage difference between the background gas ring-down curve and the ring-down curve under the different optical losses.</p>
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<p>The repeatability of single-point measurement.</p>
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<p>Stability test.</p>
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11 pages, 2613 KiB  
Communication
Overcoming the Lead Fiber-Induced Limitation on Pulse Repetition Rate in Distributed Fiber Sensors
by Hailiang Zhang, Hui Dong, Dora Juan Juan Hu and Jianzhong Hao
Photonics 2022, 9(12), 965; https://doi.org/10.3390/photonics9120965 - 10 Dec 2022
Cited by 2 | Viewed by 1417
Abstract
Distributed fiber sensor (DFS)-based dynamic sensing has attracted increasing attention thanks to the growing demand in areas such as structural health monitoring and geophysical science. The maximum detectable frequency of DFSs depends on the maximum pulse repetition rate (MPRR), which is limited by [...] Read more.
Distributed fiber sensor (DFS)-based dynamic sensing has attracted increasing attention thanks to the growing demand in areas such as structural health monitoring and geophysical science. The maximum detectable frequency of DFSs depends on the maximum pulse repetition rate (MPRR), which is limited by the total length of the fiber under test (FUT). In some real-world applications, there is some distance between the interrogator and the monitoring site. Therefore, only a small part of the FUT acts as a sensing fiber (SF), while the other major part just acts as a lead fiber (LF), and the MPRR is limited by the LF and SF. Overcoming the LF-induced extra limitation on the MPRR is a practical problem for many DFS applications. In this paper, to the best of our knowledge, we propose a simple approach for overcoming the LF-induced extra limitation on the MPRR by dividing the DFS interrogator into two parts, for the first time. The proposed approach can be easily implemented for the real-world applicationsof DFSs whose LF is much longer than SF. It has been experimentally validated by using conventional phase-sensitive optical time domain reflectometry and Brillouin optical time domain analysis. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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<p>Schematic diagram of experimental setup for monitoring the dynamic strain of the basin ship model.</p>
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<p>Schematic diagram of ϕ-OTDR system. The gray dashed rectangle and red dashed rectangle show the difference between the conventional ϕ-OTDR system and our proposed one. Points “a” and “b” represent the connection points. In the conventional setup, the CIR is inside of the interrogator, and FUT = LF + SF. In our proposed setup, CIR is moved to the sensing site from the interrogator, and FUT = SF. AOM: acousto-optic modulator, CIR: circulator, PD: photodetector, DAQ: data acquisition card. LF: lead fiber, SF: sensing fiber.</p>
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<p>Experimental results of using conventional ϕ-OTDR setup, the total length of the FUT was about 12.5 km. (<b>a</b>) Measured incorrect ϕ-OTDR traces while filtering out the low-frequency components when the pulse repetition rate was 40 kHz. (<b>b</b>) Frequency spectrum of the measured incorrect signal located at 12,445 m, which was within the PZT zone.</p>
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<p>Experimental results of using the proposed ϕ-OTDR setup. (<b>a</b>) Measured correct ϕ-OTDR traces corresponding to the 2.19 km SF while filtering out the low-frequency components when the pulse repetition rate was 40 kHz, the location of PZT zone on the SF was the same as that in <a href="#photonics-09-00965-f003" class="html-fig">Figure 3</a>a. (<b>b</b>) Frequency spectrum of the measured signal located at 2195 m (the same location as <a href="#photonics-09-00965-f003" class="html-fig">Figure 3</a>b, 2195 m + LF = 12,445 m) within the PZT zone.</p>
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<p>Schematic diagram of BOTDA setup. The gray dashed rectangle and red dashed rectangle show the difference between the conventional BOTDA system and our proposed one. Points “a”, “b” and “c” represent the connection points. In conventional setup, the OI and CIR are inside of the interrogator, and FUT = LF1 + SF + LF2. In our proposed setup, the OI and CIR are moved to the sensing site from the interrogator, and FUT = SF. OC: optical coupler; EOM: electro-optic modulator; VOA: variable optical attenuator; OI: optical isolator; LF1: lead fiber 1; LF2: lead fiber 2; LF3: lead fiber 3; SF: sensing fiber; CIR: circulator; EDFA: erbium-doped fiber amplifier PD: photodetector, DAQ: data acquisition card.</p>
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<p>Experimental results of using the proposed BOTDA setup. (<b>a</b>) Measured BGS distribution along the sensing fiber. (<b>b</b>) Extracted strain distribution along the sensing fiber.</p>
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<p>Comparison between the conventional and our proposed BOTDA systems when the interrogator is close to the sensing zone. Points “a”, “b” and “c” represent the connection points. (<b>a</b>) Conventional BOTDA system, in which the OI and CIR are integrated into the interrogator. (<b>b</b>) By using our proposed approach, the OI and CIR are installed on-site. OI: optical isolator; CIR: circulator.</p>
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9 pages, 6658 KiB  
Communication
Fluorescence Mapping of Agricultural Fields Utilizing Drone-Based LIDAR
by Vasily N. Lednev, Mikhail Ya. Grishin, Pavel A. Sdvizhenskii, Rashid K. Kurbanov, Maksim A. Litvinov, Sergey V. Gudkov and Sergey M. Pershin
Photonics 2022, 9(12), 963; https://doi.org/10.3390/photonics9120963 - 10 Dec 2022
Cited by 7 | Viewed by 2036
Abstract
A compact and low-weight LIDAR instrument has been developed for laser-induced fluorescence spectroscopy sensing of maize fields. Fluorescence LIDAR had to be installed on a small industrial drone so that its mass was <2 kg and power consumption was <5 W. The LIDAR [...] Read more.
A compact and low-weight LIDAR instrument has been developed for laser-induced fluorescence spectroscopy sensing of maize fields. Fluorescence LIDAR had to be installed on a small industrial drone so that its mass was <2 kg and power consumption was <5 W. The LIDAR instrument utilized a continuous wave diode laser (405 nm, 150 mW) for inducing fluorescence and a small spectrometer for backscattered photons acquisition. For field testing, the LIDAR instrument was installed on a quadcopter for remote sensing of plants in a maize field in three periods of the plant’s life. The obtained fluorescence signal maps have demonstrated that the average chlorophyll content is rather non-uniform over the field and tends to increase through the plant vegetation cycle. Field tests proved the feasibility and perspectives of autonomous LIDAR sensing of agricultural fields from drones for the detection and location of plants under stress. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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<p>(<b>a</b>) Principal scheme of the LIDAR components; (<b>b</b>) general view of the ultracompact LIDAR.</p>
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<p>Photo of the LIDAR installed on the quadcopter (<b>a</b>) and during maize field sensing (<b>b</b>).</p>
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<p>(<b>a</b>)—Photo of a <span class="html-italic">Zéa máys</span> plant (arrows indicate laser-induced fluorescence measurement points); (<b>b</b>)—laser-induced fluorescence spectra for different parts of the maize plant (green leaf—top arrow in (<b>a</b>); stem—central arrow in (<b>a</b>); yellow leaf—bottom arrow in (<b>a</b>)).</p>
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<p>Aerial photo of the maize field. The white rectangle (size ~50 m × 100 m) represents the area where LIDAR measurements were carried out.</p>
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<p>Laser-induced fluorescence spectrum (black color) and background emission spectrum (red color). Spectra reproducibility estimated by 10 parallel measurements is indicated by grey and light red shaded areas.</p>
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<p>Example of the maize leaf fluorescence spectrum. A two-shouldered band of chlorophyll fluorescence can be seen at ~650–800 nm. Shaded regions indicate the spectrum integrals used for calculating the metrics.</p>
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<p>Fluorescence map for maize field acquired on 17 August 2021: (<b>a</b>) map of 680 nm band integral; (<b>b</b>) map of 740 nm band integral; (<b>c</b>) map of 680/740 nm bands ratio.</p>
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<p>Maize photos taken during characteristic periods of the plant life cycle: leaf growth (<b>a</b>), flowering (<b>b</b>), and fruit ripening (<b>c</b>), and spectra of laser-induced fluorescence measured at corresponding periods (<b>d</b>).</p>
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<p>Maps of the 680/740 nm integral ratio acquired during three periods of maize plant life cycle.</p>
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15 pages, 3841 KiB  
Article
Au Nanoparticles (NPs) Decorated Co Doped ZnO Semiconductor (Co400-ZnO/Au) Nanocomposites for Novel SERS Substrates
by Yan Zhai, Xiaoyu Zhao, Zhiyuan Ma, Xiaoyu Guo, Ying Wen and Haifeng Yang
Biosensors 2022, 12(12), 1148; https://doi.org/10.3390/bios12121148 - 8 Dec 2022
Cited by 2 | Viewed by 2475
Abstract
Au nanoparticles were decorated on the surface of Co-doped ZnO with a certain ratio of Co2+/Co3+ to obtain a novel semiconductor-metal composite. The optimal substrate, designated as Co400-ZnO/Au, is beneficial to the promotion of separation efficiency of electron [...] Read more.
Au nanoparticles were decorated on the surface of Co-doped ZnO with a certain ratio of Co2+/Co3+ to obtain a novel semiconductor-metal composite. The optimal substrate, designated as Co400-ZnO/Au, is beneficial to the promotion of separation efficiency of electron and hole in a semiconductor excited under visible laser exposure, which the enhances localized surface plasmon resonance (LSPR) of the Au nanoparticles. As an interesting finding, during Co doping, quantum dots of ZnO are generated, which strengthen the strong semiconductor metal interaction (SSSMI) effect. Eventually, the synergistic effect effectively advances the surface enhancement Raman scattering (SERS) performance of Co400-ZnO/Au composite. The enhancement mechanism is addressed in-depth by morphologic characterization, UV-visible, X-ray diffraction, photoluminescence, X-ray photoelectron spectroscopy, density functional theory, and finite difference time domain (FDTD) simulations. By using Co400-ZnO/Au, SERS detection of Rhodamine 6G presents a limit of detection (LOD) of 1 × 10−9 M. As a real application, the Co400-ZnO/Au-based SERS method is utilized to inspect tyramine in beer and the detectable concentration of 1 × 10−8 M is achieved. In this work, the doping strategy is expected to realize a quantum effect, triggering a SSSMI effect for developing promising SERS substrates in future. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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<p>XRD patterns of ZnO and Co-ZnO.</p>
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<p>Proposed band structures of the Co<sub>400</sub>-ZnO (<b>A</b>) and Co<sub>400</sub>-ZnO/Au (<b>B</b>).</p>
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<p>(<b>A</b>–<b>C</b>) TEM images of Co<sub>400</sub>-ZnO/Au at different scales. (<b>D</b>) Representative high-resolution TEM images at the interface of Co<sub>400</sub>-ZnO/Au (the regions indexed below the TEM image correspond to the marked areas by numbers 1–6).</p>
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<p>EDX elemental mappings of Co<sub>400</sub>-ZnO/Au: The overlaid image (<b>A</b>) from (<b>B</b>−<b>D</b>), and Zn (<b>B</b>), Co (<b>C</b>), and Au (<b>D</b>).</p>
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<p>XPS spectra of (<b>A</b>) XPS survey spectrum of Co<sub>400</sub>-ZnO/Au, (<b>B</b>) Zn 2p, (<b>C</b>) Co 2p, and (<b>D</b>) Au 4f for Co<sub>400</sub>-ZnO/Au.</p>
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<p>Electromagnetic field enhancement of ZnO, Co−ZnO, and Co−ZnO/Au nanostructures by using finite difference time domain simulations: (<b>A</b>–<b>C</b>) ZnO structure in xy axial under 532 nm laser; (<b>D</b>–<b>F</b>) Co−ZnO structure in xy axial under 633 nm laser; (<b>G</b>–<b>I</b>) ZnO structure in xy axial under 785 nm laser.</p>
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<p>(<b>A</b>) Concentration-dependent SERS spectra of tyramine recorded on Co<sub>400</sub>-ZnO/Au substrate. (<b>B</b>) Calibration plot based on Raman intensity at 1208 cm<sup>−1</sup>.</p>
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<p>Concentration-dependent SERS spectra of tyramine in beer on Co<sub>400</sub>−ZnO/Au substrate.</p>
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13 pages, 3351 KiB  
Article
Highly Sensitive Zinc Oxide Fiber-Optic Biosensor for the Detection of CD44 Protein
by Zhaniya U. Paltusheva, Zhannat Ashikbayeva, Daniele Tosi and Lesya V. Gritsenko
Biosensors 2022, 12(11), 1015; https://doi.org/10.3390/bios12111015 - 14 Nov 2022
Cited by 8 | Viewed by 2310
Abstract
Currently, significant progress is being made in the prevention, treatment and prognosis of many types of cancer, using biological markers to assess current physiological processes in the body, including risk assessment, differential diagnosis, screening, treatment determination and monitoring of disease progression. The interaction [...] Read more.
Currently, significant progress is being made in the prevention, treatment and prognosis of many types of cancer, using biological markers to assess current physiological processes in the body, including risk assessment, differential diagnosis, screening, treatment determination and monitoring of disease progression. The interaction of protein coding gene CD44 with the corresponding ligands promotes the processes of invasion and migration in metastases. The study of new and rapid methods for the quantitative determination of the CD44 protein is essential for timely diagnosis and therapy. Current methods for detecting this protein use labeled assay reagents and are time consuming. In this paper, a fiber-optic biosensor with a spherical tip coated with a thin layer of zinc oxide (ZnO) with a thickness of 100 nm, deposited using a low-cost sol–gel method, is developed to measure the CD44 protein in the range from 100 aM to 100 nM. This sensor is easy to manufacture, has a good response to the protein change with detection limit of 0.8 fM, and has high sensitivity to the changes in the refractive index (RI) of the environment. In addition, this work demonstrates the possibility of achieving sensor regeneration without damage to the functionalized surface. The sensitivity of the obtained sensor was tested in relation to the concentration of the control protein, as well as without antibodies—CD44. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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<p>Experimental setup for the detection of the CD44 protein using a biofunctionalized sensor.</p>
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<p>Design and calibration of the ball resonator biosensor: (<b>a</b>) two-sided profilometry of the ball resonator, measured through the CO<sub>2</sub> laser splicer; (<b>b</b>) 3D mesh of the ball resonator, highlighting the longitudinal cross-sections (grey) and azimuthal planes (purple); (<b>c</b>) S-polarization spectrum of the bare ball resonator sensor, measured for different RI values ranging from 1.351 to 1.360; (<b>d</b>) the inset shows the spectral feature around 1567 nm used for spectral tracking of the intensity; (<b>e</b>) RI calibration, showing the change of intensity as a function of the RI change and sensitivity estimation (−80.056 dB/RIU).</p>
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<p>Morphological analysis of the surface of the ball resonator optical fiber coated with a ZnO layer: (<b>a</b>) SEM image of the optical fiber sensor showing its spherical shape and surface coating; (<b>b</b>) SEM image demonstrating the grain structure of the ZnO layer; (<b>c</b>) ZnO layer thickness on the surface of the optical fiber biosensor; (<b>d</b>) TEM image of ZnO; (<b>e</b>) EDS—surface analysis of the ball resonator optical fibers demonstrating the presence of Zn, O, C, and Si elements.</p>
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<p>(<b>a</b>) X-ray diffraction pattern of ZnO layer; (<b>b</b>) FT-IR spectrum of ZnO layer.</p>
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<p>Detection of CD44 using the biofunctionalized sensor: (<b>a</b>) reflective spectrum of the biosensor; (<b>b</b>) the S-polarization spectrum is chosen for interrogation; (<b>c</b>) the inset shows the spectral portion in correspondence to the main dip; interrogation can be performed by tracking either the intensity change ΔA or the wavelength shift Δλ; (<b>d</b>,<b>e</b>) CD44 protein detection charts, reporting the wavelength shift (<b>d</b>) and the intensity change (<b>e</b>); (<b>f</b>) sensorgram for the CD44 detection, reporting the instantaneous wavelength (markers) and average (solid lines) over 109 min with 1-min sampling.</p>
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<p>Evaluation of specificity, repeatability, and regeneration of the biosensor: (<b>a</b>) the specificity was estimated by comparing the response of the CD44 biosensor from the reference value, for every concentration within 1 fM and 10 nM, to two additional ball resonator sensors fabricated with the same method and having a similar sensitivity and interrogation process. Negative control = biosensor with no antibodies; PSA control = CD44-biosensor detecting different contrations of PSA. Error bars = ±standard deviation reported over 11 consecutive measurements; (<b>b</b>) repeatability of the whole biosensing device; the chart compares the normalized response, in terms of intensity change, for 3 different ball resonator biosensors fabricated and interrogated with the same method, responding to CD44 concentrations. Furthermore, 0–100% normalized values account for the response of the sensor at 1 fM (≈LoD) and 100 nM, respectively. Solid line = average, shadowed region = ±standard deviation for 3 different sensors with same biofunctionalization; markers show individual data points; (<b>c</b>) regeneration of the biosensor: the chart displays the response of the same biosensor in the first measurement, compared with the sensor regenerated once (red) and twice (green).</p>
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9 pages, 2531 KiB  
Article
Sagnac Interferometric Temperature Sensor Based on Boron-Doped Polarization-Maintaining Photonic Crystal Fibers
by Lan Cheng, Jun Liang, Shiwei Xie and Yilin Tong
Optics 2022, 3(4), 400-408; https://doi.org/10.3390/opt3040034 - 5 Nov 2022
Cited by 2 | Viewed by 1380
Abstract
A sensitive temperature sensor was demonstrated using boron-doped polarization-maintaining photonic crystal fiber (PM-PCF) as a Sagnac interferometer (SI). This boron-doped PM-PCF combines both the geometric birefringence introduced by the PCF structure design and the stress birefringence introduced by the boron-doped stress-applying parts. However, [...] Read more.
