Photonic Sensor Research Articles

A highly sensitive multi-channel SPR-PCF based biosensor with deep learning prediction approach

A very sensitive multi-channel refractive index-based biosensor with a detection range of 1.26 to 1.36 has been proposed. Titanium oxide (TiO2) was utilized as the dielectric, and gold as the plasmonic material in the sensor. The suggested sensor achieved a maximum sensitivity value of 48,000 nm/RIU and 7220 RIU-1 using the wavelength and amplitude interrogation techniques with a pitch layer variation of 5.55–5.95 μm and a metal layer variation of 30–50 nm. The suggested sensor can detect many compounds with amazing sensitivity, such as glucose, sucrose, ethanol, methanol, human intestinal mucosa, sevoflurane, and bio-chemicals. Additionally, a deep learning model that forecasts six optical properties has been proposed. The hyperparameters of the deep neural network model are tuned extensively to maximize accuracy. Our model had a Mean Squared Error of 0.006 and was significantly faster than conventional techniques. The results show that deep learning can predict optical features in photonic sensors, which can identify specific analytes or biomolecules in a sample without costly and time-consuming simulations. Photonic sensor researchers and engineers may utilize the suggested model on vast datasets and adjust it to new settings. This study may open the door to the use of deep learning-based optimization techniques to enhancebiosensors.

Measurement of high-power transient electromagnetic pulse field with integrated photonic electric-field sensor

To satisfy certain special requirements for high-power transient electromagnetic pulse (EMP) field measurements, such as high electric field intensity, broad bandwidth, fast rise time, and compact size, here is described an integrated electro-optic sensor. The frequency response in the range from 100 kHz to 12 GHz and the time-domain input/output characteristics of a sub-nanosecond EMP field with an intensity from 5 to 100 kV/m were experimentally characterized. The sensor was demonstrated to measure the time-domain waveform of the ultrawideband EMP field signals with a rise time of 0.35 ns and bandwidth of 1 GHz. In addition, the minimal detectable electric field strength was 16 mV/m/Hz1/2 in the frequency domain, and an intense sub-nanosecond electromagnetic pulse with a peak amplitude of 100 kV/m was observed in the time domain. The reported sensor is expected to be broadly used for intense EMP measurements.

Feasibility of Insect Identification Based on Spectral Fringes Produced by Clear Wings

Due to the growing awareness that insects' diversity and populations are in decline, there is an increased need for monitoring insects. Entomological lidars and photonic sensors can monitor and remotely identify flying insects based on their backscattered signal in terms of oscillations-, polarization-, and spectral content. The backscattered light from insects is predominantly oscillatory and derives from the wings. This part of the signal is also more coherent and co-polarized than the light reflected from the insect's abdomen. Clear membranes can display soap-bubble colors due to thin-film interference, a feature that can be associated with the thickness of the wing. A hyperspectral camera can capture these wing interference patterns with hundreds of spectral bands and accurately identify the wing thickness. Here we investigate whether the spectral fringes can provide complementary information to aid remote species identification. We demonstrate that we can extract wing thickness and modulation depth information from spectral fringes of 87 species of common insect pollinators in Skåne, Sweden. The modulation depth of a fringe provides information related to insect wing thickness homogeneity, wrinkledness, or anti-reflectance features. Our results show that examined species display distinct modulation and wing thickness, and therefore such features can be used to improve the specificity of species identification of photonics sensors.

A Deep Learning Regression Model for Photonic Crystal Fiber Sensor with XAI Feature Selection and Analysis.

A Deep Learning Multi-output regression model is employed to correctly model the relationships between optical design parameters of an asymmetric Twin Elliptical Core Photonic Crystal Fiber (TEC-PCF) and its sensing performances. TEC-PCF acts as a biosensor to detect the blood glucose level taking hemoglobin components into account. Since asymmetric TEC-PCF uses a dual elliptical core, four super modes have to be evaluated to analyze the sensing performance in terms of effective index difference, transmission spectrum, coupling length, and sensor sensitivity. The dataset used in this work is of the optical design parameters of the sensor and Finite Element Method (FEM) results with effective indices of four super modes obtained from the COMSOL Multiphysics by varying hemoglobin concentration to 120 g/L, 140 g/L, and 160 g/L. Gretel.ai's free open-source synthetic data library is used to augment the dataset to make the training more efficient. Explainable AI (XAI) feature analysis using Shapley Additive Explanations (SHAP) framework is used for two purposes: feature selection and to know the feature's effect on prediction. The former led to the development of an optimal model with much fewer computational demands and the latter made the model interpretable. The proposed model can predict the accurate super modes when given input specifications with wavelength ranging from 1.27-1.5 μm and for various glucose concentrations under the influence of hemoglobin much faster compared to the other numerical simulations which are computationally expensive. Computation time taken by the proposed Artificial Neural Network (ANN) model, the proposed model with XAI and FEM is also being compared.

