Optical Detection Method Research Articles

Optical Methods of Methane Detection.

Methane is the most frequently analyzed gas with different concentrations ranging from single ppm or ppb to 100%. There are a wide range of applications for gas sensors including urban uses, industrial uses, rural measurements, and environment monitoring. The most important applications include the measurement of anthropogenic greenhouse gases in the atmosphere and methane leak detection. In this review, we discuss common optical methods used for detecting methane such as non-dispersive infrared (NIR) technology, direct tunable diode spectroscopy (TDLS), cavity ring-down spectroscopy (CRDS), cavity-enhanced absorption spectroscopy (CEAS), lidar techniques, and laser photoacoustic spectroscopy. We also present our own designs of laser methane analyzers for various applications (DIAL, TDLS, NIR).

Recent Progress of Molecularly Imprinted Optical Sensors

Molecularly imprinted polymers (MIPs) have been widely utilized in the field of sensing due to their specific and high affinity towards target molecules. Combining the selective preconcentration capability of MIPs and the rapid quantitation merit of optical analytical techniques, MIP optical sensors have been applied to the analysis of various kinds of samples and have received considerable attention in recent years. In this review, we overviewed the progress of MIP sensors in combination with various optical detection methods, including fluorescence, surface plasmon resonance, Raman scattering, and chemiluminescence. The construction, characterization, working principle, and application of four kinds of MIP optical sensors are covered in detail. Finally, the opportunities and challenges currently encountered by MIP optical sensors are summarized.

Colorimetric Assaying of Exosomal Metabolic Biomarkers.

Exosomes released into the extracellular matrix have been reported to contain metabolic biomarkers of various diseases. These intraluminal vesicles are typically found in blood, urine, saliva, breast milk, cerebrospinal fluid, semen, amniotic fluid, and ascites. Analysis of exosomal content with specific profiles of DNA, microRNA, proteins, and lipids can mirror their cellular origin and physiological state. Therefore, exosomal cargos may reflect the physiological processes at cellular level and can potentially be used as biomarkers. Herein, we report an optical detection method for assaying exosomal biomarkers that supersedes the state-of-the-art time consuming and laborious assays such as ELISA and NTA. The proposed assay monitors the changes in optical properties of poly(3-(4-methyl-3'-thienyloxy) propyltriethylammonium bromide) upon interacting with aptamers/peptide nucleic acids in the presence or absence of target biomarkers. As a proof of concept, this study demonstrates facile assaying of microRNA, DNA, and advanced glycation end products in exosomes isolated from human plasma with detection levels of ~1.2, 0.04, and 0.35 fM/exosome, respectively. Thus, the obtained results illustrate that the proposed methodology is applicable for rapid and facile detection of generic exosomal biomarkers for facilitating diseases diagnosis.

Refractive index inversion method for metals based on circular polarization detection of light

Among many optical detection methods, the polarization detection method of light has been proven to be capable of providing outstanding, even unique sometimes, information of targets under test, this includes detecting objects that are difficult to be distinguished by the light intensity or spectrum information alone. However, as for materials identification, the current polarization detection method which usually uses linearly polarized light can only roughly distinguish metallic materials from non-metallic materials but cannot further differentiate among types of metallic materials. Note that the phase of a linearly polarized light may change after being reflected by a metal due to its complex refractive index, and the circular polarization information of the reflected light can be used to sense the phase change property of the metal, therefore, different types of metallic materials can be identified according to their characteristic circular polarization information due to their diverse complex refractive indices. In this paper, based on the circular polarization detection of light, a complex refractive index inversion method for metals is proposed accordingly, and experimental measurements and fitting estimations are carried out for different types of metallic materials using a Bidirectional Reflectance Distribution Function (BRDF) measurement equipment. The experimental results show that the method can accurately invert the complex refractive indices of different metals and distinguish different types of metal samples. Compared to the Mueller-matrix-based measurement method, the proposed method is computationally simple, needless of measuring a large number of parameters and performing complex calculations, it only needs to invert the results of twice measurements. In addition, it also has the advantages of high sensitivity, good stability and intuitive algorithm, which are valuable for identification applications of metallic materials.