A sensitive temperature sensor was demonstrated using boron-doped polarization-maintaining photonic crystal fiber (PM-PCF) as a Sagnac interferometer (SI). This boron-doped PM-PCF combines both the geometric birefringence introduced by the PCF structure design and the stress birefringence introduced by the boron-doped stress-applying parts. However, we found that the stress birefringence dominates the total birefringence of the sensor by numerical analysis. In the experiments, the fabricated sensor exhibited the highest temperature sensitivity of −1.83 nm/°C within the wide temperature range of 28~76 °C. The temperature sensitivity was mainly derived from the stress birefringence of boron-doped PM-PCF SI. These findings provide some support for the designation of high-precision temperature sensors. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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<p>(<bold>a</bold>) Optical micrograph of fiber ends face, and (<bold>b</bold>) schematic diagram of the SI experimental setup.</p>
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<p>The contour extraction map of the fiber end face.</p>
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<p>(<bold>a</bold>) Stress distribution diagram of PM-PCF. (<bold>b</bold>) Fundamental mode field distribution at 1550 nm.</p>
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<p>Variation of modal phase birefringence B and group birefringence Bg.</p>
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<p>(<bold>a</bold>) Variation of <inline-formula><mml:math id="mm39"><mml:semantics><mml:mrow><mml:mo>∂</mml:mo><mml:mi>B</mml:mi><mml:mrow><mml:mo>(</mml:mo><mml:mrow><mml:mi>λ</mml:mi><mml:mo>,</mml:mo><mml:mi>T</mml:mi></mml:mrow><mml:mo>)</mml:mo></mml:mrow><mml:mo>/</mml:mo><mml:mo>∂</mml:mo><mml:mi>T</mml:mi></mml:mrow></mml:semantics></mml:math></inline-formula> with wavelength at 30 °C, and (<bold>b</bold>) temperature sensitivity (S) at 28–76 °C.</p>
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<p>Experimental and simulated transmission spectra of boron-doped PM-PCF at lengths of (<bold>a</bold>) 7.2 and (<bold>b</bold>) 14.7 cm.</p>
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<p>Wavelengths variation of dips for the fibers with lengths of 7.2 and 14.7 cm.</p>
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<p>(<bold>a</bold>) Transmission spectra of PM-PCF-based SI at 14.7 cm length, and (<bold>b</bold>) wavelength variations (the discrete points) of dips A-F at the temperature range of 28–76 °C, where the solid curves are the linear fitting curves of experimental results.</p>
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12 pages, 4412 KiB  
Article
A High-Detection-Efficiency Optoelectronic Device for Trace Cadmium Detection
by Huangling Gu and Long Wang
Sensors 2022, 22(15), 5630; https://doi.org/10.3390/s22155630 - 28 Jul 2022
Cited by 1 | Viewed by 2033
Abstract
Cadmium (Cd) pollution in soil is a serious threat to food security and human health, while, currently, the most widely used detection methods cannot accurately reflect the content of heavy metals in soil. Soil heavy metal detection combined with microelectronic sensors has become [...] Read more.
Cadmium (Cd) pollution in soil is a serious threat to food security and human health, while, currently, the most widely used detection methods cannot accurately reflect the content of heavy metals in soil. Soil heavy metal detection combined with microelectronic sensors has become an important means of environmental heavy metal pollution prevention and control. X-ray Fluorescence spectrometry (XRF) can capture the excitation spectrum of metal elements, which is often used to detect Cd (II). However, due to the lack of high-performance optoelectronic devices, the analysis accuracy of the system cannot meet the requirements. Therefore, this study proposes a high-detection-efficiency photodiode (HDEPD) which can effectively improve the detection accuracy of the analyzer. The HDEPD is manufactured based on a 0.18 μm standard complementary metal-oxide-semiconductor (CMOS) process. The volt-ampere curve, spectral response and noise characteristics of the device are obtained by constructing a test circuit combined with a spectral detection system. The test results show that the threshold voltage of HDEPD is 12.15 V. When the excess bias voltage increases from 1 V to 3 V, the spectral response peak of the device appears at 500 nm, and the photon detection probability (PDP) increases from 41.7% to 52.8%. The dark count rate (DCR) is 31.9 Hz/μm2 at a 3 V excess bias voltage. Since the excitation spectrum peak of Cd (II) is between 500 nm and 600 nm, the wavelength response range of HDEPD fully meets the detection requirements of Cd (II). Full article
(This article belongs to the Topic Advances in Optical Sensors)
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<p>Three-dimensional schematic structure of HDEPD device (<b>a</b>) and cross-section of HDEPD device (<b>b</b>).</p>
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<p>Two-dimensional impact ionization distribution of HDEPD device (<b>a</b>) and one-dimensional tangent distribution of impact ionization for HDEPD device (<b>b</b>).</p>
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<p>Two-dimensional electric field distribution of HDEPD device (<b>a</b>) and one-dimensional tangent distribution of electric field in HDEPD device (<b>b</b>).</p>
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<p>Current distribution of HDEPD device under light-free conditions (<b>a</b>) and current distribution of HDEPD device under light conditions (<b>b</b>).</p>
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<p>I–V curves of HDEPD device under light-free and light conditions.</p>
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<p>Spectral simulation curve of HDEPD device.</p>
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<p>The layout of HDEPD device (<b>a</b>) and the microscope image of HDEPD device (<b>b</b>).</p>
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<p>Measured I–V curve of HDEPD device (temperature: 20 °C).</p>
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<p>Measured PDP curve of HDEPD device (temperature: 20 °C).</p>
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<p>Measured DCR of HDEPD device (temperature: 20 °C).</p>
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18 pages, 5681 KiB  
Article
Study on Quantitative Characterization of Coupling Effect between Mining-Induced Coal-Rock Mass and Optical Fiber Sensing
by Wengang Du, Jing Chai, Dingding Zhang, Yibo Ouyang and Yongliang Liu
Sensors 2022, 22(13), 5009; https://doi.org/10.3390/s22135009 - 2 Jul 2022
Cited by 3 | Viewed by 1627
Abstract
The monitoring of mine pressure, division of vertical zoning of the overburden, discrimination of key stratum structure of the overburden and monitoring of advanced abutment pressure are still the main research problems in the field of coal mining. Therefore, the promotion of development [...] Read more.
The monitoring of mine pressure, division of vertical zoning of the overburden, discrimination of key stratum structure of the overburden and monitoring of advanced abutment pressure are still the main research problems in the field of coal mining. Therefore, the promotion of development of a monitoring technology of mining-induced rock mass deformation has important research value in the mining field. There are many problems to be solved in the application of optical fiber sensing (OFS) to deformation monitoring, such as the corresponding relationship between actual deformation and optical parameters, the coupling relationship between the optical fiber and rock mass and the reasonable division of vertical zoning of the overburden. In this study, a quantitative index of coupling action between the mining rock mass and optical fiber is put forward, and the coupling coefficient of different vertical zonings is quantitatively analyzed and discussed. Based on this, five different media in contact with optical fiber are proposed. The relationship between the strain curve form, the development height of the fracture zone and the activity of key stratum is established. It is of great academic value and research significance to establish a characterization system of displacement, deformation and structural evolution of overlying strata based on optical fiber sensing technology. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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<p>Structure evolution process of mining overburden. (<b>a</b>) Fixed beam structure; (<b>b</b>) cantilever beam structure; (<b>c</b>) masonry beam structure.</p>
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<p>Mechanical model of roof fixed beam in initial mining stage.</p>
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<p>Vertical zoning division of overlying strata caused by mining.</p>
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<p>Schematic diagram of roof fracture of multi-key layer structure (<b>a</b>) initial weighting process (<b>b</b>) period weighting process.</p>
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<p>Principle of strain monitoring with BOTDA technology.</p>
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<p>Stress analysis of optical fiber in rock mass.</p>
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<p>Theoretical model of coupling relationship between rock and optical fiber.</p>
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<p>Model test system and vertical optical fiber arrangement.</p>
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<p>Model test system and vertical optical fiber arrangement.</p>
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<p>Strain distribution characteristics of rock mass detected with optical fiber at different heights. (<b>a</b>) Floor region and caving zone. (<b>b</b>) Top airspace area. (<b>c</b>) Mining-affected area under main key stratum. (<b>d</b>) Mining-affected area above main key stratum.</p>
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<p>Strain fitting functions in different vertical zones.</p>
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<p>Characteristics stage division for the deformation process of overburden based on the analysis of fiber–rock coupling.</p>
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<p>Spatiotemporal evolution of fiber–rock coupling coefficient with stope variation.</p>
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13 pages, 2582 KiB  
Article
A Combined Near-Infrared and Mid-Infrared Spectroscopic Approach for the Detection and Quantification of Glycine in Human Serum
by Thulya Chakkumpulakkal Puthan Veettil and Bayden R. Wood
Sensors 2022, 22(12), 4528; https://doi.org/10.3390/s22124528 - 15 Jun 2022
Cited by 10 | Viewed by 2889
Abstract
Serum is an important candidate in proteomics analysis as it potentially carries key markers on health status and disease progression. However, several important diagnostic markers found in the circulatory proteome and the low-molecular-weight (LMW) peptidome have become analytically challenging due to the high [...] Read more.
Serum is an important candidate in proteomics analysis as it potentially carries key markers on health status and disease progression. However, several important diagnostic markers found in the circulatory proteome and the low-molecular-weight (LMW) peptidome have become analytically challenging due to the high dynamic concentration range of the constituent protein/peptide species in serum. Herein, we propose a novel approach to improve the limit of detection (LoD) of LMW amino acids by combining mid-IR (MIR) and near-IR spectroscopic data using glycine as a model LMW analyte. This is the first example of near-IR spectroscopy applied to elucidate the detection limit of LMW components in serum; moreover, it is the first study of its kind to combine mid-infrared (25–2.5 μm) and near-infrared (2500–800 nm) to detect an analyte in serum. First, we evaluated the prediction model performance individually with MIR (ATR-FTIR) and NIR spectroscopic methods using partial least squares regression (PLS-R) analysis. The LoD was found to be 0.26 mg/mL with ATR spectroscopy and 0.22 mg/mL with NIR spectroscopy. Secondly, we examined the ability of combined spectral regions to enhance the detection limit of serum-based LMW amino acids. Supervised extended wavelength PLS-R resulted in a root mean square error of prediction (RMSEP) value of 0.303 mg/mL and R2 value of 0.999 over a concentration range of 0–50 mg/mL for glycine spiked in whole serum. The LoD improved to 0.17 mg/mL from 0.26 mg/mL. Thus, the combination of NIR and mid-IR spectroscopy can improve the limit of detection for an LMW compound in a complex serum matrix. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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<p>Conceptual representation of experiment and associated chemometrics.</p>
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<p>(<b>a</b>) Second derivatized spectra of fused ATR–NIR datasets of dried glycine deposits in 12,500–1350 nm region. Magnified view of (<b>b</b>) NIR region (2500–1350 nm) and (<b>c</b>) mid-IR region (1600–800 cm<sup>−1</sup>). Important bands in the spectra are labeled.</p>
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<p>(<b>a</b>) Baseline corrected raw spectra of glycine-spiked human serum samples. The concentration of glycine ranges from 0–50 mg/mL. (<b>b</b>) Magnified view of 2500–2000 nm region where major contribution from glycine is observed.</p>
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<p>PLS-R predicted model of glycine-spiked serum samples. (<b>a</b>) Regression plot of entire range between 0 (control) and 50 mg/mL region. (<b>b</b>) Extrapolated and remodeled 0–2.5 mg/mL region. (<b>c</b>) Corresponding regression coefficient/vector over hetero-spectral region covering NIR (2500–1350 nm) and MIR (12,500–5555 nm). (<b>d</b>) Magnified view of regression vector over 2500–1350 nm and (<b>e</b>) 12,500–5555 nm region.</p>
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<p>PCR predicted model of glycine-spiked serum samples. (<b>a</b>) Regression plot of entire range between 0 (control) and 50 mg/mL region. (<b>b</b>) Extrapolated and remodeled 0–2.5 mg/mL region. (<b>c</b>) Corresponding regression coefficient/vector over hetero-spectral region covering NIR (2500–1350 nm) and MIR (1800–800 cm<sup>−1</sup>). (<b>d</b>) Magnified view of regression vector over 2500–1350 nm and (<b>e</b>) scores plot between PC1 and PC2.</p>
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12 pages, 2687 KiB  
Article
Terahertz Metamaterial Sensor for Sensitive Detection of Citrate Salt Solutions
by Xinxin Deng, Yanchun Shen, Bingwei Liu, Ziyu Song, Xiaoyong He, Qinnan Zhang, Dongxiong Ling, Dongfeng Liu and Dongshan Wei
Biosensors 2022, 12(6), 408; https://doi.org/10.3390/bios12060408 - 13 Jun 2022
Cited by 29 | Viewed by 3189
Abstract
Citrate salts (CSs), as one type of organic salts, have been widely used in the food and pharmaceutical industries. Accurate and quantitative detection of CSs in food and medicine is very important for health and safety. In this study, an asymmetric double-opening ring [...] Read more.
