Optical Detection Method Research Articles

Detection of topological charge for composite perfect vortex beams in atmospheric turbulence

Aiming at the problem of detecting the orbital angular momentum (OAM) states of the composite perfect vortex beams (CPVBs) under atmospheric turbulence (AT) channels, we propose and investigate a joint scheme of combing an optical detection method and the Gerchberg-Saxton (GS) algorithm. We firstly used the GS algorithm to pre-compensate the distorted CPVBs, and then the optical intensity distribution, together with the far-field diffraction patterns of the CPVBs after they passing through an elliptical aperture which shields part of the azimuth angle (EA-shielded), can tell us the topological charges (TCs) carried by each sub beam. The results show that the tailing direction of the bright stripes in the CPVBs intensity distribution denotes the sign of the higerh-order TC, counterclockwise is positive, clockwise is negative. The difference between the TCs of the two beams is indicated by the number of stripes, that is, the number of stripes is equal to the absolute values of differences between the two beams. After passing through the EA-shielded, the far-field diffraction intensity patterns is related to the magnitude and sign of the lower-order TC. If the bright stripes are distributed above, the TC is positive, otherwise, the TC is negative, and the number of dark stripes is equal to the lower-order TC-1. The results provide a new method for detecting the TC information of the CPVBs after phase distortion.

Electrochemical and Optical Sensors for Real-Time Detection of Nitrate in Water.

The health and integrity of our water sources are vital for the existence of all forms of life. However, with the growth in population and anthropogenic activities, the quality of water is being impacted globally, particularly due to a widespread problem of nitrate contamination that poses numerous health risks. To address this issue, investigations into various detection methods for the development of in situ real-time monitoring devices have attracted the attention of many researchers. Among the most prominent detection methods are chromatography, colorimetry, electrochemistry, and spectroscopy. While all these methods have their pros and cons, electrochemical and optical methods have emerged as robust and efficient techniques that offer cost-effective, accurate, sensitive, and reliable measurements. This review provides an overview of techniques that are ideal for field-deployable nitrate sensing applications, with an emphasis on electrochemical and optical detection methods. It discusses the underlying principles, recent advances, and various measurement techniques. Additionally, the review explores the current developments in real-time nitrate sensors and discusses the challenges of real-time implementation.

MOF-Based Materials for Glucose Detection

Metal–organic frameworks (MOFs), constructed by coordination between metal-containing nodes and organic linkers, are widely used in various fields due to the advantages of tunable pores, diverse functional sites, stable structure, and multi-functionality. It should be noted that MOF-based materials play a major role in glucose detection, serving as a signal transducer or functional substrate for embedding nanoparticles/enzymes. Diabetes is one of the most common and fast-growing diseases worldwide, whose main clinical manifestation is high blood sugar levels. Therefore, accurate, sensitive, and point-of-care glucose detection is necessary. This review orderly introduces general synthetic strategies of MOF-based materials (pristine MOF, nanoparticles, or enzymes-modified MOF and MOF-derived materials) and detection methods (electrochemical and optical methods) for glucose detection. Then, the review refers to the novel MOF-based glucose detection devices (flexible wearable devices and microfluidic chips), which enable non-invasive continuous glucose monitoring or low-cost microscale detection. On the basis of describing the development of glucose sensors based on MOF materials in the past five years, the review presents merits, demerits, and possible improvements of various detection methods.

Selective Molecular Recognition and Indicator Displacement Sensing of Neurotransmitters in Cellular Environments.

Flexible, water-soluble hosts are capable of selective molecular recognition in cellular environments and can detect neurotransmitters such as choline in cells. Both cationic and anionic water-soluble self-folded deep cavitands can recognize suitable styrylpyridinium dyes in cellular interiors. The dyes selectively accumulate in nucleotide-rich regions of the cell nucleus and cytoplasm. The hosts bind the dyes and promote their relocation to the outer cell membrane: the lipophilic cavitands predominantly reside in membrane environments but are still capable of binding suitable targets in other cellular organelles. Incubating the cells with structurally similar biomarkers such as choline, cholamine, betaine, or butyrylcholine illustrates the selective recognition. Choline and butyrylcholine can be bound by the hosts, but minimal binding is seen with betaine or cholamine. Varying the dye allows control of the optical detection method, and both "turn-on" sensing and "turn-off" sensing are possible.

Simultaneous visualization of density and pressure in hydrogen leakage based on self-imaging via dual-channel interference

Risk assessment of hydrogen energy technologies is a necessary condition for the arrival of a hydrogen energy economy society. Currently, most methods for detecting hydrogen leaks use a single concentration or pressure sensor. Structural visualization and parametric diagnosis of complex flow fields cannot be solved simultaneously by a single detection method. The main objective of this work is to propose an advanced optical detection method to simultaneously monitor the outlet pressure and density field distribution during hydrogen leakage. For the detection of the density field distribution, we use double propagation of the laser beam in the hydrogen jet to improve the phase sensitivity and relay imaging of the object between each pass to maintain spatial resolution. Error analysis shows that the error of our proposed method is 2.47 %, which is within the error tolerance. The sensitivity analysis shows that our detection sensitivity is twice that of the conventional Mach-Zehnder interferometer. For the detection of outlet pressure, we propose a mathematical model in which the half-length axis of the laser spot is linearly related to the outlet pressure and use the deformation of the laser beam in the hydrogen jet to detect the outlet pressure. The results show that the hydrogen jet can be regarded as a gas-phase lens when detecting the outlet pressure, and the deformation of the laser beam profile in the horizontal direction increases linearly with the increase of the jet pressure. The results of the study can provide a reference for the detection of accidental hydrogen leakage and the improvement of hydrogen safety regulations.