A simple gradient centrifugation method for bacteria detection in skim milk

Development of simple methods for bacteria detection is of great importance, especially in the undeveloped countries where there are limited resources for microbial testing. Herein, we present a simple gradient centrifugation-based optical detection (GCB-OD) method for bacteria testing in skim milk. Our method incorporates capturing bacteria using nanoparticles in Eppendorf tubes, followed by separation of bacteria-captured particles in the sucrose gradient within 6 min of centrifugation. Using a simple mobile phone-setup, images of sucrose-gradients are captured, and optical density of the particle-bound bacteria zones are measured with a MATLAB software, without requirement of a sophisticated optical instrument. In this approach, different nanoparticles are compared according to delta-E (ΔE) color difference value and sedimentation rate to obtain detectable narrow particle-bound bacteria zones. The spherical shaped carbon nanoparticles (CNP) with mean diameters of 119 nm, are found suitable for low concentrations of bacteria detection for having high sedimentation rates comparing to smaller sized particles and having higher ΔE than other particles as well. For CNP-captured bacteria band detection, sucrose-gradient consist of 1 ml of 60–65–70 % (w/v) and 2 ml of 75 % (w/v) sucrose was found suitable.Escherichia coli(E. coli) was used as model fecal indicator bacteria, and the correlation of optical density andE. coliconcentration showed linearity in the range of 1.5x100–1.5x104CFU/mlE. coliin skim milk. The culture plating and transmission electron micrographs were utilized to evaluate bacterial capture performance. The developed simple centrifugation-based method that allows detection of 2 CFU/ml and 3 CFU/ml E. coliin 1XPBS and skim milk, can be useful for microbial testing in resource limited areas.

Detection of Energetic Ions Based on Tapered Optical Fiber

Single-mode tapered optical fibers (TOF) are well-known for applications in sensing. In this work, we demonstrate the use of tapered optical fibers to detect charged particles (ions) irradiated at various energies, fluences, and species. In this experiment, two different ion species, namely, Ar+ and N+, have been used to irradiate tapered optical fibers at various fluences and energies. The variations in the free spectral range (FSR), period, and transmission power loss from the ion beam irradiated TOFs are picked up by the optical spectrum analyzer (OSA). We were able to identify ions with energy as low as 80 keV because of the change in the refractive index of the cladding material caused by the implanted ions. The observed changes in spectra are explained using the results of COMSOL simulations. Using Monte Carlo-based TRI3DYN ion–solid interaction simulation, the surface modification and defect formation caused by ion beams as well as the implantation profile in the TOF have been predicted. These results are further corroborated by experimental studies such as scanning electron microscopy and Raman scattering spectroscopy. Such a tapered optical fiber-based detection method will aid in the creation of portable equipment to identify charged particles in nuclear reactors and in space exploration.

Rapid on-site nucleic acid testing: On-chip sample preparation, amplification, and detection, and their integration into all-in-one systems.

As nucleic acid testing is playing a vital role in increasingly many research fields, the need for rapid on-site testing methods is also increasing. The test procedure often consists of three steps: Sample preparation, amplification, and detection. This review covers recent advances in on-chip methods for each of these three steps and explains the principles underlying related methods. The sample preparation process is further divided into cell lysis and nucleic acid purification, and methods for the integration of these two steps on a single chip are discussed. Under amplification, on-chip studies based on PCR and isothermal amplification are covered. Three isothermal amplification methods reported to have good resistance to PCR inhibitors are selected for discussion due to their potential for use in direct amplification. Chip designs and novel strategies employed to achieve rapid extraction/amplification with satisfactory efficiency are discussed. Four detection methods providing rapid responses (fluorescent, optical, and electrochemical detection methods, plus lateral flow assay) are evaluated for their potential in rapid on-site detection. In the final section, we discuss strategies to improve the speed of the entire procedure and to integrate all three steps onto a single chip; we also comment on recent advances, and on obstacles to reducing the cost of chip manufacture and achieving mass production. We conclude that future trends will focus on effective nucleic acid extraction via combined methods and direct amplification via isothermal methods.