Citrate salts (CSs), as one type of organic salts, have been widely used in the food and pharmaceutical industries. Accurate and quantitative detection of CSs in food and medicine is very important for health and safety. In this study, an asymmetric double-opening ring metamaterial sensor is designed, fabricated, and used to detect citrate salts combined with THz spectroscopy. Factors that influence the sensitivity of the metamaterial sensor including the opening positions and the arrangement of the metal opening ring unit, the refraction index and the thickness of the analyte deposited on the metamaterial sensor were analyzed and discussed from electromagnetic simulations and THz spectroscopy measurements. Based on the high sensitivity of the metamaterial sensor to the refractive index of the analyte, six different citrate salt solutions with low concentrations were well identified. Therefore, THz spectroscopy combined with a metamaterials sensor can provide a new, rapid, and accurate detection of citrate salts. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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<p>Schematic diagrams of the asymmetric metal ring unit with two openings at a changing angle of Δθ (<b>a</b>) and the asymmetric metal ring array at a rotation angle of φ = 40° (<b>b</b>). The THz wave TE incidence is indicated in the inset of (<b>a</b>).</p>
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<p>Transmission spectra of the metamaterial sensor with different changing angles (<b>a</b>) and with different rotation angles (<b>b</b>).</p>
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<p>Optical microscope image of the sensor.</p>
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<p>(<b>a</b>) Transmission spectra of the simulated metamaterial sensor covered by analytes with different refractive indices at <span class="html-italic">h</span> = 20 μm; (<b>b</b>) variation in the resonant peak frequency shift with the refractive index of the analyte; (<b>c</b>) transmission spectra of the simulated metamaterial sensor covered by analytes with different thicknesses at <span class="html-italic">n</span> = 1.8; (<b>d</b>) variation in the resonant peak frequency shift with the thickness of the analyte.</p>
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<p>Measured and simulated THz transmission spectra of the blank sensor without analytes.</p>
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<p>Transmission spectral curves of the blank sensor and the sensor covered with six different CSs.</p>
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<p>Refractive indices of CSs measured by THz–TDS system.</p>
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10 pages, 1629 KiB  
Article
Charge-Sensitive Optical Detection of Binding Kinetics between Phage-Displayed Peptide Ligands and Protein Targets
by Runli Liang, Yingnan Zhang, Guangzhong Ma and Shaopeng Wang
Biosensors 2022, 12(6), 394; https://doi.org/10.3390/bios12060394 - 8 Jun 2022
Viewed by 1903
Abstract
Phage display technology has been a powerful tool in peptide drug development. However, the supremacy of phage display-based peptide drug discovery is plagued by the follow-up process of peptides synthesis, which is costly and time consuming, but is necessary for the accurate measurement [...] Read more.
Phage display technology has been a powerful tool in peptide drug development. However, the supremacy of phage display-based peptide drug discovery is plagued by the follow-up process of peptides synthesis, which is costly and time consuming, but is necessary for the accurate measurement of binding kinetics in order to properly triage the best peptide leads during the affinity maturation stages. A sensitive technology is needed for directly measuring the binding kinetics of peptides on phages to reduce the time and cost of the entire process. Here, we show the capability of a charge-sensitive optical detection (CSOD) method for the direct quantification of binding kinetics of phage-displayed peptides to their target protein, using whole phages. We anticipate CSOD will contribute to streamline the process of phage display-based drug discovery. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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<p>Schematic of charge-sensitive optical detection of binding kinetics between M13 phage-displayed peptides and the protein target. An optical fiber is inserted into a glass capillary and the fiber tip is dipped into a microplate well between a pair of steel electrodes. An alternating electric field is applied through the electrodes to drive the fiber tip into oscillation. The light coming out from the tip bottom is collected by a 40× objective and measured by a quadrant cell detector. For the binding kinetics measurement, the M13 phages with peptides displayed on pVIII coating proteins are immobilized on the fiber tip, and the tip is inserted into a well with target protein. Upon binding, the net charges of the M13 phages are changed and the oscillation amplitude of the fiber tip changes as well. By recording the oscillation change in real-time, the binding kinetics between the peptide, and the protein can be quantified.</p>
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<p>CSOD data processing workflow. (<b>a</b>) Schematic shows the light out of the fiber tip projected on the center of the quadrant cell detector, where the sensor response is calculated with the equation shown on the right. <span class="html-italic">Q</span>1 to <span class="html-italic">Q</span>4 are the signals collected by the quadrant cell detector. (<b>b</b>) Representative measured detector response plotted against time with a sampling rate of 16.000 data points per second. (<b>c</b>) The calibration curve and linear region of the quadrant cell detector. (<b>d</b>) The calibrated fiber oscillation amplitudes over time. (<b>e</b>) The fast Fourier transform (FFT) result of the fiber oscillation amplitude in 1 s, where the peak at 511 Hz clearly shows the fiber vibrates at the set frequency.</p>
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<p>CSOD measurement results of PCSK9 binding to different peptides displayed on the M13 phage surface. Sample IDs are marked on the top right corner of each plot and the details of the samples are listed in <a href="#biosensors-12-00394-t002" class="html-table">Table 2</a>. (<b>a</b>) Binding curves for different peptides. The fiber probes were switched from a well containing a buffer to a well containing PCSK9 at 0 s for the measurement of the association process (red arrow) and then switched back to the buffer well at the time indicated by the black arrow for the measurement of the dissociation process. (<b>b</b>) CSOD measurement results of PCSK9 binding to negative samples. The red arrows indicate switching the fiber probe from the buffer well to a well with 1000 nM PCSK9 solution.</p>
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<p>SPR measurement results of PCSK9 binding to synthesized pep2-8. The synthesized peptide was immobilized to a streptavidin-coated gold surface. Different concentrations of PCSK9 were flowed to the surface to measure the binding kinetics. By fitting the data obtained with different concentrations, the average and standard deviation for <span class="html-italic">k<sub>a</sub></span>, <span class="html-italic">k<sub>d</sub></span>, and <span class="html-italic">K<sub>D</sub></span> were determined to be (3.88 ± 3.26) × 10<sup>5</sup> M<sup>−1</sup>s<sup>−1</sup>, (1.73 ± 0.25) × 10<sup>−1</sup> s<sup>−1</sup>, and 0.985 ± 0.724 µM, respectively.</p>
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15 pages, 2811 KiB  
Article
Single-Mode Input Fiber Combined with Multimode Sensing Fiber Used in Brillouin Optical Time-Domain Reflectometry
by Yongqian Li, Haijun Fan, Lixin Zhang, Zijuan Liu, Lei Wang, Jiaqi Wu and Shaokang Wang
Photonics 2022, 9(6), 398; https://doi.org/10.3390/photonics9060398 - 5 Jun 2022
Cited by 3 | Viewed by 2100
Abstract
Conventional single-mode fiber (SMF) Brillouin optical time-domain reflectometry (BOTDR) suffers from a low signal-to-noise ratio (SNR) and severe sensing reliability due to the influence of the stimulated Brillouin scattering threshold and bend loss. In this study, a simple and low-cost distributed sensing structure, [...] Read more.
Conventional single-mode fiber (SMF) Brillouin optical time-domain reflectometry (BOTDR) suffers from a low signal-to-noise ratio (SNR) and severe sensing reliability due to the influence of the stimulated Brillouin scattering threshold and bend loss. In this study, a simple and low-cost distributed sensing structure, with a single-mode input fiber alignment fusion and a 50 μm diameter graded index multimode sensing fiber, is designed, and the SNR characteristic is investigated. Through theoretical derivation and experimental verification, a higher SNR and excellent bending resistance are realized in BOTDR. The experimentally measured improvements in the SNR of the proposed sensing structure over the SMF at the beginning and end of a 5 km fiber are 2.5 dB and 1.3 dB, respectively. The minimum bending radius of the sensing structure is 2.25 mm, which is much better than that of the SMFs. The bidirectional optical losses between the SMF and the 50 μm graded index multimode fiber are measured by a simple experiment system and are 0.106 dB and 1.35 dB, respectively. The temperature-sensing characteristics of the sensing structure are measured by the self-built frequency-shift local heterodyne BOTDR sensor, and the measured temperature sensitivity and accuracy are 0.946 MHz/℃ and 1 ℃, respectively. The design provides a reference for BOTDR with a high SNR and has great potential for structural safety and health monitoring of infrastructures. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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<p>Brillouin gain spectra of MMF and SMF.</p>
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<p>The calculated ISNR of the designed sensing structure over SMF in the BOTDR system. (<b>a</b>) 5 km; (<b>b</b>) 20 km.</p>
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<p>Experimental setup for measuring coupling efficiency.</p>
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<p>Optical power measurement results and comparison for four structures.</p>
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<p>Experimental setup of BOTDR. PMC: polarization-maintaining coupler; PG: pulse generator; EOM: electro-optic modulator; EDFA: erbium-doped fiber amplifier; FBG: fiber Bragg grating; PS: polarization scrambler; MG: microwave generator; TOF: tunable optical filter; CO: coupler; PD: photoelectric detector; ESA: electrical spectrum analyzer.</p>
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<p>Trace of the measured Brillouin intensity.</p>
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<p>Measured Fresnel reflection signal with different coil radii.</p>
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<p>Measured Brillouin signals intensity with different bending radii. (<b>a</b>) SMF; (<b>b</b>) SMF alignment fusion to 50 μm GI-MMF.</p>
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<p>Temperature measurement results of SMF alignment fusion to 50 μm GI-MMF. (<b>a</b>) three-dimensional BGS of the whole sensing structure at a heating section of 75 ℃; (<b>b</b>) BFS at 35–75 ℃; (<b>c</b>) Linear fitting between BFS and temperature; (<b>d</b>) BGS at different temperatures.</p>
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<p>Temperature measurement results of SMF alignment fusion to 50 μm GI-MMF. (<b>a</b>) three-dimensional BGS of the whole sensing structure at a heating section of 75 ℃; (<b>b</b>) BFS at 35–75 ℃; (<b>c</b>) Linear fitting between BFS and temperature; (<b>d</b>) BGS at different temperatures.</p>
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19 pages, 5376 KiB  
Article
Sensitivity Improvement of Multi-Slot Subwavelength Bragg Grating Refractive Index Sensors by Increasing the Waveguide Height or Suspending the Sensor
by Siim Heinsalu and Katsuyuki Utaka
Sensors 2022, 22(11), 4136; https://doi.org/10.3390/s22114136 - 29 May 2022
Viewed by 2300
Abstract
We present two methods of improving wavelength sensitivity for multi-slot sub-wavelength Bragg grating (MS-SW BG) refractive index sensors. The sensor structure is designed to have high optical mode confinement in the gaps between the silicon pillars whereby the surrounding medium interaction is high, [...] Read more.
We present two methods of improving wavelength sensitivity for multi-slot sub-wavelength Bragg grating (MS-SW BG) refractive index sensors. The sensor structure is designed to have high optical mode confinement in the gaps between the silicon pillars whereby the surrounding medium interaction is high, thus improving the sensitivity. Further sensitivity improvements are achieved by increasing the waveguide height or suspending the sensor. The second option, sensor suspension, additionally requires supporting modifications in which case various configurations are considered. After the optimization of the parameters the sensors were fabricated. For the case of a waveguide height increase to 500 nm, the sensitivity of 850 nm/RIU was obtained; for sensor suspension with fully etched holes, 922 nm/RIU; for the case of not fully etched holes, 1100 nm/RIU; with the sensor lengths of about 10 µm for all cases. These values show improvements by 16.5%, 25%, and 50.5%, respectively, compared to the previous result where the height was fixed to 340 nm. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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<p>Schematic of transmission spectra for typical uniform MS-SW BG as a sensor.</p>
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<p>Optical intensity for Si MS-WG for (<b>a</b>) TE and (<b>b</b>) TM modes with SC = 3, W<sub>s</sub> = 60 nm, W<sub>t</sub> = 1100 nm, and H =220 nm.</p>
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<p>Mapping of Δ<span class="html-italic">n<sub>eff</sub></span> for (<b>a</b>) non-suspended and (<b>b</b>) suspended Si MS-WGs depending on W<sub>t</sub> and H with W<sub>s</sub> = 60 nm and SC = 3.</p>
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<p>(<b>a</b>) Top views of the various BG RI sensors: I—SW BG, II—MS-SW BG, III- suspended ladder BG, IV– SAW BG, V—CSAW BG, and VI—CWIRE BG. (<b>b</b>) The respective transmission spectra with shorter (in blue) and longer (in red) wavelength-sides of the stopband at a fixed wavelength of 1550 nm fitted by Λ values. Parameters used are as follows: H = 220 nm (I, III–VI), 500 nm (II); W<sub>t</sub> = 500 nm (I), 980 nm (II, VI), 600 nm (III), 1300 nm (III–V); W<sub>s</sub> = 60 nm (II, IV-VI); W<sub>su</sub> = 60 nm (II, V, VI); W<sub>w</sub> = 100 nm (III–V); d = 100 nm (IV–VI); c = 100 nm (V, VI); the duty ratios for all of the cases is 0.5. (<b>c</b>) E-field top views for the various BGs.</p>
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<p>Sensing characteristics of MS-SW BG RI sensors for three pillar configurations schematically shown in the top Δ<span class="html-italic">λ</span>; ER and TL dependent on W<sub>t</sub> at height of H = 220 nm, 340 nm, and H = 500 nm with a/Λ = 0.5 and W<sub>s</sub> = 60 nm, where Λ is fitted to have sensing peak at 1550 nm.</p>
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<p>SAW, CSAW, and CWIRE BG RI sensors. Δ<span class="html-italic">λ</span>, ER and TL dependence on (<b>a</b>,<b>b</b>) W<sub>p</sub> with various W<sub>s</sub> and W<sub>w</sub> values with constant values being W<sub>su</sub> = 60 nm and c = d = 100 nm or (<b>c</b>) a/(a + b) for SAW BG RI sensor and (<b>b</b>) H = 500 nm. With Λ fitted to have sensing peak at 1550 nm.</p>
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<p>(<b>a</b>) Mapping of characteristics of CSAW BG RI sensor, Δ<span class="html-italic">λ</span>, ER and TL, dependent on H and W<sub>p</sub> with other parameters as W<sub>s</sub> = W<sub>su</sub> = 60 nm, W<sub>w</sub> = d = c = 100 nm, and N = 20. (<b>b</b>) Simulated transmission spectra for various W<sub>p</sub> values with H = 340 nm and (<b>c</b>) simulated OSCF and dependent on W<sub>p</sub>. Insets show electric field profiles in logarithmic scale at 10th pillar area cross-sections.</p>
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<p>Sensor fabrication procedure steps (<b>a</b>) Lift-off method for WG formation, (<b>b</b>) inverse exposure method for WG formation, and (<b>c</b>) sensing region suspension.</p>
Full article ">Figure 9
<p>SEM images of fabricated BG RI sensors: (<b>a</b>) SW, (<b>b</b>) MS-SW, (<b>c</b>) suspended ladder, (<b>d</b>) CSAW formed by lift-off method, (<b>e</b>) CSAW formed by inverse exposure with not-fully etched or (<b>f</b>) with fully etched, and (<b>g</b>) SAW at duty of 0.2.</p>
Full article ">Figure 10
<p>Measured transmission spectra for BG RI sensors with different surrounding medium liquids for (<b>a</b>) SW, (<b>b</b>) MS-SW, (<b>c</b>) suspended ladder, (<b>d</b>) CSAW by the lift-off method, (<b>e</b>) CSAW by the EBL inverse exposure with not fully etched holes, (<b>f</b>) with fully etched holes, and (<b>g</b>) SAW. (<b>h</b>) Measured SAW spectra for various duty ratios (a/(a + b)) in W medium. The surrounding media were W for water, Sx% (Gx%) for water with x weight concentration sugar (glycerol), and IPA for isopropyl alcohol. In (<b>f</b>) for CSAW, the simulated spectra are drawn as references for a sensing liquid with RI of pure water (W) at room temperature (RT), RI of W + 0.01, RIU at RT, and RI of W at RT + 10 K by green, black, and yellow lines, respectively.</p>
Full article ">Figure 11
<p>(<b>a</b>) Observed lag effect on a silicon wafer samples with grating periods of 200 nm (<b>left</b>) and 1 µm (<b>right</b>) with duty of 0.5 by inverse exposure method. (<b>b</b>) Schematic cross-sections of the MS WG and respective E-field profiles with fully etched (<b>left</b>) and not fully etched holes (<b>right</b>), with design parameters the same as in <a href="#sensors-22-04136-f010" class="html-fig">Figure 10</a>e.</p>
Full article ">Figure A1
<p>SEM images of (<b>a</b>–<b>d</b>) MS-SW, (<b>e</b>), (<b>f</b>) CWIRE, (<b>g</b>) CSAW, and (<b>h</b>) SAW; MS-SW for WG thickness H = 500 nm in (<b>a</b>) zoomed-out and (<b>b</b>) zoomed-in views etched with 20 nm Ni mask, and (<b>c</b>) zoomed-in view etched with 40 nm Ni mask. (<b>d</b>) Etched by inverse exposure method with EBL resist mask thickness H = 520 nm with etching time of 90 s. CWIRE BG fabricated by (<b>e</b>) lift-off and (<b>f</b>) inverse exposure methods. Destroyed CSAW and SAW BGs due to (<b>g</b>) acid cleaning or (<b>h</b>) blower usage on the samples after measurements.</p>
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17 pages, 14192 KiB  
Article
High Sensitivity Surface Plasmon Resonance Sensor Based on a Ge-Doped Defect and D-Shaped Microstructured Optical Fiber
by Nilson H. O. Cunha and José P. Da Silva
Sensors 2022, 22(9), 3220; https://doi.org/10.3390/s22093220 - 22 Apr 2022
Cited by 10 | Viewed by 2316
Abstract
In this work a plasmonic sensor with a D-Shaped microstructured optical fiber (MOF) is proposed to detect a wide range of analyte refractive index (RI ;na) by doping the pure silica (SiO2) core [...] Read more.
