Crystal Sensor Research Articles

Mathematical model for highly sensitive photonic crystal fiber sensor based on hyperbolic black holes

In this paper, the photonic crystal fiber sensor based on the geometry of hyperbolic black holes is proposed. As the hyperbolic black hole concentrates the electromagnetic radiation in its powerful gravitational field, the designed sensor has resulted in the concentration of the most electromagnetic field in the core of fiber. The extraordinary sensitivity of the sensor is due to the topology and exact geometry, which originates from the idea of the black hole. All the parameters related to the geometry of the structure are optimized by the Nelder-Mead algorithm, also, a unique three variable equation for the behavior of the structure is provided, which allows obtaining the possible errors due to the construction based on the geometry of the structure. In addition, the calculated equation leads to saving the simulation time. The proposed sensor has an amplitude sensitivity of 4650 (RIU-1) and wavelength sensitivity of 7000 (nm/RIU) and covers a wide range of refractive indices (1.31–1.42) in the bio and chemical range. Because of the amazing options that represent the functionality of the sensor, its construction is highly recommended.

Detection of CO2, H2S, NH3, and gas mixtures using a quartz crystal microbalance sensor array with five sensitive materials

The large-scale development of chicken farms has inevitably led to an increase in the emission of harmful gases, which has prompted rapid research development on the detection of harmful gases, such as quartz crystal microbalance (QCM) sensors. In this research, a QCM sensor array modified with ethyl cellulose (EC), polyethyleneimine (PEI), polypyrrole (PPy), tetramethylammonium fluoride tetrahydrate (TMAF), and Nitrogen-doped tungsten carbide supported on carbon nanosheets (WC@NC) was established to detect gas mixtures. By analyzing the relationship between the fundamental frequency shift and the number of sensitive material layers for the QCM sensor, the optimal number of layers was determined. The QCM sensor array consisted of a blank QCM sensor, an 8-layer EC sensor, a 4-layer PEI sensor, a 3-layer PPy sensor, an 8-layer TMAF sensor, and an 8-layer WC@NC sensor. The results showed that the PEI sensor exhibited maximum frequency shifts when detecting gases, while TMAF and WC@NC films had the highest contribution to NH3 detection. TMAF, PEI, and WC@NC played significant roles in the binary classification of exceeding the standard detection of NH3. Additionally, WC@NC and EC sensors played an important role in detecting H2S and CO2, respectively. The QCM sensor array could accurately classify the excessive state of CO2. Overall, the QCM sensor array demonstrated a correct recognition rate of 87.5 %, indicating its potential for classifying the exceedance of NH3, CO2, and H2S gases in gas mixtures. This work provides basic information for research on QCM sensor arrays in gas detection.

Designing a one-dimensional photonic crystal sensor for dimethyl methylphosphonate detection leveraging a hydrogen-bonding-based acidic strategy

Chemical warfare agents (CWAs) are extremely toxic chemicals, necessitating rapid, easy-to-use, sensitive and selective sensors for detection. Dimethyl methylphosphonate (DMMP) serves as a simulant of nerve agents and is commonly used to evaluate the efficacy of sensors in detecting these hazardous compounds. In this context, this paper proposes a one-dimensional (1D) photonic crystal (PC) gas sensor functionalised with UIO-66-COOH, leveraging a hydrogen-bonding-based acidic strategy, for rapid and sensitive DMMP detection. To optimise DMMP uptake, the organic ligand, UIO-66, is functionalised by grafting additional carboxyl groups to facilitate hydrogen-bonding interactions with the PO groups of organophosphorus gases such as DMMP. Subsequently, attenuated total reflection surface-enhanced infrared absorption spectroscopy is performed to quantitatively monitor the impact of strong interactions between the PC bonds and PO bonds of DMMP and the adsorption sites of metal–organic frameworks (MOFs) during adsorption. The results reveal an increase in the number of hydrogen-bonding sites available for DMMP adsorption, thus promoting hydrogen-bonding interactions. Furthermore, density functional theory calculations are employed to analyse the presence and strength of hydrogen bonds between the MOFs and DMMP. The results reveal that the chemisorption energy of UIO-66-COOH exceeds those of its variants, corroborating the findings of sensing experiments. Overall, the developed 1D PC gas sensor comprising UIO-66-COOH/TiO2 demonstrates excellent stability and reproducibility, with a limit of detection of 0.3 ppm. This sensor also demonstrates enhanced selectivity towards organophosphorus gases compared to volatile organic compounds.