Detection of Acetone Using Surface Plasmon Resonance

Abstract: In most industries, detection of substances remains important as applications differ from the industry such as detections of materials for research, detection of toxic substances in liquids and more. There have been numerous ways of detection but few can only acquire data quickly and in real time such as SPR sensors. Surface Plasmon Resonance is an optical detection method that uses surface plasmons and spectroscopy that can only detect a particular substance. Using this technique can be applied for quick detection of substances which can help researchers and engineers to have a more solid precautionary equipment. For this project, the experimental setup has the characteristics of an SPR sensor; however the reflected light can be quickly transferred via fiber optic to a spectrometer and computer for instant results. To further elaborate and complement experimental data, simulations that show the dip of reflectivity of a certain angle at which is called resonance angle which can be done by using Lumerical.

Recent Advance in Cortisol Immunosensing Technologies and Devices

Well known as the “stress hormone”, cortisol plays an indispensable role in life activities. In the past few decades, accurate information about the intracorporal level of cortisol has been proven to be an important and effective indicator for evaluating physical and mental states and diagnosing a series of pressure-induced diseases. Hence, various rapid and efficient cortisol sensing technologies with high sensitivity and selectivity and low detection limit have been developed. This review examines most recent works and progress in cortisol detection via immunoassay, highlighting the construction of sensitive sensor systems. We aimed to provide a comprehensive description in the aspects of general optical and electrochemical detection methods, novel immunosensing systems, and advanced portable and wearable devices. Outlooks and suggestions for the development of continuous and real-time monitoring techniques and devices were finally provided.

Rapid Identification of Infectious Pathogens at the Single-Cell Level via Combining Hyperspectral Microscopic Images and Deep Learning.

Identifying infectious pathogens quickly and accurately is significant for patients and doctors. Identifying single bacterial strains is significant in eliminating culture and speeding up diagnosis. We present an advanced optical method for the rapid detection of infectious (including common and uncommon) pathogens by combining hyperspectral microscopic imaging and deep learning. To acquire more information regarding the pathogens, we developed a hyperspectral microscopic imaging system with a wide wavelength range and fine spectral resolution. Furthermore, an end-to-end deep learning network based on feature fusion, called BI-Net, was designed to extract the species-dependent features encoded in cell-level hyperspectral images as the fingerprints for species differentiation. After being trained based on a large-scale dataset that we built to identify common pathogens, BI-Net was used to classify uncommon pathogens via transfer learning. An extensive analysis demonstrated that BI-Net was able to learn species-dependent characteristics, with the classification accuracy and Kappa coefficients being 92% and 0.92, respectively, for both common and uncommon species. Our method outperformed state-of-the-art methods by a large margin and its excellent performance demonstrates its excellent potential in clinical practice.

Influence of Dielectric Liquid Type on Partial-Discharge Inception Voltage in Oil-Wedge-Type Insulating System under AC Stress

This article describes the results of laboratory tests on an oil-wedge-type electrode system, which were supplemented by FEM (finite element method) simulations. The studies were focused on the comparison of the partial-discharge inception voltage (PDIV) in the abovementioned system when immersed in different liquid dielectrics, namely inhibited mineral oil, uninhibited mineral oil, synthetic ester, and natural ester. In addition, the electric field stress obtained from the simulations was used in each case to determine the safe level for the actual transformer insulation. The studies were performed under AC voltage. Both electrical and optical detection methods were applied in order to properly determine the discharge inception. The statistical analysis of the results obtained from the laboratory measurements was carried out using Weibull distribution. We found that both mineral oils demonstrated better properties than the ester liquids in terms of resistance against partial-discharge appearance under the conditions of the oil-wedge-type electrode model. Therefore, for all considered cases, the inception electric field stress obtained from the FEM-based simulations corresponding to the partial-discharge inception voltage was found to be significantly higher than the commonly accepted safe design level, which is in the range of 10–12 kV/mm. This proved the good electrical strength of all liquids under test.