In this work a plasmonic sensor with a D-Shaped microstructured optical fiber (MOF) is proposed to detect a wide range of analyte refractive index (RI ;na) by doping the pure silica (SiO2) core with distinct concentrations of Germanium Dioxide (GeO2), causing the presentation of high spectral sensitivity. In this case, the fiber is shaped by polishing a coating of SiO2, on the region that will be doped with GeO2, in the polished area, a thin gold (Au) layer, which constitutes the plasmonic material, is introduced, followed by the analyte, in a way which the gold layer is deposited between the SiO2. and the analyte. The numerical results obtained in the study shows that the sensor can determine efficiently a range of 0.13 refractive index units (RIU), with a limit operation where na varies from 1.32 to 1.45. Within this application, the sensor has reached an average wavelength sensitivity (WS) of up to 11,650.63 nm/RIU. With this level of sensitivity, the D-Shaped format and wide range of na detection, the proposed fiber has great potential for sensing applications in several areas. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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Figure 1

Figure 1
<p>Cross section sensor design.</p>
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<p>Real and imaginary part of the gold RI, for the wavelength range between <math display="inline"><semantics> <mrow> <mn>0.24797</mn> <mrow> <mo> </mo> <mi mathvariant="sans-serif">μ</mi> <mi mathvariant="normal">m</mi> </mrow> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mn>6.1992</mn> <mrow> <mo> </mo> <mi mathvariant="sans-serif">μ</mi> <mi mathvariant="normal">m</mi> </mrow> </mrow> </semantics></math>.</p>
Full article ">Figure 3
<p>Magnetic field in fiber for: (<b>a</b>) Fiber with <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>SiO</mi> </mrow> <mn>2</mn> </msub> </mrow> </semantics></math> defect, <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="normal">n</mi> <mi mathvariant="normal">a</mi> </msub> <mo>=</mo> <mn>1.43</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">λ</mi> <mo>=</mo> <mn>1.55</mn> <mrow> <mo> </mo> <mi mathvariant="sans-serif">μ</mi> <mi mathvariant="normal">m</mi> </mrow> </mrow> </semantics></math>; (<b>b</b>) Defect with doping <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>SiO</mi> </mrow> <mn>2</mn> </msub> <mo>+</mo> <msub> <mrow> <mi>GeO</mi> </mrow> <mn>2</mn> </msub> <mrow> <mo>(</mo> <mrow> <mn>13.5</mn> <mo>%</mo> </mrow> <mo>)</mo> </mrow> <mo>,</mo> <msub> <mrow> <mrow> <mo> </mo> <mi mathvariant="normal">n</mi> </mrow> </mrow> <mi mathvariant="normal">a</mi> </msub> <mo>=</mo> <mn>1.43</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">λ</mi> <mo>=</mo> <mn>1.55</mn> <mrow> <mo> </mo> <mi mathvariant="sans-serif">μ</mi> <mi mathvariant="normal">m</mi> </mrow> </mrow> </semantics></math>.</p>
Full article ">Figure 4
<p>Detail of the LSPR in fiber with <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>SiO</mi> </mrow> <mn>2</mn> </msub> </mrow> </semantics></math> defect.</p>
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<p>1D analysis scheme of plasmonic and fundamental modes.</p>
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<p>One-dimensional <b>E</b>-field for sensor with <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>SiO</mi> </mrow> <mn>2</mn> </msub> </mrow> </semantics></math> defect for: (<b>a</b>) Entire diameter; (<b>b</b>) Close to SPR.</p>
Full article ">Figure 7
<p>One-dimensional <b>E</b>-field for sensor with defect doped with <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>GeO</mi> </mrow> <mn>2</mn> </msub> </mrow> </semantics></math>: (<b>a</b>) <math display="inline"><semantics> <mrow> <mn>4.1</mn> <mo>%</mo> </mrow> </semantics></math>; (<b>b</b>) <math display="inline"><semantics> <mrow> <mn>6.3</mn> </mrow> </semantics></math>; (<b>c</b>) <math display="inline"><semantics> <mrow> <mn>13.5</mn> <mo>%</mo> </mrow> </semantics></math>; (<b>d</b>) <math display="inline"><semantics> <mrow> <mn>19.3</mn> <mo>%</mo> </mrow> </semantics></math>.</p>
Full article ">Figure 8
<p>Confinement loss versus wavelength, considering the defect: (<b>a</b>) without doping; (<b>b</b>) doped with <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>GeO</mi> </mrow> <mrow> <mn>2</mn> <mo> </mo> </mrow> </msub> <mrow> <mo>(</mo> <mrow> <mn>4.1</mn> <mo>%</mo> </mrow> <mo>)</mo> </mrow> </mrow> </semantics></math>; (<b>c</b>) doped with <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>GeO</mi> </mrow> <mn>2</mn> </msub> <mo> </mo> <mo stretchy="false">(</mo> <mn>6.3</mn> <mo>%</mo> </mrow> </semantics></math> ); (<b>d</b>) doped with <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>GeO</mi> </mrow> <mn>2</mn> </msub> <mo> </mo> <mrow> <mo>(</mo> <mrow> <mn>13.5</mn> <mo>%</mo> </mrow> <mo>)</mo> </mrow> </mrow> </semantics></math>; (<b>e</b>) doped with <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>GeO</mi> </mrow> <mn>2</mn> </msub> <mo> </mo> <mrow> <mo>(</mo> <mrow> <mn>19.3</mn> <mo>%</mo> </mrow> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
Full article ">Figure 9
<p>Relationship between effective RI and wavelength for the various detection ranges: (<b>a</b>) Defect without doping; (<b>b</b>) Doping with <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>GeO</mi> </mrow> <mn>2</mn> </msub> <mo> </mo> <mrow> <mo>(</mo> <mrow> <mn>4.1</mn> <mo>%</mo> </mrow> <mo>)</mo> </mrow> </mrow> </semantics></math>; (<b>c</b>) Doping with <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>GeO</mi> </mrow> <mrow> <mn>2</mn> <mo> </mo> </mrow> </msub> <mrow> <mo>(</mo> <mrow> <mn>6.3</mn> <mo>%</mo> </mrow> <mo>)</mo> </mrow> </mrow> </semantics></math>; (<b>d</b>) Doping with <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>GeO</mi> </mrow> <mn>2</mn> </msub> <mo> </mo> <mrow> <mo>(</mo> <mrow> <mn>13.5</mn> <mo>%</mo> </mrow> <mo>)</mo> </mrow> </mrow> </semantics></math>; (<b>e</b>) Doping with <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>GeO</mi> </mrow> <mn>2</mn> </msub> <mo> </mo> <mrow> <mo>(</mo> <mrow> <mn>19.3</mn> <mo>%</mo> </mrow> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
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<p>Sensor sensitivity regions scheme for doping with <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>GeO</mi> </mrow> <mn>2</mn> </msub> <mo> </mo> <mrow> <mo>(</mo> <mrow> <mn>19.3</mn> <mo>%</mo> </mrow> <mo>)</mo> </mrow> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi mathvariant="normal">n</mi> <mi mathvariant="normal">a</mi> </msub> <mo>=</mo> <mn>1.41</mn> </mrow> </semantics></math>.</p>
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<p>Adjustment of curves for the sensitivity values obtained: (<b>a</b>) Defect without doping; (<b>b</b>) Doping with <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>GeO</mi> </mrow> <mn>2</mn> </msub> <mo> </mo> <mrow> <mo>(</mo> <mrow> <mn>4.1</mn> <mo>%</mo> </mrow> <mo>)</mo> </mrow> </mrow> </semantics></math>; (<b>c</b>) Doping with <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>GeO</mi> </mrow> <mn>2</mn> </msub> <mo> </mo> <mrow> <mo>(</mo> <mrow> <mn>6.3</mn> <mo>%</mo> </mrow> <mo>)</mo> </mrow> </mrow> </semantics></math>; (<b>d</b>) Doping with <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>GeO</mi> </mrow> <mn>2</mn> </msub> <mo> </mo> <mrow> <mo>(</mo> <mrow> <mn>13.5</mn> <mo>%</mo> </mrow> <mo>)</mo> </mrow> </mrow> </semantics></math>; (<b>e</b>) Doping with <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>GeO</mi> </mrow> <mn>2</mn> </msub> <mo> </mo> <mrow> <mo>(</mo> <mrow> <mn>19.3</mn> <mo>%</mo> </mrow> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
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11 pages, 2970 KiB  
Communication
Sapphire Photonic Crystal Waveguides with Integrated Bragg Grating Structure
by Stefan Kefer, Gian-Luca Roth, Julian Zettl, Bernhard Schmauss and Ralf Hellmann
Photonics 2022, 9(4), 234; https://doi.org/10.3390/photonics9040234 - 1 Apr 2022
Cited by 7 | Viewed by 2755
Abstract
This contribution demonstrates photonic crystal waveguides generated within bulk planar sapphire substrates. A femtosecond laser is used to modify the refractive index in a hexagonal pattern around the pristine waveguide core. Near-field measurements reveal single-mode behavior at a wavelength of 1550 nm and [...] Read more.
This contribution demonstrates photonic crystal waveguides generated within bulk planar sapphire substrates. A femtosecond laser is used to modify the refractive index in a hexagonal pattern around the pristine waveguide core. Near-field measurements reveal single-mode behavior at a wavelength of 1550 nm and the possibility to adapt the mode-field diameter. Based on far-field examinations, the effective refractive index contrast between the pristine waveguide core and depressed cladding is estimated to 3·10−4. Additionally, Bragg gratings are generated within the waveguide core. Due to the inherent birefringence of Al2O3, the gratings exhibit two distinct wavelengths of main reflection. Each reflection peak exhibits a narrow spectral full width at a half maximum of 130 pm and can be selectively addressed by exciting the birefringent waveguide with appropriately polarized light. Furthermore, a waveguide attenuation of 1 dB cm−1 is determined. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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Figure 1

Figure 1
<p>Illustration of the sapphire crystal structure. A,C,N and R indicate the respective crystal planes.</p>
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<p>(<b>a</b>) Schematic of the employed femtosecond laser setup. (<b>b</b>) Exemplary cross-sectional schematic of a sapphire photonic crystal waveguide (S-PCWG) with integrated Bragg grating (BG). d<sub>x</sub> indicates the distance of two modification lines in x-direction, while D<sub>x</sub> and D<sub>y</sub> represent the theoretical inner hexagon diameters in x- and y-direction, respectively.</p>
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<p>Bright-field microscopy images of a sapphire photonic crystal waveguide with 5 µm modification distance: (<b>a</b>) top view; (<b>b</b>) cross-section.</p>
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<p>(<b>a</b>) Exemplary near-field image of an S-PCWG with a modification distance of 7 µm. (<b>b</b>) Intensity distribution along the x-axis cross-section for waveguides with modification distances of 7 and 9 µm. (<b>c</b>) Intensity distribution along the y-axis cross-section. (<b>d</b>) Mode-field diameter as a function of the modification distance. The respective core diameters in x- and y-direction are also indicated.</p>
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<p>(<b>a</b>) Far-field image at a relative distance change Δz of 0 mm. (<b>b</b>) Far-field image at a relative dis-tance change Δz of 10 mm. (<b>c</b>) Respective far-field diameters in x- and y-direction as a function of the relative distance change.</p>
Full article ">Figure 6
<p>(<b>a</b>) Schematic of the employed evaluation setup for S-PCWGs with integrated Bragg grating structures. (<b>b</b>) Exemplary Bragg reflection signal when an S-PCWG with a modification distance of 5 µm is excited with linearly polarized light, oriented in parallel or perpendicular to the sapphire crystal’s C-axis, as well as unpolarized radiation.</p>
Full article ">Figure 7
<p>(<b>a</b>) Schematic of Bragg grating positions within the S-PCWG. (<b>b</b>) Bragg reflection signal of both coupling directions. (<b>c</b>) Forward and backward coupling peak power ratio as a function of Bragg grating distance.</p>
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16 pages, 4764 KiB  
Article
Distorted Acquisition of Dynamic Events Sensed by Frequency-Scanning Fiber-Optic Interrogators and a Mitigation Strategy
by Hari Datta Bhatta, Roy Davidi, Arie Yeredor and Moshe Tur
Sensors 2022, 22(6), 2403; https://doi.org/10.3390/s22062403 - 21 Mar 2022
Cited by 2 | Viewed by 2045
Abstract
Fiber-optic dynamic interrogators, which use periodic frequency scanning, actually sample a time-varying measurand on a non-uniform time grid. Commonly, however, the sampled values are reported on a uniform time grid, synchronized with the periodic scanning. It is the novel and noteworthy message of [...] Read more.