A systematic study on the crystal facets-dependent TEA sensing properties of designed anatase {001 and 101} and rutile {110} facets TiO2

Triethylamine (TEA), a toxic and explosive volatile organic compound (VOC) gas, is hazardous to human health and the environment. Therefore, it is crucial to develop crystal-faceted TEA gas sensors with improved sensitivity and rapid detection capabilities. In this study, TiO2 nanocrystal sensors with different crystal facets of anatase {101} and {001} and rutile {110} were synthesized using the hydrothermal method. The nanomaterials underwent characterization through XRD, SEM, TEM, XPS, and BET analysis. The results revealed that the materials exhibited bipyramid anatase {101} facet, nanorod anatase {001} facet, and rutile {110} facet. The sensors demonstrated superior gas sensing performance in the following order: {101} > {110} > {001} facets to 100 ppm TEA gas at 240 °C. The sensors also exhibited short response and recovery times, low detection limits, excellent stability, repeatability, and selectivity. The enhanced sensing properties of {101} faceted TiO2 can be ascribed to the bipyramid structure and crystal facets with higher adsorbed oxygen peak specific area, which provide numerous active sites and improved extra oxygen-active site species. This study offers valuable insight into the design mechanism to enhance the TEA response of {101} faceted TiO2 and further contributes to our understanding of the sensitivity of crystal faceted sensors.

Terahertz photonic crystal fiber-based edible oil sensor: Performance evaluation and identification

This model introduced an innovative hollow-core optical waveguide with an octagonal core, specifically designed for rapid detection of various food oil contaminations is founded on the principles of Photonic Crystal Fiber (PCF). By analyzing the refractive index (RI) variations between pure and contaminated oil, we evaluate other essential optical parameters. The characteristics inherent to the suggested food oil sensor are examined using COMSOL Multiphysics v6.1, employing the Finite Element Method (FEM). Highly precise mesh components are included to provide optimal simulation accuracy. The outcomes from the suggested sensor model demonstrate exceptionally strong relative sensitivity of 98.52 % for castor oil, 98.46 % for sunflower oil, 98.41 % for mustard oil, 98.32 % for olive oil, and 98.03 % for coconut oil, all measured at 2 THz. Additionally, the simulation shows a very low confinement loss of 2.37 × 10−12 cm-1, a numerical aperture of 0.242, effective area of 1.1459 × 10–7 m², and effective material loss of 0.0038 cm-1 for castor oil under optimal structural circumstances. The straightforward design of the PCF in the sensor indicates that it can be implemented with ease, given these standard performance indicators. Therefore, it is anticipated that this sensor will open improved avenues for detection and identification of several distinct food oil contaminations. It can be produced using standard fabrication processes.

Liquid crystal gel-based acetone sensor using correlated laser speckles

Acetone, a common volatile organic compound (VOC), poses health risks even at low concentrations. Current acetone sensors are costly and require specialized equipment and expertise. This work develops a novel vapor sensor for determining acetone vapor concentration using the speckle patterns generated by liquid crystal gels (LCGs). The vapor sensor comprises a LCG film prepared by the phase separation of a mixture containing polystyrene microspheres and liquid crystals (LCs). The orientation of the LC molecules changes when the LCG film is exposed to an acetone vapor environment, altering the equivalent refractive indices of the LC domains. This leads to a change in the scattering state of the LCG film under laser illumination, forming different speckle patterns. The concentration of acetone vapor is determined by calculating the correlation coefficient of the speckle images, where the sensitivity and limit of detection of the sensor are 4×10-4 ppm-1 and 754.05 ppm, respectively. The developed correlated laser speckle-based optical system is simpler, less expensive, and more stable than traditional LC film vapor sensors. This acetone gas sensor has potential applications in industrial and indoor air quality testing.

Investigation of an annular photonic crystal sensor for real-time monitoring of calcium carbonate scales in water distribution systems

This research exhibits a new configuration of photonic crystals known as annular photonic crystals (APCs) for real-time detection of calcium carbonate (CaCO3) scale in the water pipeline. The proposed sensor features a circular arrangement of porous silicon materials with varying levels of porosity. A central defect layer is incorporated into the design to capture the target analyte, allowing it to detect changes in the refractive index caused by scale formation. To analyze the reflectance spectrum of this structure, a modified transfer matrix method is utilized. An extensive optimization process is conducted based on the characteristics of the defect mode, focusing on various geometric parameters, including layer thickness, porosity levels, core circle radius, and structural periodicity, to achieve optimal sensor performance. The simulation outcomes revealed that at the optimized structure parameters, the sensor offers a remarkable QF, sensitivity, and FoM of 1215, 176.85 nm/RIU, and 350.5 1/RIU, respectively. Moreover, the proposed structure is simple, cost-effective, and compact, which makes it an ideal candidate for the detection of calcium carbonate scales formed in pipes and devices in water supply networks.