Comparison of Milled Full-Arch Implant-Supported Frameworks Realised with a Full Digital Workflow or from Conventional Impression: A Clinical Study.

The aim of the present study was to investigate the accuracy of a new digital impression system, comparing it to the plaster impression technique in the realization of full-arch implant-supported metal frameworks. We took 11 scans (8 of the upper maxilla and 3 of the lower jaw) on a sample of nine patients previously rehabilitated with fixed full-arch screw-retained prostheses following the Columbus Bridge Protocol (CBP) with four to six implants (total: 51) since at least 4 months. Two impressions were taken for each dental arch: one analogic plaster impression using pick-up copings and an open tray technique and a second one using an intra-oral scanner. Two milled metal substructures were realised. The precision and passivity of the substructures were clinically analysed through the Sheffield test and endo-oral radiographs. Laboratory scans of the plaster casts obtained from an intra-oral scanner (IOS) and of the plaster casts obtained from traditional impression were compared with the intraoral scans following Hausdorff's method and an industrial digital method of optical detection to measure discrepancies. A Mann-Whitney test was performed in order to investigate average distances between surfaces after the superposition. The Sheffield test demonstrated an excellent passivity of the frameworks obtained through both the digital and the analogic method. In 81.81% of cases (n = 9) both substructures were found to have a perfect fit with excellent passivity, while in 18.18% (n = 2) of cases the substructures were found to have a very slight discrepancy. From the radiographic examination, no gaps between the frameworks and the implant heads or multiunit abutments were observed, with 100% accuracy. By superimposing digital files of scans according to Hausdorff's method, a statistically significant discrepancy (p = 0.006) was found between the digital scans and the digital models obtained from plaster impressions. Three-dimensional optical detection found a mean discrepancy of 0.11 mm between the analogic cast and the cast derived from the digital impression. The present study clinically demonstrates that milled implant-supported full-arch frameworks obtained through a digital scan and the herein described technique have an accuracy comparable to those obtained with traditional plaster impression.

Metal-Organic Frameworks-Based Optical Nanosensors for Analytical and Bioanalytical Applications

Metal-organic frameworks (MOFs)-based optical nanoprobes for luminescence and surface-enhanced Raman spectroscopy (SERS) applications have been receiving tremendous attention. Every element in the MOF structure, including the metal nodes, the organic linkers, and the guest molecules, can be used as a source to build single/multi-emission signals for the intended analytical purposes. For SERS applications, the MOF can not only be used directly as a SERS substrate, but can also improve the stability and reproducibility of the metal-based substrates. Additionally, the porosity and large specific surface area give MOF a sieving effect and target molecule enrichment ability, both of which are helpful for improving detection selectivity and sensitivity. This mini-review summarizes the advances of MOF-based optical detection methods, including luminescence and SERS, and also provides perspectives on future efforts.

Recent advances in point-of-care testing of COVID-19.

Advances in microfluidic device miniaturization and system integration contribute to the development of portable, handheld, and smartphone-compatible devices. These advancements in diagnostics have the potential to revolutionize the approach to detect and respond to future pandemics. Accordingly, herein, recent advances in point-of-care testing (POCT) of coronavirus disease 2019 (COVID-19) using various microdevices, including lateral flow assay strips, vertical flow assay strips, microfluidic channels, and paper-based microfluidic devices, are reviewed. However, visual determination of the diagnostic results using only microdevices leads to many false-negative results due to the limited detection sensitivities of these devices. Several POCT systems comprising microdevices integrated with portable optical readers have been developed to address this issue. Since the outbreak of COVID-19, effective POCT strategies for COVID-19 based on optical detection methods have been established. They can be categorized into fluorescence, surface-enhanced Raman scattering, surface plasmon resonance spectroscopy, and wearable sensing. We introduced next-generation pandemic sensing methods incorporating artificial intelligence that can be used to meet global health needs in the future. Additionally, we have discussed appropriate responses of various testing devices to emerging infectious diseases and prospective preventive measures for the post-pandemic era. We believe that this review will be helpful for preparing for future infectious disease outbreaks.