Fiber-optic dynamic interrogators, which use periodic frequency scanning, actually sample a time-varying measurand on a non-uniform time grid. Commonly, however, the sampled values are reported on a uniform time grid, synchronized with the periodic scanning. It is the novel and noteworthy message of this paper that this artificial assignment may give rise to significant distortions in the recovered signal. These distortions increase with both the signal frequency and measurand dynamic range for a given sampling rate and frequency scanning span of the interrogator. They may reach disturbing values in dynamic interrogators, which trade-off scanning speed with scanning span. The paper also calls for manufacturers of such interrogators to report the sampled values along with their instants of acquisition, allowing interpolation algorithms to substantially reduce the distortion. Experimental verification of a simulative analysis includes: (i) a commercial dynamic interrogator of ‘continuous’ FBG fibers that attributes the measurand values to a uniform time grid; as well as (ii) a dynamic Brillouin Optical time Domain (BOTDA) laboratory setup, which provides the sampled measurand values together with the sampling instants. Here, using the available measurand-dependent sampling instants, we demonstrate a significantly cleaner signal recovery using spline interpolation. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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Figure 1

Figure 1
<p>(<b>a</b>) A sinusoidal measurand signal of a normalized temporal frequency of <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mrow> <mi>s</mi> <mi>i</mi> <mi>g</mi> <mi>n</mi> <mi>a</mi> <mi>l</mi> </mrow> </msub> <mo>/</mo> <msub> <mi>f</mi> <mrow> <mi>s</mi> <mi>c</mi> <mi>a</mi> <mi>n</mi> </mrow> </msub> </mrow> </semantics></math> = 0.23 (50 Hz/220 Hz) and filling factor of <math display="inline"><semantics> <mrow> <msub> <mi>ν</mi> <mrow> <mi>s</mi> <mi>i</mi> <mi>g</mi> <mi>n</mi> <mi>a</mi> <mi>l</mi> <mo>−</mo> <mi>a</mi> <mi>m</mi> <mi>p</mi> </mrow> </msub> <mo>/</mo> <msubsup> <mi>ν</mi> <mrow> <mi>s</mi> <mi>c</mi> <mi>a</mi> <mi>n</mi> </mrow> <mrow> <mi>s</mi> <mi>p</mi> <mi>a</mi> <mi>n</mi> </mrow> </msubsup> <mo>=</mo> <mn>0.3</mn> </mrow> </semantics></math> (solid-blue sinusoidal curve), is scanned by a periodic (every <math display="inline"><semantics> <mrow> <mtext> </mtext> <msub> <mi>T</mi> <mrow> <mi>s</mi> <mi>c</mi> <mi>a</mi> <mi>n</mi> </mrow> </msub> </mrow> </semantics></math> ) saw-tooth waveform (green). (<b>b</b>) The saw-tooth scanning results in a time-dependent detected power (FBG reflection [<a href="#B7-sensors-22-02403" class="html-bibr">7</a>,<a href="#B8-sensors-22-02403" class="html-bibr">8</a>], or Brillouin probe amplification [<a href="#B11-sensors-22-02403" class="html-bibr">11</a>,<a href="#B12-sensors-22-02403" class="html-bibr">12</a>,<a href="#B13-sensors-22-02403" class="html-bibr">13</a>]: red dot curves (arbitrary units). The purple X’s designate the intersection of the signal with the saw-tooth waveform, also indicating the instants where the detected power reaches it maximum. The black filled circles are the measurand sampled values (the ordinates of the X’s), attributed to the beginning of the corresponding scan periods. Only the middle ~6 scan periods are shown from a simulated temporal range of <math display="inline"><semantics> <mrow> <mrow> <mo>[</mo> <mrow> <mo>−</mo> <mn>550</mn> <mtext> </mtext> <mn>549</mn> </mrow> <mo>]</mo> </mrow> <msub> <mi>T</mi> <mrow> <mi>s</mi> <mi>c</mi> <mi>a</mi> <mi>n</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>The original sinusoidal signal (blue) of <a href="#sensors-22-02403-f001" class="html-fig">Figure 1</a>, together with its Nyquist–Shannon sinc-reconstruction (red) from the sampled values, <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mrow> <mo>{</mo> <mrow> <msub> <mi>s</mi> <mi>n</mi> </msub> </mrow> <mo>}</mo> </mrow> </mrow> <mrow> <mi>n</mi> <mo>=</mo> <mn>0</mn> </mrow> <mrow> <mi>N</mi> <mo>−</mo> <mn>1</mn> </mrow> </msubsup> </mrow> </semantics></math>, assuming the latter are attributed (see horizontal arrows) to the scans’ starting points (vertical dashed green lines). Shown are the middle ~20 scan periods out of 1100, starting at <math display="inline"><semantics> <mrow> <mo>−</mo> <mn>550</mn> <mtext> </mtext> <msub> <mi>T</mi> <mrow> <mi>s</mi> <mi>c</mi> <mi>a</mi> <mi>n</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>Hamming-weighed FFT-based spectrum of the signal acquired from its per-period intersections with the saw-tooth scanning waveform (<a href="#sensors-22-02403-f001" class="html-fig">Figure 1</a>), exhibiting significant harmonic distortion. The highest harmonic at <math display="inline"><semantics> <mrow> <mi>ξ</mi> <mo>=</mo> <mn>0.46</mn> </mrow> </semantics></math> is the signal’s second harmonic, whereas the other peaks are folded ones (see text). The time record was 1100⋅<math display="inline"><semantics> <mrow> <msub> <mi>T</mi> <mrow> <mi>s</mi> <mi>c</mi> <mi>a</mi> <mi>n</mi> </mrow> </msub> </mrow> </semantics></math> long, starting at −550<math display="inline"><semantics> <mrow> <mtext> </mtext> <msub> <mi>T</mi> <mrow> <mi>s</mi> <mi>c</mi> <mi>a</mi> <mi>n</mi> </mrow> </msub> </mrow> </semantics></math>. Incidentally, using the true signal values on the same temporal grid of period <math display="inline"><semantics> <mrow> <msub> <mi>T</mi> <mrow> <mi>s</mi> <mi>c</mi> <mi>a</mi> <mi>n</mi> </mrow> </msub> <mo>,</mo> </mrow> </semantics></math> gives rise only to a single peak at <math display="inline"><semantics> <mi>ξ</mi> </semantics></math> = 0.23.</p>
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<p>The power (magnitude-squared value) of the second harmonic of an originally pure sinusoidal signal, when acquired from its temporally non-uniform per-period intersections with the linear (instantaneous fly back) saw-tooth scanning waveform of <a href="#sensors-22-02403-f001" class="html-fig">Figure 1</a>. Simulated results are shown for a range of scaled signal frequencies (<math display="inline"><semantics> <mi>ξ</mi> </semantics></math>-legends box) and filling factors (<math display="inline"><semantics> <mi>η</mi> </semantics></math> -abscissa). The higher <math display="inline"><semantics> <mi>ξ</mi> </semantics></math> and/or <math display="inline"><semantics> <mi>η</mi> </semantics></math>, the worse the harmonic distortion. The corresponding total harmonic distortion curves lie within half a dB from the displayed second harmonic ones. The black squares represent experimental results for the Brillouin setup of <a href="#sec4-sensors-22-02403" class="html-sec">Section 4</a>. Note that a different scan pattern, such as a triangular one, will result in different curves.</p>
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<p>The sinusoidal green curve represents sinc-based reconstruction of the signal from <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mrow> <mo>{</mo> <mrow> <msub> <mover accent="true"> <mi>s</mi> <mo>^</mo> </mover> <mi>n</mi> </msub> <mo>,</mo> <msub> <mover accent="true"> <mi>τ</mi> <mo>^</mo> </mover> <mi>n</mi> </msub> </mrow> <mo>}</mo> </mrow> </mrow> <mrow> <mi>n</mi> <mo>=</mo> <mo>−</mo> <mn>550</mn> </mrow> <mrow> <mn>549</mn> </mrow> </msubsup> </mrow> </semantics></math>, where <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mrow> <mo>{</mo> <mrow> <msub> <mover accent="true"> <mi>s</mi> <mo>^</mo> </mover> <mi>n</mi> </msub> </mrow> <mo>}</mo> </mrow> </mrow> <mrow> <mi>n</mi> <mo>=</mo> <mo>−</mo> <mn>550</mn> </mrow> <mrow> <mn>549</mn> </mrow> </msubsup> </mrow> </semantics></math> are the spline-interpolated signal values on the computable uniform time grid <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mrow> <mo>{</mo> <mrow> <msub> <mover accent="true"> <mi>τ</mi> <mo>^</mo> </mover> <mi>n</mi> </msub> </mrow> <mo>}</mo> </mrow> </mrow> <mrow> <mi>n</mi> <mo>=</mo> <mo>−</mo> <mn>550</mn> </mrow> <mrow> <mn>549</mn> </mrow> </msubsup> </mrow> </semantics></math>, Equation (4). The blue pluses (+) represent a few values of the original sinusoidal signal, and their very tight proximity to the recovered green curve attests to the high quality of the reconstruction. The red curve is the one from <a href="#sensors-22-02403-f002" class="html-fig">Figure 2</a>, representing sinc-based reconstruction from <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mrow> <mo>{</mo> <mrow> <msub> <mi>s</mi> <mi>n</mi> </msub> </mrow> <mo>}</mo> </mrow> </mrow> <mrow> <mi>n</mi> <mo>=</mo> <mn>0</mn> </mrow> <mrow> <mi>N</mi> <mo>−</mo> <mn>1</mn> </mrow> </msubsup> </mrow> </semantics></math>, being attributed to the uniform time grid at the start of the scans.</p>
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<p>Spectrum of the pure sinusoidal signal of <a href="#sensors-22-02403-f001" class="html-fig">Figure 1</a>, calculated from <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mrow> <mo>{</mo> <mrow> <msub> <mover accent="true"> <mi>s</mi> <mo>^</mo> </mover> <mi>n</mi> </msub> <mo>,</mo> <msub> <mover accent="true"> <mi>τ</mi> <mo>^</mo> </mover> <mi>n</mi> </msub> </mrow> <mo>}</mo> </mrow> </mrow> <mrow> <mi>n</mi> <mo>=</mo> <mo>−</mo> <mn>550</mn> </mrow> <mrow> <mn>549</mn> </mrow> </msubsup> </mrow> </semantics></math>, where <math display="inline"><semantics> <mrow> <mo>{</mo> <msub> <mover accent="true"> <mi>s</mi> <mo>^</mo> </mover> <mi>n</mi> </msub> <mo>}</mo> </mrow> </semantics></math> are spline interpolated signal values on the computable uniform time grid <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mrow> <mo>{</mo> <mrow> <msub> <mover accent="true"> <mi>τ</mi> <mo>^</mo> </mover> <mi>n</mi> </msub> </mrow> <mo>}</mo> </mrow> </mrow> <mrow> <mi>n</mi> <mo>=</mo> <mo>−</mo> <mn>550</mn> </mrow> <mrow> <mn>549</mn> </mrow> </msubsup> </mrow> </semantics></math>, Equation (4), based on the known sampled values <math display="inline"><semantics> <mrow> <mrow> <mo>{</mo> <mrow> <msub> <mi>s</mi> <mi>n</mi> </msub> </mrow> <mo>}</mo> </mrow> </mrow> </semantics></math> and their actual sampling instants <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mrow> <mo>{</mo> <mrow> <msub> <mi>τ</mi> <mi>n</mi> </msub> </mrow> <mo>}</mo> </mrow> </mrow> <mrow> <mi>n</mi> <mo>=</mo> <mo>−</mo> <mn>550</mn> </mrow> <mrow> <mn>549</mn> </mrow> </msubsup> </mrow> </semantics></math>. Note the considerably lower harmonics, when compared with those of <a href="#sensors-22-02403-f003" class="html-fig">Figure 3</a>.</p>
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<p>Brillouin amplification in single-mode fibers. Pump light at an arbitrary frequency/wavelength, e.g., <math display="inline"><semantics> <mrow> <msub> <mi>λ</mi> <mi>B</mi> </msub> </mrow> </semantics></math> = 1550 nm, propagating in one direction in the fiber core generates narrowband gain for light propagating in the opposite direction. Gain is maximized when the frequency difference, <math display="inline"><semantics> <mrow> <msub> <mi>υ</mi> <mrow> <mi>p</mi> <mi>u</mi> <mi>m</mi> <mi>p</mi> </mrow> </msub> <mo>−</mo> <msub> <mi>υ</mi> <mrow> <mi>p</mi> <mi>r</mi> <mi>o</mi> <mi>b</mi> <mi>e</mi> </mrow> </msub> </mrow> </semantics></math>, equals the so-called Brillouin Frequency Shift, <math display="inline"><semantics> <mrow> <msub> <mi>υ</mi> <mrow> <mi>B</mi> <mi>F</mi> <mi>S</mi> </mrow> </msub> </mrow> </semantics></math>. For silica-based single-mode fibers around 1550 nm, <math display="inline"><semantics> <mrow> <msub> <mi>υ</mi> <mrow> <mi>B</mi> <mi>F</mi> <mi>S</mi> </mrow> </msub> </mrow> </semantics></math> is ~11 GHz and the Brillouin gain bandwidth is ~30 MHz for pulses longer than ~40 ns. Of crucial importance for sensing applications is the fact that <math display="inline"><semantics> <mrow> <msub> <mi>υ</mi> <mrow> <mi>B</mi> <mi>F</mi> <mi>S</mi> </mrow> </msub> </mrow> </semantics></math> is a function of both strain and temperature, mainly through the dependence of the local acoustic velocity, <math display="inline"><semantics> <mrow> <msub> <mi>V</mi> <mi>A</mi> </msub> <mo>,</mo> </mrow> </semantics></math> on these two measurands.</p>
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<p>A longitudinally vibrating fiber is interrogated by either an all-polarization-maintaining F-BOTDA setup, producing temporally non-uniform samples, or by a uniformly sampling white-light spectrometer-based interrogator that measures the response of an on-fiber FBG. The <math display="inline"><semantics> <mrow> <msub> <mi>λ</mi> <mi>B</mi> </msub> </mrow> </semantics></math> of the inscribed FBG is away from the Brillouin scanning region. AWG: Arbitrary Waveform Generator, RF: Radio frequency, SOA: Semiconductor Optical Amplifier/switch, EDFA: Erbium Doped Fiber Amplifier, ISO: Optical isolator, FBG: Fiber Bragg Grating inscribed on the FUT, PD: Photo diode, CIR: Circulator, EOM: Electro-Optic Modulator, LD: Narrowband Laser Diode, DAQ: Data Acquisition, VSG: Vector Signal Generator, ATT: Attenuator.</p>
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<p>Strain signal spectrum at 50 Hz longitudinal vibrations, interrogated by the spectrometer-based temporally uniform interrogator. Highest harmonic (at 100 Hz) is &gt;37 dB below the signal.</p>