Enhanced Sensing of Diseased Blood Samples through One-Dimensional MgO-SiO2 Photonic Crystal Sensor

In this investigation, we present a tailored one-dimensional photonic crystal sensor (1D PCS), magnesium oxide (MgO) and silicon dioxide (SiO2) layers designed for the specific detection of diseased blood samples components, including plasma, platelets, red blood cells, and uric acid concentrations. The sensor structure is architecturally optimized for 6, 8,10,12,14, and 20 periods, encapsulating a central defect cavity that facilitates the interaction with the blood samples. Upon introducing the blood samples into this cavity, the transmittance spectrum is meticulously analyzed using the transfer matrix method to observe the variations in the defect mode’s wavelength. The study is conducted over a range of incident waves from wavelength 450 to 750 μm, enhancing the understanding of the sensor’s effect on the detection mechanism. In this context, our sensor demonstrates a remarkable sensitivity of approximately 815 nm per refractive index unit (RIU-1). It achieves a detection limit of 10–5, showcasing an exceptional ability to detect low concentrations of the infected blood components.Moreover, Q Factor of 3795 and FOM of 3369.18 indicate the sensor’s high precision in differentiating between healthy and infected blood samples.These findings underscore the potential of the proposed MgO-SiO2-based 1D PhC sensor in serving as a high-fidelity tool for biosensing application.

Investigating the impact of shear and bulk viscosity on the damping of confined acoustic modes in phononic crystal sensors

Phononic crystal (PnC) sensors are recognized for their capability to control acoustic wave propagation through periodic structures, presenting considerable potential across various applications. Despite advancements, the effects of fluid viscosity on PnC performance remain intricate and inadequately understood. This study theoretically investigates the influence of shear (dynamic) and bulk viscosity on acoustic wave damping in defective one-dimensional phononic crystal (1D PnC) sensors designed for detecting liquid analytes. Acetic acid with varying viscosities is considered to fill a cavity layer intermediated by a multilayer stack of lead and epoxy. The effects of dynamic and bulk viscosity on the resonance characteristics of the defective mode were analyzed. Numerical results reveal that increased dynamic viscosity leads to substantial broadening and decreased intensity of resonance peaks, accompanied by a shift to higher frequencies due to enhanced elastic wave attenuation and damping. At low dynamic viscosity (η = 0.2 ηd), numerous resonance peaks with varying intensities are observed. However, at higher viscosities (η = 2.0 ηd to η = 10.0 ηd), only one prominent peak appears in the spectrum. The intensity of this resonant peak starts at 98% for η = 2 ηd and decreases to 58.8% as the dynamic viscosity increases to η = 10 ηd. Additionally, the combined effect of dynamic and bulk viscosity introduces further damping, causing a strong shift of the resonance peak to higher frequencies, along with an increase in the full width at half maximum (FWHM) and a decrease in the quality factor (QF). These findings emphasize the necessity of incorporating both shear and bulk viscosity in the design of PnC sensors to enhance their sensitivity and accuracy in practical applications. This theoretical framework provides critical insights for optimizing sensor performance and bridging gaps between theoretical predictions and experimental observations, especially in 1D PnCs, offering potential solutions to challenges in real-world PnC sensor applications.

Optimization of highly sensitive three-layer photonic crystal fiber sensor based on plasmonic

In this work, a photonic crystal fiber (PCF) refractive index (RI) sensor has been designed and optimized. The RIs range covered by the sensor is from 1.38 to 1.41. The proposed optical sensor has three layers of air holes with 24, 12 and 6 holes in each layer. The geometry parameters of the proposed sensor (the radius of the air holes and the thickness of the plasmonic layer) have been optimized using the Nelder-Mead algorithm and the FEM numerical with the objective of achieving the highest sensitivity. To achieve an optimized structure with minimal sensitivity to fabrication errors, the rotation angle of the hole layers has been analyzed. The results indicate that, due to the specific geometry of the proposed structure, variations in the rotation angle and displacement of the air holes have no significant impact on the outcomes. The results also indicate that the sensor’s maximum amplitude sensitivity (AS), maximum wavelength sensitivity (WS), and figure of merit (FOM) are 10000 (RIU−1), 23000 (nm/RIU) and 131 (RIU−1) respectively. The optimized design provides high sensitivity, a wide diagnostic range for the detection of the analytes’ RIs, and the advantages of a gold plasmonic layer, ensuring high stability in biological environments. This combination results in enhanced performance of the sensor for various applications particularly in biosensing and medical fields. The designed structural geometry also eliminates the effects of tolerances in manufacturing processes which makes the proposed PCF device a very efficient sensor.