Progressive Learning for Unsupervised Change Detection on Aerial Images

This article focuses on unsupervised methods for optical aerial image change detection. Existing unsupervised change detection techniques are mainly categorized as patch-based methods and transfer-learning-based methods. However, the first type ignores the spatial information in the images, and the second type may introduce new errors due to knowledge extracted from additional datasets. To effectively tackle these problems, we propose an unsupervised progressive learning framework (UPLF). We first use original estimated change maps as the labeled samples and choose the reliable regions from samples to train the network. We then propose a progressive learning method to expand the reliable labeled region. Briefly, we apply a label selection filter to filter out incorrect change information from the regions to help rectify incorrect labeling in the regions. This leads to a more reliable labeled region and thus, in turn, more accurate detection results. Compared with the patch-based and transfer-learning-based unsupervised techniques, our method takes the entire map as the training sample to avoid the problem associated with using small patches; moreover, our iterative and progressive methods further enhance the change detection performance without involving external knowledge. Indeed, based on our experimental results on the real datasets, the proposed method demonstrates highly competitive performance compared with the state-of-the-art.

Self-Sufficient Feature Enhancing Networks for Video Salient Object Detection

Detecting salient objects in videos is a very challenging task. Current state-of-the-art methods are dominated by motion based deep neural networks, among which optical flow is often leveraged as motion representation. Though with robust performance, these optical flow-based video salient object detection methods face at least two problems that may hinder their generalization and application. First, computing optical flow as a pre-processing step does not support direct end-to-end learning; second, little attention has been given to the quality of visual features due to high computational cost of spatiotemporal feature encoding. In this paper we propose a novel self-sufficient feature enhancing network (SFENet) for video salient object detection, which leverages optical flow estimation as an auxiliary task while being end-to-end trainable. With a joint training scheme of both salient object detection and optical flow estimation, its multi-task architecture can be totally self-sufficient for achieving good performance without any pre-processing. Furthermore, for improving feature quality, we design four lightweight modules in spatial and temporal domains, including cross-layer fusion, multi-level warping, spatial-channel attention and boundary-aware refinement. The proposed method is evaluated through extensive experiments on five video salient object detection datasets. Experimental results show that our SFENet can be easily trained with fast convergence speed. It significantly outperforms previous methods in terms of various evaluation metrics. Moreover, with optical flow estimation and unsupervised video object segmentation as example applications, our method also yields state-of-the-art results on standard datasets.

Developing an improved optical biosensing system based on gold nanoparticles acting as interferometric enhancers in Lactoferrin detection.

We report for the first time the whole development of a biosensing system based on the Interferometric Optical Detection Method (IODM) enriched with gold nanoparticles (AuNPs), acting as interferometric enhancers for improving the performance of immunoassays. For this purpose, the Lactoferrin sandwich immunoassay model was employed. We describe in detail the entire value chain from the AuNPs production, its functionalization, and characterization with anti-Lactoferrin (anti-LF), the biosensing response of these conjugates as well as their corresponding calculation of the kinetic constants, performance comparison of the readout interferometric signals versus Scanning Electron Microscopy (SEM) and the percentage of the sensing surface covered. Finally, a Lactoferrin sandwich immunoassay was carried out and correlated with Enzyme-Linked ImmunoSorbent Assay (ELISA), and the Limit of Detection and sensitivity figures were obtained. As a result, we demonstrate how the AuNPs act as interferometric amplifiers of the IODM for improving the biosensing response, opening the possibility of being applied in multiple biological detection applications.