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<p>(<b>Left</b>) Hamming-weighed FFT spectrum of raw BFS vs. time 50 Hz vibration data, obtained from the experimental setup of <a href="#sensors-22-02403-f008" class="html-fig">Figure 8</a>. The scan rate is 164 Hz, the scan range is 108 MHz and the vibration amplitude is 17 MHz, resulting in <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mrow> <mi>s</mi> <mi>i</mi> <mi>g</mi> <mi>n</mi> <mi>a</mi> <mi>l</mi> </mrow> </msub> <mo>/</mo> <msub> <mi>f</mi> <mrow> <mi>s</mi> <mi>c</mi> <mi>a</mi> <mi>n</mi> </mrow> </msub> </mrow> </semantics></math> = 0.3 and <math display="inline"><semantics> <mrow> <msub> <mi>ν</mi> <mrow> <mi>s</mi> <mi>i</mi> <mi>g</mi> <mi>n</mi> <mi>a</mi> <mi>l</mi> <mo>−</mo> <mi>a</mi> <mi>m</mi> <mi>p</mi> </mrow> </msub> <mo>/</mo> <msubsup> <mi>ν</mi> <mrow> <mi>s</mi> <mi>c</mi> <mi>a</mi> <mi>n</mi> </mrow> <mrow> <mi>s</mi> <mi>p</mi> <mi>a</mi> <mi>n</mi> </mrow> </msubsup> </mrow> </semantics></math> = 0.16, respectively. Note the strong (−16.3 dB) second harmonic (dotted square), occurring at the folded frequency of 64 Hz (=164/2 − (2 × 50 − 164/2)). It is due to the fact the FFT algorithm implicitly treats its input temporally non-uniform data as uniform (The other peaks are folded higher harmonics). (<b>Right</b>) Using the measured instants of acquisition, <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mrow> <mo>{</mo> <mrow> <msub> <mi>τ</mi> <mi>n</mi> </msub> </mrow> <mo>}</mo> </mrow> </mrow> <mrow> <mi>n</mi> <mo>=</mo> <mn>0</mn> </mrow> <mrow> <mi>N</mi> <mo>−</mo> <mn>1</mn> </mrow> </msubsup> </mrow> </semantics></math>, and the procedure of spline interpolation of <a href="#sec3-sensors-22-02403" class="html-sec">Section 3</a>, the second harmonic is significantly attenuated to −29 dB (dotted square). Record duration is 9 s.</p>
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<p>(<b>Left</b>) Hamming-weighed FFT spectrum of raw BFS vs. time 50 Hz vibration data, obtained from the experimental setup of <a href="#sensors-22-02403-f008" class="html-fig">Figure 8</a>. Here, the scan rate is 412 Hz, the scan range is 112 MHz and the vibration amplitude 17 MHz, resulting <math display="inline"><semantics> <mrow> <msub> <mi>f</mi> <mrow> <mi>s</mi> <mi>i</mi> <mi>g</mi> <mi>n</mi> <mi>a</mi> <mi>l</mi> </mrow> </msub> <mo>/</mo> <msub> <mi>f</mi> <mrow> <mi>s</mi> <mi>c</mi> <mi>a</mi> <mi>n</mi> </mrow> </msub> </mrow> </semantics></math> = 0.12 and <math display="inline"><semantics> <mrow> <msub> <mi>ν</mi> <mrow> <mi>s</mi> <mi>i</mi> <mi>g</mi> <mi>n</mi> <mi>a</mi> <mi>l</mi> <mo>−</mo> <mi>a</mi> <mi>m</mi> <mi>p</mi> </mrow> </msub> <mo>/</mo> <msubsup> <mi>ν</mi> <mrow> <mi>s</mi> <mi>c</mi> <mi>a</mi> <mi>n</mi> </mrow> <mrow> <mi>s</mi> <mi>p</mi> <mi>a</mi> <mi>n</mi> </mrow> </msubsup> </mrow> </semantics></math> = 0.15, respectively. Note the −26 dB second harmonic peak at 100 Hz (dotted square). While lower than the −16.3 dB one of <a href="#sensors-22-02403-f010" class="html-fig">Figure 10</a>, it is still higher than the spectrometer-based measurement of below −37 dB (The observed peaks are again folded high harmonics). (<b>Right</b>) Using the measured instants of acquisition, <math display="inline"><semantics> <mrow> <msubsup> <mrow> <mrow> <mo>{</mo> <mrow> <msub> <mi>τ</mi> <mi>n</mi> </msub> </mrow> <mo>}</mo> </mrow> </mrow> <mrow> <mi>n</mi> <mo>=</mo> <mn>0</mn> </mrow> <mrow> <mi>N</mi> <mo>−</mo> <mn>1</mn> </mrow> </msubsup> </mrow> </semantics></math>, and the procedure of spline interpolation of <a href="#sec3-sensors-22-02403" class="html-sec">Section 3</a>, the second harmonic is down to −44.7 dB (dotted square) but there is now a dominant harmonic at −31 dB. Record duration is 3.6 s.</p>
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<p>Setup for the CFBG experiment, using a polyimide-coated composite FUT. Taking advantage of the high spatial resolution of the CFBG interrogator (&lt;1 cm), a very short CFBG fiber is used. The coreless fiber segment, serving as a high insertion loss, bidirectional isolator, allows for the CFBG interrogation to be augmented by an independent and simultaneous uniformly triggered FBG interrogation of the FUT vibrations.</p>
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<p>Hamming-weighed FFT spectra of the strain of the vibrating fiber in <a href="#sensors-22-02403-f012" class="html-fig">Figure 12</a>, simultaneously measured by the two interrogators. The scaled vibration frequency and amplitude were <math display="inline"><semantics> <mrow> <mi>ξ</mi> <mo>=</mo> <msub> <mi>f</mi> <mrow> <mi>s</mi> <mi>i</mi> <mi>g</mi> <mi>n</mi> <mi>a</mi> <mi>l</mi> </mrow> </msub> <mo>/</mo> <msub> <mi>f</mi> <mrow> <mi>s</mi> <mi>c</mi> <mi>a</mi> <mi>n</mi> </mrow> </msub> <mo>=</mo> <mn>0.2</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <mi>η</mi> <mo>=</mo> <msub> <mi>ν</mi> <mrow> <mi>s</mi> <mi>i</mi> <mi>g</mi> <mi>n</mi> <mi>a</mi> <mi>l</mi> <mo>−</mo> <mi>a</mi> <mi>m</mi> <mi>p</mi> </mrow> </msub> <mo>/</mo> <msubsup> <mi>ν</mi> <mrow> <mi>s</mi> <mi>c</mi> <mi>a</mi> <mi>n</mi> </mrow> <mrow> <mi>s</mi> <mi>p</mi> <mi>a</mi> <mi>n</mi> </mrow> </msubsup> <mo>=</mo> <mn>0.38</mn> </mrow> </semantics></math>. (<b>Left</b>) Results from the uniformly triggered interrogator of <a href="#sec4-sensors-22-02403" class="html-sec">Section 4</a>. (<b>Right</b>) Results from the frequency-scanning CFG interrogator. While its noise level is higher, the peaks at 10 and 30 Hz are still barely seen (these &lt;−60 dB peaks are not folded harmonics, but are rather due to the insufficient spectral purity of the oscillator-shaker combination).</p>
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17 pages, 10725 KiB  
Review
Recent Advances in Surface Plasmon Resonance Sensors for Sensitive Optical Detection of Pathogens
by Joon-Ha Park, Yeon-Woo Cho and Tae-Hyung Kim
Biosensors 2022, 12(3), 180; https://doi.org/10.3390/bios12030180 - 17 Mar 2022
Cited by 54 | Viewed by 6409
Abstract
The advancement of science and technology has led to the recent development of highly sensitive pathogen biosensing techniques. The effective treatment of pathogen infections requires sensing technologies to not only be sensitive but also render results in real-time. This review thus summarises the [...] Read more.
The advancement of science and technology has led to the recent development of highly sensitive pathogen biosensing techniques. The effective treatment of pathogen infections requires sensing technologies to not only be sensitive but also render results in real-time. This review thus summarises the recent advances in optical surface plasmon resonance (SPR) sensor technology, which possesses the aforementioned advantages. Specifically, this technology allows for the detection of specific pathogens by applying nano-sized materials. This review focuses on various nanomaterials that are used to ensure the performance and high selectivity of SPR sensors. This review will undoubtedly accelerate the development of optical biosensing technology, thus allowing for real-time diagnosis and the timely delivery of appropriate treatments as well as preventing the spread of highly contagious pathogens. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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<p>Schematic of recent advances in SPR sensor technology with various nanomaterials and applications for pathogen detection.</p>
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<p>(<b>a</b>) SPR signal intensity vs. incident angle plot with polyuria (left) and oliguria (right). (<b>b</b>) Variation in parameters for different sensing medium refractive indices in pure water, polyuria, and oliguria. With permission from [<a href="#B76-biosensors-12-00180" class="html-bibr">76</a>], Copyright 2020, Springer.</p>
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<p>(<b>a</b>) Schematic illustration of the fabricated gold nanospike-based SPR sensor. (<b>b</b>) Plot representing the detection limit for the analyte. (<b>c</b>) Selective affinity test against other interference substances. With permission from [<a href="#B81-biosensors-12-00180" class="html-bibr">81</a>], Copyright 2020, ELSEVIER.</p>
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<p>(<b>a</b>) Schematic illustration of the biosensor fabrication process. (<b>b</b>) Plot indicating the limit of detection and linear range. (<b>c</b>) Selectivity of the fabricated platform. With permission from [<a href="#B83-biosensors-12-00180" class="html-bibr">83</a>], Copyright 2019, MDPI.</p>
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<p>(<b>a</b>) Schematic illustration of SPR sensor fabrication via the sandwich aptamer technique. (<b>b</b>) Linear plot of norovirus spike protein-sensing performance. (<b>c</b>) Linear plot of norovirus spike protein-sensing performance without gold nanorods. With permission from [<a href="#B88-biosensors-12-00180" class="html-bibr">88</a>], Copyright 2018, American Chemical Society.</p>
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<p>(<b>a</b>) Schematic illustration of an experimental setup to test sensors. (<b>b</b>) Field emission scanning electron microscope (FESEM) image of the fabricated optic fibre surface. (<b>c</b>) Transmission spectra plot indicating the limit of detection. (<b>d</b>) Atomic force microscope image analysis of the fabricated optic fibre surface. With permission from [<a href="#B91-biosensors-12-00180" class="html-bibr">91</a>], Copyright 2018, Elsevier.</p>
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14 pages, 6093 KiB  
Article
Silicone Rubber Fabry-Perot Pressure Sensor Based on a Spherical Optical Fiber End Face
by Changxing Jiang, Xiaohua Lei, Yuru Chen, Shaojie Lv, Xianming Liu and Peng Zhang
Sensors 2022, 22(5), 1862; https://doi.org/10.3390/s22051862 - 26 Feb 2022
Cited by 3 | Viewed by 2456
Abstract
To improve the fringe contrast and the sensitivity of Fabry-Perot (FP) pressure sensors, a silicone rubber FP pressure sensor based on a spherical optical fiber end face is proposed. The ratio of silicone rubber ingredients and the diameter and thickness of silicone rubber [...] Read more.
To improve the fringe contrast and the sensitivity of Fabry-Perot (FP) pressure sensors, a silicone rubber FP pressure sensor based on a spherical optical fiber end face is proposed. The ratio of silicone rubber ingredients and the diameter and thickness of silicone rubber diaphragm were optimized by a simulation based on experimental tests that analyzed elastic parameters, and the influence of the radius of a spherical optical fiber and the initial cavity length of the sensor on the fringe contrast was investigated and optimized. Pressure sensor samples were fabricated for pressure test and temperature cross-influence test. Gas pressure experimental results within a pressure range of 0~40 kPa show the average sensitivity of the sensor is −154.56 nm/kPa and repeatability error is less than 0.71%. Long-term pressure experimental results show it has good repeatability and stability. Temperature experimental results show its temperature cross-sensitivity is 0.143 kPa/°C. The good performance of the proposed FP pressure sensor will expand its applications in biochemical applications, especially in human body pressure monitoring. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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<p>The optical path diagram of the optical fiber FP pressure sensor.</p>
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<p>Relationship between transmission coefficient and fringe contrast of interference pattern.</p>
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<p>Structure diagram of the proposed sensor based on a spherical end face.</p>
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<p>Relationship between tensile ratio and stress.</p>
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<p>Model building diagram: (<b>a</b>) simulation model diagram and (<b>b</b>) deformation cloud diagram.</p>
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<p>Relationship between the pressure and deformation: (<b>a</b>) diameter of 150 μm, (<b>b</b>) diameter of 180 μm, and (<b>c</b>) diameter of 200 μm.</p>
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<p>A 3D diagram of simulation model in ZEMAX. (<b>a</b>) the physical model of the silicone rubber pressure sensor; (<b>b</b>) simulation parameters.</p>
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<p>Ray tracing and wavelength scanning results. (<b>a</b>) simulation result for one single wavelength, (<b>b</b>) spectrum formed by simulation results of every wavelength within the range of 1525~1565 nm.</p>
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<p>Relationship between the fringe contrast and applied pressure under different initial cavity lengths: (<b>a</b>) L = 200 μm, (<b>b</b>) L = 250 μm, (<b>c</b>) L = 300 μm, and (<b>d</b>) L = 350 μm.</p>
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<p>Spherical end faces with different radii.</p>
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<p>The fabrication process of proposed sensor.</p>
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<p>A pressure sensor sample.</p>
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<p>Sensors’ spectra: (<b>a</b>) radius is 62.5 μm, (<b>b</b>) radius is 70 μm, (<b>c</b>) radius is 80 μm, and (<b>d</b>) radius is 90 μm.</p>
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<p>Experimental setup for pressure test.</p>
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<p>Response of FP cavity length to pressure. (<b>a</b>) relationship between the cavity length change and pressure in uploading process, (<b>b</b>) relationship between the cavity length change and pressure in downloading process, (<b>c</b>) spectrum changes during the pressure loading process, (<b>d</b>) a linear fitting of experimental results.</p>
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<p>Stability test results.</p>
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<p>Test results after 7 days.</p>
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<p>Temperature test results. (<b>a</b>) Temperature change response spectra and (<b>b</b>) temperature response.</p>
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21 pages, 4539 KiB  
Article
Fibre Bragg Grating Based Interface Pressure Sensor for Compression Therapy
by James A. Bradbury, Qimei Zhang, Francisco U. Hernandez Ledezma, Ricardo Correia, Serhiy Korposh, Barrie R. Hayes-Gill, Ferdinand Tamoué, Alison Parnham, Simon A. McMaster and Stephen P. Morgan
Sensors 2022, 22(5), 1798; https://doi.org/10.3390/s22051798 - 24 Feb 2022
Cited by 4 | Viewed by 3123
Abstract
Compression therapy is widely used as the gold standard for management of chronic venous insufficiency and venous leg ulcers, and the amount of pressure applied during the compression therapy is crucial in supporting healing. A fibre optic pressure sensor using Fibre Bragg Gratings [...] Read more.