Photonic Crystal Fiber Sensors, Literature Review, Challenges, and Some Novel Trends

Photonic Crystal Fiber Sensors, Literature Review, Challenges, and Some Novel Trends

Chameleon-inspired flexible photonic crystal lens-shaped dynamic pressure sensor based on structural color shift

Chameleon-inspired flexible photonic crystal lens-shaped dynamic pressure sensor based on structural color shift

One-dimensional photonic crystal magnetic sensor design based on Bloch surface waves with high sensitivity and high figure of merit (FOM)

A novel Bloch surface wave (BSW)-based one-dimensional photonic crystal magnetic sensor is proposed. Grating is used to realize the coupling of electromagnetic waves and BSW, and magnetic fluid is placed at the bottom of the sensor as the sensing medium. The sensing characteristics of a one-dimensional photonic crystal magnetic sensor were analyzed using the rigorous coupled wave analysis (RCWA) method. Based on the azimuthal interrogation method, the effects of different pole angles, defect layers, and structural parameters on sensitivity and figure of merit (FOM) were investigated. According to the drift of the resonance peak, the azimuthal sensitivity S = 9 °/mT, and the maximum detection sensitivity S = 14 °/mT were obtained (converted to refractive index sensitivity S = 6536 °/RIU and maximum detection sensitivity S = 9333 °/RIU). Excitingly, we found that the introduction of a defective layer can significantly improve the FOM (1925 RIU-1 to 69,444 RIU-1). The results show that the designed magnetic sensor structure has high sensitivity and a high FOM, which is an order of magnitude higher than other magnetic sensors. This work provides a guideline for the future development of one-dimensional photonic crystals in the field of weak magnetic sensing.

Epsilon-near-zero surface waves enhance infrared vibrational spectroscopy

Thin film epsilon-near-zero (ENZ) supports guided modes analogous to surface plasmon modes in the infrared, where surface plasmons are difficult to excite. Leveraging these modes can enhance the signal of surface-enhanced infrared absorption (SIERA) sensors by a factor of three, enabling the detection of minute amounts of materials. However, material losses can significantly impact sensor performance. To address this issue, we establish a condition that limits the impact of losses while still preserving the advantage of ENZ-surface waves. Our findings may pave the way for the identification and exploration of particularly suitable materials for highly efficient photonic SIERA sensors.

Characteristics of MoO2 Deposited C-Shaped Photonic Crystal Fiber Sensor with a Micro-Opening Based on Surface Plasmon Resonance

Characteristics of MoO2 Deposited C-Shaped Photonic Crystal Fiber Sensor with a Micro-Opening Based on Surface Plasmon Resonance

Determining the Nutrient Content of Hydroponically-Cultivated Microgreens with Immersible Silicon Photonic Sensors: A Preliminary Feasibility Study.

Microgreens have gained attention for their exceptional culinary characteristics and high nutritional value. The present study focused on a novel approach for investigating the easy extraction of plant samples and the utilization of immersible silicon photonic sensors to determine, on the spot, the nutrient content of microgreens and their optimum time of harvest. For the first time, it was examined how these novel sensors can capture time-shifting spectra caused by the molecules' dynamic adhesion onto the sensor surface. The experiment involved four types of microgreens (three types of basil and broccoli) grown in a do-it-yourself hydroponic installation. The sensors successfully distinguished between different plant types, showcasing their discriminative capabilities. To determine the optimum harvest time, this study compared the sensor data with results obtained through standard analytical methods. Specifically, the total phenolic content and antioxidant activity of two basil varieties were juxtaposed with the sensor data, and this study concluded that the ideal harvest time for basil microgreens was 14 days after planting. This finding highlights the potential of the immersible silicon photonic sensors for potentially replacing time-consuming analytical techniques. By concentrating on obtaining plant extracts, capturing time-shifting spectra, and assessing sensor reusability, this research paves the way for future advancements in urban farming.

A D-Shaped SPR-Based PCF Sensor with an Extremely High-Amplitude Sensitivity for Measuring the Refractive Index.