Optical, electrochemical, and test strip methods for sensitive and selective detection of Cyanide ion using a multifunctional π-extended azaacene-based system

A reversible multichannel chemosensor IPBTO [E)-5-(4-(1H- imidazo[4,5-b]phenazin-2-yl) benzylidene)-2-thioxothiazolidin-4-one] was fabricated as a D-π-A system and used for the detection of cyanide ion (CN–) in aqueous solutions. This chemosensor exhibited a switch-off fluorescence response at 566 nm for CN– in the presence of other tested anions. The detection limit of IPBTO toward CN– was 0.7 μM with the association constant being 2.0 × 106 M−1. The reversibility and reusability aspects of this chemosensor were investigated for five consecutive runs, and good results were obtained. In addition, IPBTO as a bioimaging agent with good cell viability was deployed for the detection of CN– in MDA-MB-231 cells. Excellent potential for sensing CN– was also realized for this chemosensor in food and environmental samples. Besides, IPBTO was self-assembled on the gold electrode surface (Au-IPBTO SAM) and used for accumulation and detection of CN– in aqueous media. This modified electrode was characterized by ATR surface analysis, and the electrochemical behavior of the electrode was studied utilizing cyclic voltammetry (CV), differential pulse voltammetry (DPV), and electrochemical impedance spectroscopy (EIS). Our results have conclusively revealed that this electrochemical sensor could be successfully used to detect CN−.

Optical Methods for Label-Free Detection of Bacteria

Pathogenic bacteria are the leading causes of food-borne and water-borne infections, and one of the most serious public threats. Traditional bacterial detection techniques, including plate culture, polymerase chain reaction, and enzyme-linked immunosorbent assay are time-consuming, while hindering precise therapy initiation. Thus, rapid detection of bacteria is of vital clinical importance in reducing the misuse of antibiotics. Among the most recently developed methods, the label-free optical approach is one of the most promising methods that is able to address this challenge due to its rapidity, simplicity, and relatively low-cost. This paper reviews optical methods such as surface-enhanced Raman scattering spectroscopy, surface plasmon resonance, and dark-field microscopic imaging techniques for the rapid detection of pathogenic bacteria in a label-free manner. The advantages and disadvantages of these label-free technologies for bacterial detection are summarized in order to promote their application for rapid bacterial detection in source-limited environments and for drug resistance assessments.

Integration of Impedimetric Sensors for In Situ Electrochemical Impedance Spectroscopy in Free-Flow Electrophoresis Applications in Lab-on-Chip Systems.

Miniaturization and integration of chemical reactions into fluidic systems in combination with product purification or buffer exchange can reduce the amount of solvents and reactants required while increasing synthesis efficiency. A critical step is the regulation of flow rates to realize optimal synthesis conditions and high purification rates, so real-time, label-free monitoring is required in methods such as free-flow electrophoresis. Optical detection methods are widely used, but they often have complex excitation and detection setups that are disadvantageous for point-of-care applications. The method we have chosen is electrochemical impedance spectroscopy for detecting charged compounds in aqueous buffers with low ionic strength. Propranolol was selected for proof of concept and was separated from the organic solvent and the precursor oxirane by free-flow electrophoresis. For this purpose, electrode structures were fabricated in microfluidic channels by photolithographic lift-off technique and optimized in terms of positioning, electrode size and distance for sensitive detection, and quantification of propranolol in the nanomolar range. It is also noteworthy that the organic solvent dimethyl sulfoxide (DMSO) could be detected and quantified by an increased impedance magnitude. Subsequently, the optimized interdigital electrode structures were integrated into the outlet channels of the electrophoretic separation chamber to monitor the various outgoing fluidic streams and provide in-line control of the fluidic flows for the purification step. In conclusion, we can provide a microfluidic chip to monitor the separation efficiency of a substance mixture during free-flow electrophoresis without the need of complex analytical techniques using electrochemical impedance spectroscopy.