Compression therapy is widely used as the gold standard for management of chronic venous insufficiency and venous leg ulcers, and the amount of pressure applied during the compression therapy is crucial in supporting healing. A fibre optic pressure sensor using Fibre Bragg Gratings (FBGs) is developed in this paper to measure sub-bandage pressure whilst removing cross-sensitivity due to strain in the fibre and temperature. The interface pressure is measured by an FBG encapsulated in a polymer and housed in a textile to minimise discomfort for the patient. The repeatability of a manual fabrication process is investigated by fabricating and calibrating ten sensors. A customized calibration setup consisting of a programmable translation stage and a weighing scale gives sensitivities in the range 0.4–1.5 pm/mmHg (2.6–11.3 pm/kPa). An alternative calibration method using a rigid plastic cylinder and a blood pressure cuff is also demonstrated. Investigations are performed with the sensor under a compression bandage on a phantom leg to test the response of the sensor to changing pressures in static situations. Measurements are taken on a human subject to demonstrate changes in interface pressure under a compression bandage during motion to mimic a clinical application. These results are compared to the current gold standard medical sensor using a Bland–Altman analysis, with a median bias ranging from −4.6 to −20.4 mmHg, upper limit of agreement (LOA) from −13.5 to 2.7 mmHg and lower LOA from −32.4 to −7.7 mmHg. The sensor has the potential to be used as a training tool for nurses and can be left in situ to monitor bandage pressure during compression therapy. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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<p>Schematic of the optical fibre-based pressure sensor. An FBG (FBG<sub>PST</sub>) is encapsulated in a polymer to transduce applied pressure into a measurable strain–effective pressure sensing area shown in a red rectangle. Two reference FBGs (FBG<sub>ST</sub> and FBG<sub>T</sub>) sensitive to strain and temperature respectively are used to compensate for these effects on the pressure measurements. The sensors are enclosed in a textile ‘sandwich’ and are connected to an interrogator unit via an optical fibre patch cord.</p>
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<p>Customised calibration setup. (<b>a</b>) The motorised translation stage is programmed to lower the rod onto the weighing scale. The pressure sensor in its textile housing is attached to the plate of the weighing scale to keep it in place during the calibration. (<b>b</b>) The load is transferred from the translation stage to the pressure sensor via a metal rod and an aluminium metal plate. The probe is lined up over the central FBG of the sensor before starting the loading process.</p>
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<p>Experimental setup for testing the strain response of the fibre. The mould provides an anchor point to isolate FBG<sub>T</sub> from the effects of strain, the magnets hold the yellow protective tubing in place and the rest of the fibre can slide within the yellow jacket. (<b>a</b>) Labelled photograph; (<b>b</b>) labelled schematic.</p>
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<p>Experimental setup for measurements using a blood pressure cuff. A controlled volume of air is added via syringe pump to the cuff, which is wrapped around the materials on the acrylic tube. The pressure of the cuff is recorded by the manometer and is compared to the wavelength shift recorded by the interrogator.</p>
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<p>Custom-made phantom leg shown with sensors (optical fibre and PicoPress) at the approximate B1 position and with a full bandage wrap.</p>
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<p>Photos of the optical fibre sensor and the PicoPress at approximately the B1 position on a human subject.</p>
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<p>Typical calibration results of the FOPS: wavelength shift against load weight using experimental set up illustrated in <a href="#sensors-22-01798-f002" class="html-fig">Figure 2</a>.</p>
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<p>(<b>a</b>) Typical response of the 3 FBGs to the load applied for strain compensation measurements (using experimental set up in <a href="#sensors-22-01798-f003" class="html-fig">Figure 3</a>), showing the mean wavelength shift for each applied mass. (<b>b</b>) Typical results showing the relative wavelength shift in response to strain from the FBG<sub>PST</sub> encapsulated with polymer and FBG<sub>ST</sub> in the bare fibre. Although only three different masses were used, the sampling rate of the sensor compared to the settling time of the scales means a range of wavelengths were recorded for each mass.</p>
Full article ">Figure 8 Cont.
<p>(<b>a</b>) Typical response of the 3 FBGs to the load applied for strain compensation measurements (using experimental set up in <a href="#sensors-22-01798-f003" class="html-fig">Figure 3</a>), showing the mean wavelength shift for each applied mass. (<b>b</b>) Typical results showing the relative wavelength shift in response to strain from the FBG<sub>PST</sub> encapsulated with polymer and FBG<sub>ST</sub> in the bare fibre. Although only three different masses were used, the sampling rate of the sensor compared to the settling time of the scales means a range of wavelengths were recorded for each mass.</p>
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<p>(<b>a</b>) Typical results: comparison of wavelength shift produced by the sensor to the pressure from a manometer, taken on a rigid cylindrical tube and controlled by a blood pressure cuff (using the experimental set up in <a href="#sensors-22-01798-f004" class="html-fig">Figure 4</a>). (<b>b</b>–<b>e</b>) Pressure against wavelength shift for four loading and unloading cycles.</p>
Full article ">Figure 9 Cont.
<p>(<b>a</b>) Typical results: comparison of wavelength shift produced by the sensor to the pressure from a manometer, taken on a rigid cylindrical tube and controlled by a blood pressure cuff (using the experimental set up in <a href="#sensors-22-01798-f004" class="html-fig">Figure 4</a>). (<b>b</b>–<b>e</b>) Pressure against wavelength shift for four loading and unloading cycles.</p>
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<p>Typical results: wavelength shift against time underneath a compression bandage wrapped multiple times (in this case 8 layers) on a single location on the phantom leg. The displayed wavelength values are strain and temperature compensated.</p>
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<p>Pressure recorded by the Fibre Optic Sensor (after compensation for strain) compared to the PicoPress as shown in the experimental set up in <a href="#sensors-22-01798-f006" class="html-fig">Figure 6</a>. The trace has been divided into 7 sections showing the different activities the subject performs during the wrapping experiment, which are then used to perform a Bland–Altman assessment of the data across all five wrapping experiments. 1: Sitting; leg supine; 2: Sitting; leg down; 3: Standing; 4: Calf raises; 5: Standing; 6: Sitting, leg down; 7: Sitting, leg supine.</p>
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27 pages, 6428 KiB  
Article
Residual Interpolation Integrated Pixel-by-Pixel Adaptive Iterative Process for Division of Focal Plane Polarimeters
by Jie Yang, Weiqi Jin, Su Qiu, Fuduo Xue and Meishu Wang
Sensors 2022, 22(4), 1529; https://doi.org/10.3390/s22041529 - 16 Feb 2022
Cited by 5 | Viewed by 2050
Abstract
Residual interpolations are effective methods to reduce the instantaneous field-of-view error of division of focal plane (DoFP) polarimeters. However, their guide-image selection strategies are improper, and do not consider the DoFP polarimeters’ spatial sampling modes. Thus, we propose a residual interpolation method with [...] Read more.
Residual interpolations are effective methods to reduce the instantaneous field-of-view error of division of focal plane (DoFP) polarimeters. However, their guide-image selection strategies are improper, and do not consider the DoFP polarimeters’ spatial sampling modes. Thus, we propose a residual interpolation method with a new guide-image selection strategy based on the spatial layout of the pixeled polarizer array to improve the sampling rate of the guide image. The interpolation performance is also improved by the proposed pixel-by-pixel, adaptive iterative process and the weighted average fusion of the results of the minimized residual and minimized Laplacian energy guide filters. Visual and objective evaluations demonstrate the proposed method’s superiority to the existing state-of-the-art methods. The proposed method proves that considering the spatial layout of the pixeled polarizer array on the physical level is vital to improving the performance of interpolation methods for DoFP polarimeters. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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Figure 1

Figure 1
<p>Schematic diagrams of DoFP polarimeter and the color filter array. (<b>a</b>) Illustrates the structure of DoFP polarimeters; (<b>b</b>) presents the spatial layout of the pixeled polarizer array and the color filter array.</p>
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<p>The framework of the residual interpolation methods for DoFP polarimeters demosaicing. Guided Filter represents RI or MLRI.</p>
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<p>The PSNR of the guide image generated by the 10 up-sampling filters. The abscissa represents the image number in the dataset.</p>
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<p>The variation in the PSNR of the high-resolution finial output <math display="inline"><semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mn>45</mn> <mo>°</mo> </mrow> <mrow> <mi>H</mi> <mi>R</mi> </mrow> </msubsup> </mrow> </semantics></math> and the DoLP image with the PSNR of the guide image. The results of 0°, 90°, and 135° are similar to that of 45°, so they are not repeatedly exhibited for conciseness. (<b>a</b>,<b>b</b>) represents the variation in the PSNR of the high-resolution finial output <math display="inline"><semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mn>45</mn> <mo>°</mo> </mrow> <mrow> <mi>H</mi> <mi>R</mi> </mrow> </msubsup> </mrow> </semantics></math> and the DoLP image calculated by RI with the PSNR of the guide image, respectively. (<b>c</b>,<b>d</b>) represents the variation in the PSNR of the high-resolution finial output <math display="inline"><semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mn>45</mn> <mo>°</mo> </mrow> <mrow> <mi>H</mi> <mi>R</mi> </mrow> </msubsup> </mrow> </semantics></math> and the DoLP image calculated by MLRI with the PSNR of the guide image, respectively.</p>
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<p>The guide images with different sampling rates.</p>
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<p>The PSNR of the high-resolution finial output <math display="inline"><semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mn>45</mn> <mo>°</mo> </mrow> <mrow> <mi>H</mi> <mi>R</mi> </mrow> </msubsup> </mrow> </semantics></math> and the DoLP image calculated by three guide images with different sampling rates. The results of 0°, 90°, and 135° are similar to that of 45°, so they are not repeatedly exhibited for conciseness. (<b>a</b>,<b>b</b>) illustrate the PSNR of <math display="inline"><semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mn>45</mn> <mo>°</mo> </mrow> <mrow> <mi>H</mi> <mi>R</mi> </mrow> </msubsup> </mrow> </semantics></math> and the DoLP calculated by RI, respectively. (<b>c</b>,<b>d</b>) present the PSNR of <math display="inline"><semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mn>45</mn> <mo>°</mo> </mrow> <mrow> <mi>H</mi> <mi>R</mi> </mrow> </msubsup> </mrow> </semantics></math> and the DoLP calculated by MLRI, respectively.</p>
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<p>The filter windows with different directions in the guided filter.</p>
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<p>The overall pipeline of the proposed PAIPRI. Horizontal, Vertical, Diagonal Adaptive Iterative Filters represent pixel-by-pixel adaptive iterative processes based on residual interpolation in horizontal, vertical, and two diagonal directions, respectively. Weighted average combiner represents fusion on the interpolation images with RI and MLRI in the horizontal, vertical and two diagonal directions.</p>
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<p>The overall pipeline of the pixel-by-pixel adaptive iterative processes based on residual interpolation in horizontal direction. Primary branch represents the branch up-sampling <span class="html-italic">I</span><sub>0°</sub>, whose final output interpolation results were <math display="inline"><semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mn>0</mn> <mo>°</mo> <mo>,</mo> <mi>R</mi> <mi>I</mi> </mrow> <mi>H</mi> </msubsup> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mn>0</mn> <mo>°</mo> <mo>,</mo> <mi>M</mi> <mi>L</mi> <mi>R</mi> <mi>I</mi> </mrow> <mi>H</mi> </msubsup> </mrow> </semantics></math>. Auxiliary branch, the branch up-sampling the guide image <span class="html-italic">I</span><sub>45°</sub>, whose purpose is updating the guide image of the primary branch and increasing the PSNR of the guide image to further increase the PSNR of <math display="inline"><semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mn>0</mn> <mo>°</mo> <mo>,</mo> <mi>R</mi> <mi>I</mi> </mrow> <mi>H</mi> </msubsup> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msubsup> <mi>I</mi> <mrow> <mn>0</mn> <mo>°</mo> <mo>,</mo> <mi>M</mi> <mi>L</mi> <mi>R</mi> <mi>I</mi> </mrow> <mi>H</mi> </msubsup> </mrow> </semantics></math>. HLI represents the horizontal linear interpolation. GF represents RI or MLRI. Adaptive pixel updater represents the process of adaptively updating the iterative results, pixel by pixel.</p>
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<p>The reconstructed results of the image numbered 4 in the tested dataset, generated by the eight demosaicing methods for DoFP polarimeters [<a href="#B35-sensors-22-01529" class="html-bibr">35</a>,<a href="#B39-sensors-22-01529" class="html-bibr">39</a>,<a href="#B41-sensors-22-01529" class="html-bibr">41</a>,<a href="#B43-sensors-22-01529" class="html-bibr">43</a>,<a href="#B44-sensors-22-01529" class="html-bibr">44</a>]. The target is a knife composed of a metal body and wooden handle. The background is a rough wall and desktop. To more clearly illustrate the visual differences in the reconstructed results of the seven comparison methods, we zoomed in on a local area marked by a red box with the size of 30 × 40. (<b>a</b>) is the <span class="html-italic">I</span><sub>0°</sub> image. (<b>b</b>) is the DoLP image. There are serious sawtooth effects at the single arc-shaped edges reconstructed by Bilinear, BS, Gradient [<a href="#B35-sensors-22-01529" class="html-bibr">35</a>], PRI [<a href="#B41-sensors-22-01529" class="html-bibr">41</a>] and EARI [<a href="#B44-sensors-22-01529" class="html-bibr">44</a>]. The similar results of PRI [<a href="#B41-sensors-22-01529" class="html-bibr">41</a>] and bilinear methods, which are also illustrated in <a href="#sensors-22-01529-t001" class="html-table">Table 1</a>, <a href="#sensors-22-01529-t002" class="html-table">Table 2</a> and <a href="#sensors-22-01529-t003" class="html-table">Table 3</a>, again confirm that it is inappropriate to choose the same polarization direction for the guide image and the input image of the guided filter (as discussed in <a href="#sec3dot2-sensors-22-01529" class="html-sec">Section 3.2</a>). NP [<a href="#B39-sensors-22-01529" class="html-bibr">39</a>], MLPRI [<a href="#B43-sensors-22-01529" class="html-bibr">43</a>] and the proposed PAIPRI can reconstruct sharp edges. However, the reconstructed results of MLPRI [<a href="#B43-sensors-22-01529" class="html-bibr">43</a>] appear as excessive smoothing in the target. The reconstructed results of NP [<a href="#B39-sensors-22-01529" class="html-bibr">39</a>] generate additional error messages. Although the reconstructed results of PAIPRI retain a small amount of mosaic effect on the edges, it is visually the closest to the ground-truth images.</p>