High-sensitivity nanostructure-based sensor using Fano resonance for noninvasive EEG monitoring

Noninvasive electroencephalogram signal detection with high sensitivity and a high signal-to-noise ratio has attracted much attention. To achieve high-sensitivity electroencephalogram (EEG) sensing, a photonic crystal side-coupled microcavity nanoscale sensor based on Fano resonance is proposed with nano electro-optic sensing technology as the core support. This configuration comprises a nanobeam resonant cavity, a waveguide, and an electrical slab. The substantial overlap between the optical and electric fields within the resonant cavity is analyzed, and the sensor’s electric field sensing performance is assessed. Due to the optically coupled nanoscale sensing structure that is adopted in the sensor, the device has an ultrahigh voltage sensing sensitivity of up to 142.64 nm/V and a compact footprint as small as 4.29 mm2, enabling real-time sensing of EEG signals of 10 μV and below. These improvements overcome the technical challenges of low precision and large size as are associated with existing optical devices used for medical monitoring.

Compact Three-Channel Photonic Crystal Fiber Sensor Based on Surface Plasmon Resonance

Compact Three-Channel Photonic Crystal Fiber Sensor Based on Surface Plasmon Resonance

Wearable photonic crystal double network hydrogel sensor based on structural color analysis

Abstract This paper introduces a high-toughness photonic crystal (PhCs) dual-network hydrogel sensor designed for mechanical sensing, which enables quantitative analysis of structural color using the HSB color space. The hydrogel achieves a maximum tensile strain of 250% under a tensile stress of 3.5 MPa, thanks to its dual-network structure comprising a covalently cross-linked polyacrylamide (PAM) network and an ionically cross-linked sodium alginate (SA) network. At an 80% tensile strain, the PAM-SA photonic crystal hydrogel displays a blue shift in the bandgap wavelength of over 130 nm and demonstrates a sensitivity of 1.69 nm/%. The analysis of the force-induced color change in the PAM-SA photonic crystal hydrogel utilized both RGB and HSB color spaces. In the HSB color space, the hue component (H) exhibited a strong linear correlation with strain (R2>0.95), indicating the feasibility of quantitative structural color analysis using HSB. As a wearable sensor, the PAM-SA photonic crystal hydrogel precisely detects human motion via bandgap displacement (R2=0.989) and structural color change (R2=0.978). The PAM-SA PhCs hydrogel, featuring easily accessible color information and high sensitivity, has broad potential applications in wearable devices and mechanical sensors.

Ultra-short pulse: A comprehensive way of sensing pure solvents through hollow core photonic crystal fiber sensor

Chemicals like acetone, ethanol, hexane, isopropanol, and hexanol are essential components of our daily routines, serving critical functions in various industries and medical settings. Therefore, it is essential to perform thorough examinations to identify any contamination in these substances, which is crucial for preserving their high quality and confirming their appropriateness for different uses. The detection of these chemicals is done using a novel approach utilizing ultra-short pulses passed through Hollow-Core-Photonic Crystal Fiber based sensor. The fiber characteristics including the non-linear and dispersion parameters are used to sense the change in shape of the ultra-short pulse as the pulse travels through the HC-PCF. By implementing this approach, we've attained distinctive levels of compression sensitivity and power upsurge for the samples tailored to each specific input setup. A minimum compression sensitivity has been recorded as 24.5 % when the input power was 600W, resulting in an outstanding power upsurge of 719 W.

Improving the sensitivity of a plasmonic photonic crystal fiber temperature sensor by introducing an array of nanoscale gold rods

Improving the sensitivity of a plasmonic photonic crystal fiber temperature sensor by introducing an array of nanoscale gold rods

Highly sensitive colorimetric detection of ascorbic acid using molecularly imprinted photonic crystal hydrogel sensor

Molecular imprinted photonic crystal hydrogel (MICPH) sensors have gained recognition as an efficient platform for selectively detecting analyte molecules. In the present work, we report the development and implementation of a colorimetric sensor based on MIPCH for the selective detection of Ascorbic acid (AA). The fabrication process of the MIPCH sensor involves the photo-polymerization of a hydrogel precursor solution containing AA molecules, which is encapsulated in the interstitial spaces of photonic crystal (PC) opal film. Following the encapsulation, these molecules are selectively removed from the hydrogel network, forming an AA-MIPCH sensor. The sensor exhibits a vivid structural color that redshifts upon rebinding with different concentrations of AA molecules. This alteration in structural coloration serves as a straightforward and visually discernible indicator of the sensor response and enables the quantitative measurement of the target molecule. The sensor exhibits remarkable sensitivity, featuring a low limit of detection (LoD) of 0.011 µM with high selectivity, minimal response time, and promising long-term stability. In addition, the sensor demonstrates its capability to detect the AA even from the complex matrix. A CNN-based deep learning algorithm in MATLAB® was employed to quantitatively predict the concentration of the target molecule. The integration with the machine learning algorithm yields a highly efficient and accurate smart sensor system that is well-suited for real-time sensing of ascorbic acid.