In this work, a new D-shaped photonic crystal fibre sensor structure based on surface plasmon resonance (SPR) is purposed for measurement of analyte refractive index (RI). In this design, a silica cylinder is polished into a D-shaped silica material structure with a flattened surface where two Au nanowires are coated. Some air holes are omitted to form the core mode region. With the implementation of gold nanowires and a core region for the exciting SPR effect with variate physical values, analyte RI can be measured with a wavelength coverage from 850 to 1350nm. The numerical simulation shows the maximum wavelength sensitivity of the purposed design achieves 19,600nm/RIU with an RI coverage from 1.37 to 1.42. Moreover, the sensor has a tremendous amplitude sensitivity and the maximum absolute value is about 2300RIU-1. Benefiting from these outstanding performance, the purposed structure can be given priority when it is applied in biomedical detecting and environmental assessment science.

A Concise Review of the Progress in Photonic Sensing Devices

Photonic sensing devices have become increasingly important in various fields such as agriculture, medicine, biochemical sensing, and manufacturing. They are highly sensitive and can classify minor changes in the physical and chemical properties of the ambient medium with high precision. This makes them practical in applications where accurate measurements are critical, such as medical diagnostics and environmental monitoring. In this review paper, recent advances in different types of photonic sensors are discussed, which include photonic crystal-based sensors, surface plasmon resonance-based sensors, optical fiber-based sensors, optical waveguide-based sensors, and wearable sensors. These highly fascinating sensing devices play a crucial role in countless applications and have several advantages over traditional sensors. As technology continues to advance, we can expect photonic sensors to become even more precise, versatile, and reliable.

Elliptical photonic crystal fiber sensor for multi-function detection based on surface plasmon resonance

Elliptical photonic crystal fiber sensor for multi-function detection based on surface plasmon resonance

A Dual-Core Surface Plasmon Resonance-Based Photonic Crystal Fiber Sensor for Simultaneously Measuring the Refractive Index and Temperature

In this correspondence, a new photonic crystal fiber biosensor structure on the basis of surface plasmon resonance is proposed for the measurement of the refractive index (RI) and TSM temperature simultaneously. In this design, the central and external surface of the biosensor structure are coated with thin gold film. A hole adjacent to the inner gold film is filled with temperature-sensitive material (TSM). With the implementation of internal and external gold coatings along with TSM, the biosensor achieves the measurement of the RI and temperature with two disjoint wavelength coverage. Numerical simulations and calculation results illustrate that the average wavelength sensitivity of the biosensor structure, respectively, achieves 7080 nm/RIU and 3.36 nm/°C with RI coverage from 1.36 to 1.41 and temperature coverage from 0 to 60 °C. Moreover, benefiting from realization of different wavelength regions in RI and temperature sensing, it is believed that the proposed biosensor structure for the measurement of the RI and temperature will have range applications in the fields of medical diagnostics and environmental assessments.

Spatially Resolved Protein Binding Kinetics Analysis in Microfluidic Photonic Crystal Sensors

Organ-on-a-Chip systems are emerging as an important in vitro analysis method for drug screening and medical research. For continuous biomolecular monitoring of the cell culture response, label-free detection within the microfluidic system or in the drainage tube is promising. We study photonic crystal slabs integrated with a microfluidic chip as an optical transducer for label-free biomarker detection with a non-contact readout of binding kinetics. This work analyzes the capability of same-channel reference for protein binding measurements by using a spectrometer and 1D spatially resolved data evaluation with a spatial resolution of 1.2 μm. A cross-correlation-based data-analysis procedure is implemented. First, an ethanol–water dilution series is used to obtain the limit of detection (LOD). The median of all row LODs is (2.3±0.4)×10−4 RIU with 10 s exposure time per image and (1.3±0.24)×10−4 RIU with 30 s exposure time. Next, we used a streptavidin–biotin binding process as a test system for binding kinetics. Time series of optical spectra were recorded while constantly injecting streptavidin in DPBS at concentrations of 1.6 nM, 3.3 nM, 16.6 nM and 33.3 nM into one channel half as well as the whole channel. The results show that localized binding within a microfluidic channel is achieved under laminar flow. Furthermore, binding kinetics are fading out at the microfluidic channel edge due to the velocity profile.

Sensing of Magnetic-Field Gradients with Nanodiamonds on Optical Glass-Fiber Facets.