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<p>The reconstructed results of the image numbered 8 in the tested dataset generated by the eight demosaicing methods for DoFP polarimeters [<a href="#B35-sensors-22-01529" class="html-bibr">35</a>,<a href="#B39-sensors-22-01529" class="html-bibr">39</a>,<a href="#B41-sensors-22-01529" class="html-bibr">41</a>,<a href="#B43-sensors-22-01529" class="html-bibr">43</a>,<a href="#B44-sensors-22-01529" class="html-bibr">44</a>]. The target is a standard color checker marked with a white brand logo. We zoomed in on a local area marked by a red box with the size of 90 × 120. (<b>a</b>) is the <span class="html-italic">I</span><sub>0°</sub> image. (<b>b</b>) is the DoLP image. There are serious sawtooth effects at the edges reconstructed by Bilinear and PRI [<a href="#B41-sensors-22-01529" class="html-bibr">41</a>]. The reconstructed results of BS, Gradient [<a href="#B35-sensors-22-01529" class="html-bibr">35</a>], and MLPRI [<a href="#B43-sensors-22-01529" class="html-bibr">43</a>] demonstrate blurred edges due to excessive smoothing. The reconstructed results of NP [<a href="#B39-sensors-22-01529" class="html-bibr">39</a>] generate a high number of additional error messages in flat-field regions. EARI [<a href="#B44-sensors-22-01529" class="html-bibr">44</a>] enhances the horizontal and vertical edges, but the sawtooth effect of edges in other directions is still obvious. However, the proposed PAIPRI can reconstruct clear and sharp edges. Although the reconstructed results of PAIPRI retain a small amount of mosaic effect on horizontal and vertical edges, it is visually the closest to the ground-truth images.</p>
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<p>The reconstructed results of the image numbered 1 in the tested dataset generated by the eight demosaicing methods for DoFP polarimeters [<a href="#B35-sensors-22-01529" class="html-bibr">35</a>,<a href="#B39-sensors-22-01529" class="html-bibr">39</a>,<a href="#B41-sensors-22-01529" class="html-bibr">41</a>,<a href="#B43-sensors-22-01529" class="html-bibr">43</a>,<a href="#B44-sensors-22-01529" class="html-bibr">44</a>]. The target is a fabric with abundant texture features. We zoomed in on a local area marked by a red box with the size of 100 × 100. (<b>a</b>) is the <span class="html-italic">I</span><sub>0°</sub> image. (<b>b</b>) is the DoLP image. Bilinear, BS, Gradient [<a href="#B35-sensors-22-01529" class="html-bibr">35</a>], PRI [<a href="#B41-sensors-22-01529" class="html-bibr">41</a>], MLPRI [<a href="#B43-sensors-22-01529" class="html-bibr">43</a>], and EARI [<a href="#B44-sensors-22-01529" class="html-bibr">44</a>] cannot reconstruct correct texture features in DoLP images. The reconstructed results of NP [<a href="#B39-sensors-22-01529" class="html-bibr">39</a>] demonstrate excessive smoothing. However, the reconstructed results of the proposed PAIPRI can basically reconstruct the correct texture features, and is visually the closest to the ground-truth images.</p>
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<p>The relationship between the PSNR of <span class="html-italic">I</span><sub>0°</sub> and the number of iterations.</p>
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<p>The reconstructed results generated by the eight demosaicing methods on the indoor scene images collected by a real-world DoFP polarimeter [<a href="#B35-sensors-22-01529" class="html-bibr">35</a>,<a href="#B39-sensors-22-01529" class="html-bibr">39</a>,<a href="#B41-sensors-22-01529" class="html-bibr">41</a>,<a href="#B43-sensors-22-01529" class="html-bibr">43</a>,<a href="#B44-sensors-22-01529" class="html-bibr">44</a>]. The target is a metal tank model with abundant high-frequency information. We zoomed in a local area marked by a red box with the size of 125 × 150. (<b>a</b>) is the <span class="html-italic">I</span><sub>0°</sub> image. (<b>b</b>) is the DoLP image. There are serious sawtooth effects at the arc-shaped edges reconstructed by Bilinear, BS, PRI [<a href="#B41-sensors-22-01529" class="html-bibr">41</a>], and EARI [<a href="#B44-sensors-22-01529" class="html-bibr">44</a>]. The reconstructed results of Gradient [<a href="#B35-sensors-22-01529" class="html-bibr">35</a>] demonstrate blurred edges due to excessive smoothing. The reconstructed results of NP [<a href="#B39-sensors-22-01529" class="html-bibr">39</a>] generate additional error messages. MLPRI [<a href="#B43-sensors-22-01529" class="html-bibr">43</a>] and the proposed PAIPRI can basically reconstruct clear edges, but MLPRI retains some sawtooth effects at the left edge of the wheel. Therefore, PAIPRI is visually the best compared with the other six methods.</p>
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<p>The reconstructed results generated by the eight demosaicing methods on the indoor scene images collected by a real-world DoFP polarimeter [<a href="#B35-sensors-22-01529" class="html-bibr">35</a>,<a href="#B39-sensors-22-01529" class="html-bibr">39</a>,<a href="#B41-sensors-22-01529" class="html-bibr">41</a>,<a href="#B43-sensors-22-01529" class="html-bibr">43</a>,<a href="#B44-sensors-22-01529" class="html-bibr">44</a>]. The target is a metal tank model with abundant high-frequency information. We zoomed in on a local area marked by a red box with the size of 125 × 150. (<b>a</b>) is the <span class="html-italic">I</span><sub>0°</sub> image. (<b>b</b>) is the DoLP image. There are serious sawtooth effects at the arc-shaped edges reconstructed by Bilinear, BS, PRI [<a href="#B41-sensors-22-01529" class="html-bibr">41</a>], and EARI [<a href="#B44-sensors-22-01529" class="html-bibr">44</a>]. The reconstructed results of Gradient [<a href="#B35-sensors-22-01529" class="html-bibr">35</a>] present blurred edges due to excessive smoothing. The reconstructed results of NP [<a href="#B39-sensors-22-01529" class="html-bibr">39</a>] generate additional error messages. MLPRI [<a href="#B43-sensors-22-01529" class="html-bibr">43</a>] and the proposed PAIPRI can basically reconstruct clear edges, but MLPRI [<a href="#B43-sensors-22-01529" class="html-bibr">43</a>] retains some sawtooth effects at the left edge of the wheel. Therefore, PAIPRI is visually the best compared with the other six methods.</p>
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11 pages, 4047 KiB  
Article
Simultaneous Sensitive Determination of δ13C, δ18O, and δ17O in Human Breath CO2 Based on ICL Direct Absorption Spectroscopy
by Ligang Shao, Jiaoxu Mei, Jiajin Chen, Tu Tan, Guishi Wang, Kun Liu and Xiaoming Gao
Sensors 2022, 22(4), 1527; https://doi.org/10.3390/s22041527 - 16 Feb 2022
Cited by 4 | Viewed by 2102
Abstract
Previous research revealed that isotopes 13C and 18O of exhaled CO2 have the potential link with Helicobacter pylori; however, the 17O isotope has received very little attention. We developed a sensitive spectroscopic sensor for simultaneous δ13C, [...] Read more.
Previous research revealed that isotopes 13C and 18O of exhaled CO2 have the potential link with Helicobacter pylori; however, the 17O isotope has received very little attention. We developed a sensitive spectroscopic sensor for simultaneous δ13C, δ18O, and δ17O analysis of human breath CO2 based on mid-infrared laser direct absorption spectroscopy with an interband cascade laser (ICL) at 4.33 μm. There was a gas cell with a small volume of less than 5 mL, and the pressure in the gas cell was precisely controlled with a standard deviation of 0.0035 Torr. Moreover, real-time breath sampling and batch operation were achieved in gas inlets. The theoretical drifts for δ13C, δ18O, and δ17O measurement caused by temperature were minimized to 0.017‰, 0.024‰, and 0.021‰, respectively, thanks to the precise temperature control with a standard deviation of 0.0013 °C. After absolute temperature correction, the error between the system responded δ-value and the reference is less than 0.3‰. According to Allan variance analysis, the system precisions for δ13C, δ18O, and δ17O were 0.12‰, 0.18‰, and 0.47‰, respectively, at 1 s integration time, which were close to the real-time measurement errors of six repeated exhalations. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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Figure 1

Figure 1
<p>Absorption lines of CO<sub>2</sub> isotopes at 4.33 μm based on HITRAN 2020.</p>
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<p>Schematic diagram of the developed sensor for simultaneous measurement of <sup>12</sup>C<sup>16</sup>O<sub>2</sub>, <sup>13</sup>C<sup>16</sup>O<sub>2</sub>, <sup>18</sup>O<sup>12</sup>C<sup>16</sup>O and <sup>17</sup>O<sup>12</sup>C<sup>16</sup>O in human breath.</p>
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<p>(<b>a</b>) Pressure in gas cell and (<b>b</b>) temperature in insulation case recorded continuously a 24 h period.</p>
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<p>Measured absorption signals fitted to Voigt profile and fitting residuals.</p>
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<p>(<b>a</b>) Measured <sup>13</sup>CO<sub>2</sub> absorption areas and (<b>b</b>) measured <sup>12</sup>CO<sub>2</sub> absorption areas when the developed system alternately measures ambient air and cylinder gases with <span class="html-italic">δ</span><sup>13</sup>C values of −18.5‰, −15.5‰, and −12.5‰. (<b>c</b>) Calculated <span class="html-italic">δ</span><sup>13</sup>C from absorption areas and uncalibrated temperature value. (<b>d</b>) Calculated <span class="html-italic">δ</span><sup>13</sup>C based on calibrated temperature value.</p>
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<p>The relationship between the calculated <span class="html-italic">δ</span><sup>13</sup>C values and the reference values.</p>
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<p>Measured absorption signals of CO<sub>2</sub> stable isotopes with a total concentration of 2–7%.</p>
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<p>Calculated isotopic abundances of the diluted CO<sub>2</sub> gases with a total concentration of 2–7%.</p>
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<p>Raw measurement results of <span class="html-italic">δ</span><sup>13</sup>C, <span class="html-italic">δ</span><sup>18</sup>O, and <span class="html-italic">δ</span><sup>17</sup>O (<b>upper panels</b>) and Allan deviation plot as a function of integration time (<b>lower panel</b>).</p>
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<p>Real-time measurement of the exhaled <span class="html-italic">δ</span><sup>13</sup>C, <span class="html-italic">δ</span><sup>18</sup>O, and <span class="html-italic">δ</span><sup>17</sup>O.</p>
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10 pages, 1298 KiB  
Communication
Single-Layer-Graphene-Coated and Gold-Film-Based Surface Plasmon Resonance Prism Coupler Sensor for Immunoglobulin G Detection
by Zhe-Wei Yang, Thi-Thu-Hien Pham, Chin-Chi Hsu, Chi-Hsiang Lien and Quoc-Hung Phan
Sensors 2022, 22(4), 1362; https://doi.org/10.3390/s22041362 - 10 Feb 2022
Cited by 14 | Viewed by 2798
Abstract
A graphene-based surface plasmon resonance (SPR) prism coupler sensor is proposed for the rapid detection of immunoglobulin G (IgG) antibodies. The feasibility of the proposed sensor is demonstrated by measuring the IgG concentration in phantom mouse and human serum solutions over the range [...] Read more.
A graphene-based surface plasmon resonance (SPR) prism coupler sensor is proposed for the rapid detection of immunoglobulin G (IgG) antibodies. The feasibility of the proposed sensor is demonstrated by measuring the IgG concentration in phantom mouse and human serum solutions over the range of 0–250 ng/mL. The results show that the circular dichroism and principal fast axis angle of linear birefringence increase in line with increases in IgG concentration over the considered range. Moreover, the proposed device has a resolution of 5–10 ng/mL and a response time of less than three minutes. In general, the sensor provides a promising approach for IgG detection and has significant potential for rapid infectious viral disease testing applications. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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Figure 1
<p>(<b>a</b>) Schematic illustration of graphene-based SPR sensor and (<b>b</b>) Raman spectroscopy analysis of single-layer graphene.</p>
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<p>Schematic illustration of dual-retarder Mueller polarimetry system.</p>
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<p>Measurement results obtained for (<b>a</b>) circular dichroism (<span class="html-italic">R</span>) and (<b>b</b>) principal fast axis angle (<span class="html-italic">α</span>) of mouse IgG samples with concentrations of 0–250 ng/mL.</p>
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<p>Measurement results obtained for (<b>a</b>) circular dichroism (<span class="html-italic">R</span>) and (<b>b</b>) principal fast axis angle of LB (<span class="html-italic">α</span>) of human IgG samples with concentrations of 0–250 ng/mL.</p>
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12 pages, 4490 KiB  
Article
Fluorescent “OFF–ON” Sensors for the Detection of Sn2+ Ions Based on Amine-Functionalized Rhodamine 6G
by Balamurugan Rathinam, Vajjiravel Murugesan and Bo-Tau Liu
Chemosensors 2022, 10(2), 69; https://doi.org/10.3390/chemosensors10020069 - 9 Feb 2022
Cited by 14 | Viewed by 3063
Abstract
These structurally isomeric rhodamine 6G-based amino derivatives are designed to detect Sn2+ ions. The receptors exhibit rapid fluorescent “turn-on” responses towards Sn2+. The absorption (530 nm) and fluorescent intensity (551 nm) of the receptors increase when increasing the concentration of [...] Read more.
These structurally isomeric rhodamine 6G-based amino derivatives are designed to detect Sn2+ ions. The receptors exhibit rapid fluorescent “turn-on” responses towards Sn2+. The absorption (530 nm) and fluorescent intensity (551 nm) of the receptors increase when increasing the concentration of Sn2+. The hydrazine derivative exhibits more rapid sensitivity towards Sn2+ than the ethylene diamine derivative, indicating that the presence of an alkyl chain in the diamine decreases the sensitivity of the receptors towards Sn2+. The presence of carbonyl groups and terminal amino groups strongly influences the sensitivity of the chemosensors toward Sn2+ by a spirolactam ring-opening mechanism. The receptors exhibit 1:1 complexation with Sn2+ as evidenced by Job plot, and the corresponding limit of detection was found to be 1.62 × 10−7 M. The fluorescence images of the receptors and their complexes reveal their potential applications for imaging of Sn2+ in real/online samples. Full article
(This article belongs to the Topic Advances in Optical Sensors)
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Figure 1
<p>Changes in the emission spectra of (<b>a</b>) Rh-Hyd and (<b>b</b>) Rh-ED (10<sup>−6</sup> M) at pH = 6.9 upon titration with various Sn<sup>2+</sup> equivalents (0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 40, 50).</p>
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<p>Time-dependent PL spectra of Rh-Hyd (<b>a</b>) and Rh-ED (<b>b</b>) with 10 equivalents of Sn<sup>2+</sup> in C<sub>2</sub>H<sub>5</sub>OH:H<sub>2</sub>O (8:2, <span class="html-italic">v</span>/<span class="html-italic">v</span>).</p>
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<p>Fluorescent emissions (<b>a</b>), UV-Vis absorbances (<b>b</b>), and UV-irradiated images (<b>c</b>) of Rh-Hyd (10<sup>−7</sup> M) upon addition of various metal ions.</p>
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<p>Fluorescent intensity of Rh-Hyd at 551 nm in single metal ion solutions (black bar) and mixtures of Sn<sup>2+</sup> and other metal ions (red bar).</p>
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<p>Job plot for Rh-Hyd-Sn<sup>2+</sup> complexes.</p>
Full article ">Figure 6
<p>UV-Vis absorption spectra of Rh-Hyd in different pH values.</p>
Full article ">Figure 7
<p>FTIR spectra of the Rh-Hyd, Rh-ED, and their corresponding complexes with metal (M = Sn<sup>2+</sup> complexes).</p>
Full article ">Figure 8
<p>Schematic representation of the possible mechanism for the fluorescent changes of Rh-Hyd with Sn<sup>2+</sup> addition and reversible binding in the presence of S<sup>2−</sup>.</p>
Full article ">Figure 9
<p>Variations on fluorescence of [Rh-Hyd-Sn<sup>2+</sup>] by the addition of S<sup>2−</sup>.</p>
Full article ">Scheme 1
<p>Synthesis of receptors.</p>
Full article ">Scheme 2
<p>SnCl<sub>2</sub> catalyzed reduction of nitro to amine as an illustration to show the efficiency of Rh-Hyd on the determination of residual tin content.</p>
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