The Development of a Novel Nitrate Portable Measurement System Based on a UV Paired Diode-Photodiode.

Nitrates can cause severe ecological imbalances in aquatic ecosystems, with considerable consequences for human health. Therefore, monitoring this inorganic form of nitrogen is essential for any water quality management structure. This research was conducted to develop a novel Nitrate Portable Measurement System (NPMS) to monitor nitrate concentrations in water samples. NPMS is a reagent-free ultraviolet system developed using low-cost electronic components. Its operation principle is based on the Beer-Lambert law for measuring nitrate concentrations in water samples through light absorption in the spectral range of 295-315 nm. The system is equipped with a ready-to-use ultraviolet sensor, light emission diode (LED), op-amp, microcontroller, liquid crystal display, quartz cuvette, temperature sensor, and battery. All the components are assembled in a 3D-printed enclosure box, which allows a very compact self-contained equipment with high portability, enabling field and near-real-time measurements. The proposed methodology and the developed instrument were used to analyze multiple nitrate standard solutions. The performance was evaluated in comparison to the Nicolet Evolution 300, a classical UV-Vis spectrophotometer. The results demonstrate a strong correlation between the retrieved measurements by both instruments within the investigated spectral band and for concentrations above 5 mg NO3-/L.

Ultra-high sensitivity photonic crystal fiber sensors based on dispersion turning point sensitization of surface plasmonic polariton modes for low RI liquid detection

Ultra-high sensitivity photonic crystal fiber sensors based on dispersion turning point sensitization of surface plasmonic polariton modes for low RI liquid detection

Simulation analysis of a photonic crystal fiber refractive index sensor based on a double-layer film structure and surface plasmon resonance technology

A photonic crystal fiber surface plasmon resonance sensor based on a double-layer membrane structure is designed and analyzed. In the simple sensing structure with only one air hole size, TiO2 and Au layers with specific thicknesses are sequentially coated on the optical fiber to form a double-layer structure. The sensing characteristics of the double-layer membrane structure are studied by the finite element method. Compared to the single-layer membrane structure, the double-layer membrane sensor has significant sensing properties such as a better wavelength sensitivity and a smaller full width at half maximum in the loss spectrum. In the refractive index range between 1.37 and 1.43, the maximum wavelength sensitivity and average wavelength sensitivity of the sensor are 19,900 nm/RIU and 7417 nm/RIU, respectively, and the resolution can be up to 5.03×10−6RIU. The proposed photonic crystal fiber optic sensor achieves high performance with a simpler sensing structure than previous photonic crystal fiber optic sensors, and eliminates the step of polishing, which will greatly reduce the difficulty of actual fabrication and the error due to uneven polishing. The results show that the photonic crystal fiber optic sensor with a double-layer membrane structure has excellent performance. Due to its high sensitivity and resolution, it has great potential for applications in environmental monitoring, biosensing and chemical sensing.

SPR based dual parameter wide range curling pot shaped photonic crystal fiber sensor

This article proposes a curling pot shaped photonic crystal fiber (PCF) sensor based on surface plasmon resonance (SPR), which utilizes two parallel polished surfaces in the cladding to achieve dual parameter measurements of liquid refractive index (RI) and temperature. The mode characteristics and sensing performance of the designed PCF sensor are studied using the finite element method, and the effects of changes in structural parameters such as pore radius, spacing, and gold film thickness on the resonance spectrum are analyzed. The sensing accuracy of the sensor is insensitive to the change of structural parameters, and it has the characteristics of a wide detection range, high sensitivity, and easy manufacture. When the measured RI is in the range of 1.33∼1.42, the maximum RI sensitivity is 20400 nm RIU−1, and the maximum FOM is 483.3 RIU−1. When the temperature ranges from −10 °C to 100 °C, the maximum sensitivity is 15.4 nm °C−1, and the maximum FOM is 0.43 RIU−1. The tight structure design of the sensor core close to the polishing surface and the anti-spill light design with a uniform arrangement of air holes enhance the SPR effect, which is the essential reason for achieving a wide detection range and high sensitivity.