We demonstrate a photonic sensor of the magnetic field and its gradients with remote readout. The sensor is based on optically detected magnetic resonance (ODMR) in nanodiamonds with nitrogen-vacancy color centers that are covalently attached as a thin film on one facet of an optical fiber bundle. By measuring ODMR signals from a group of individual fibers in an ∼0.5-mm-wide imaging bundle, differences of local magnetic field strengths and magnetic field gradients are determined across the plane of the bundle facet. The measured gradients are created by direct electric currents flowing in a wire placed near the nanodiamond film. The measurement enabled the determination of the net magnetic field corresponding to various current directions and their corresponding magnetic field gradients. This demonstration opens up a perspective for compact fiber-based endoscopy, with additional avenues for remote and sensitive magnetic field detection with submicrometer spatial resolution under ambient conditions.

Development of Optical Label-Free Biosensor Method in Detection of Listeria monocytogenes from Food.

The present work describes an alternative method for detecting and identifying Listeria monocytogenes in food samples by developing a nanophotonic biosensor containing bioreceptors and optical transducers. The development of photonic sensors for the detection of pathogens in the food industry involves the implementation of procedures for selecting probes against the antigens of interest and the functionalization of the sensor surfaces on which the said bioreceptors are located. As a previous step to functionalizing the biosensor, an immobilization control of these antibodies on silicon nitride surfaces was carried out to check the effectiveness of in plane immobilization. On the one hand, it was observed that a Listeria monocytogenes-specific polyclonal antibody has a greater binding capacity to the antigen at a wide range of concentrations. A Listeria monocytogenes monoclonal antibody is more specific and has a greater binding capacity only at low concentrations. An assay for evaluating selected antibodies against particular antigens of Listeria monocytogenes bacteria was designed to determine the binding specificity of each probe using the indirect ELISA detection technique. In addition, a validation method was established against the reference method for many replicates belonging to different batches of meat-detectable samples, with a medium and pre-enrichment time that allowed optimal recovery of the target microorganism. Moreover, no cross-reactivity with other nontarget bacteria was observed. Thus, this system is a simple, highly sensitive, and accurate platform for L. monocytogenes detection.

Scalable high Q-factor Fano resonance from air-mode photonic crystal nanobeam cavity

Abstract Fano resonance from photonic crystal nanobeam cavity (PCNC) is important building block for large-scale photonic integrated circuits (PICs) to enable photonic switches and sensors with superior characteristics. Nevertheless, most state-of-the-art demonstrations rely on electron beam lithography (EBL) and operate in dielectric mode. Hence, we theoretically, numerically and experimentally present the characteristics of Fano resonance from optical interference between the discrete state of air-mode PCNC and the continuum mode of side-coupled line-defect waveguide with partially transmitting element (PTE) using deep ultraviolet (DUV) lithography for the first time. Experimentally high average Q-factor of ∼1.58 × 104 is achieved for 30 measured devices, which indicates the feasibility of mass manufacture of high-Q Fano resonance from air-mode PTE-PCNC. Additionally, the thermo-optic bi-stability and thermal tuning characterizations of the proposed device are discussed. This work will contribute to building ultra-compact lab-on-chip resonance-based photonic components.

Millimeter‐Wave WISP Search with Coherent Light‐Shining‐Through‐a‐Wall Toward the STAX Project

AbstractA dark photon is one of the simplest extensions of the Standard Model of particle physics and can be a dark matter candidate. Dark photons kinetically mix with ordinary photons. The mass range from 10−4to 10−3 eV of such dark photons is underconstrained by laboratory‐based experiments and a new search is therefore motivated. In this mass range, dark photons behave like waves rather than particles and the corresponding electromagnetic waves are in the millimeter‐wave range. The technical difficulties of the millimeter waves have prevented so far dark photon experiments in this mass range. The use of coherent millimeter waves to search for dark photons in a Light‐Shining‐through‐a‐Wall (LSW) experiment is proposed. The merits and limitations of coherent wave detection are clarified and the potential of single photon sensors at microwaves is investigated. Development of millimeter‐wave technology is not only limited to dark photons. Technically, an experiment for dark photons by using electromagnetic waves resembles that for axions, another light dark matter candidate, with static magnetic fields. This paper represents an essential step toward axion LSW in the millimeter‐wave range (Sub‐THz‐AXion experiment; STAX) as a potential successor of an on‐going experiment in infrared.

High sensitivity photonic crystal fiber surface plasmon resonance sensor based on indium tin oxide

High sensitivity photonic crystal fiber surface plasmon resonance sensor based on indium tin oxide