A New Optical Interferometric Biosensing System Enhanced with Nanoparticles for Alzheimer's Disease in Serum.

In this scientific work, we demonstrate, for the first time, a new biosensing system and procedure to measure specifically the total Tau (T-Tau) protein in serum, one of the most relevant biomarkers of Alzheimer's disease (AD). AD is a progressive brain disorder that produces neuronal and cognitive dysfunction and affects a high percentage of people worldwide. For this reason, diagnosing AD at the earliest possible stage involves improving diagnostic systems. We report on the use of interferometric bio-transducers integrated with 65 microwells forming diagnostic KITs read-out by using the Interferometric Optical Detection Method (IODM). Moreover, biofunctionalized silicon dioxide (SiO2) nanoparticles (NPs) acting as interferometric enhancers of the bio-transducers signal allow for the improvement of both the optical read-out signal and its ability to work with less-invasive biological samples such as serum instead of cerebrospinal fluid (CSF). As a result, in this paper, we describe for the first time a relevant diagnostic alternative to detect Tau protein at demanding concentrations of 10 pg/mL or even better, opening the opportunity to be used for detecting other relevant AD-related biomarkers in serum, such as β-amyloid and phosphorylated Tau (P-Tau), neurofilaments, among others that can be considered relevant for AD.

Fiber optic detection method for intrinsic defects in carbon fiber composite core overhead conductors considering bending performance

Carbon fiber composite core wire in the carbon fiber core rod bending strength is low, easy to break, and thus affects the detection effect. In this regard, it is proposed to consider the bending performance of carbon fiber composite core overhead wire intrinsic defects fiber detection method. The overhead wire is X-ray scanned, and the image is bent compensated by the filtering algorithm. The image is reconstructed using an iterative reconstruction algorithm, and the Tamura texture feature operator is used to extract the roughness feature parameters in the texture feature enhancement map of each conductor to achieve the identification of defects. In the experiments, the proposed method is verified for detection accuracy. The analysis of the experimental results shows that the proposed method has a high correct defect recognition rate and has a more excellent detection accuracy when the proposed method is used to detect the inherent defects of overhead conductors.

Dual-mode optical chemodosimeter for detecting copper ions in the environment, food, and living organisms with smartphone

Techniques for the detection and quantification of active ingredients in plants and foods are of global interest in the field of smart agriculture. The amount of copper ions (Cu2+) in the environment is closely related to water quality, food safety, and biological health. However, the drawbacks of the current copper ions detection techniques include difficult operation and inconvenient field analysis. Due to the reliable analytical parameters, dual-mode optical analysis has become increasingly interesting and popular. Therefore, in this study, a dual-mode optical copper ions detection method was constructed based on a fluorescent chemodosimeter RH-HP. The reaction-based recognition process improves its specificity for copper ion recognition and can be utilized to determine the concentration of copper ions in water samples, agricultural products, cells, and zebrafish. It is worth noting that the analysis and photo function of the smartphone is used to establish the relationship between the change of color RGB values and copper ions concentration. This work offers an economical, portable tool for the in-situ detection of copper ions, demonstrating its potential application for monitoring plant growth processes in future smart agriculture, and provides a reference for the establishment of in-situ portable detection methods for other important substances.

Investigation of Optical Properties and Activity of Wheat Stripe Rust Urediospores

Stripe rust is one of the most common diseases challenging the safe production of wheat. Rapid identification and analysis of urediospores, responsible for disease transmission, are the key to preventing and controlling stripe rust. The current spore detection is time-consuming and requires auxiliary equipment, but many optical detection methods and sensors with high efficiency, sensitivity, and detection ability have been developed and widely used. Thus, the investigation of optical parameters is the prerequisite for optical sensitive detection and is detailed in this study. Firstly, the microscopic images and surface elements of wheat stripe rust urediospores were obtained using a high-resolution electron microscope and an energy spectrum analyzer. The reflectivity and absorptivity spectra in the near-infrared band of active/inactivate urediospores were measured. Further, the optical parameters, such as reflection phase shift, complex refractive index, and dielectric constant, of the urediospores were analyzed based on electromagnetic theory and Kramers–Kronig relation. The results revealed that the urediospores have a strong tolerance to near-infrared light, and the real part of the complex refractive index n was between 1.0 and 1.4. These observations indicate that whether the spores are active or not has little effect on the real part and dielectric constant of the complex refractive index but has a significant impact on the imaginary part and extinction coefficient of the complex refractive index, and the corresponding relationship between the optical properties of urediospores and biological components was established. These findings were verified with HPLC-MS and Near-Infrared Spectroscopy Analysis Technology and lay a theoretical foundation for detecting urediospores of wheat stripe rust by using optical sensors. The study provides a reference for the analysis of optical characteristics of other biological samples.

Ratiometric optical detection of pyrophosphate based on aggregation-caused dual-signal response of gold nanoclusters.

Sensing of pyrophosphate ion (PPi) has received much attention due to the strong demand for clinical diagnostics. Herein, based on gold nanoclusters (Au NCs), a ratiometric optical detection method for PPi is developed by simultaneously detecting the dual-signals of fluorescence (FL) and second-order scattering (SOS). The PPi is detected by inhibiting the formation of aggregates of Fe3+ with Au NCs. Binding of Fe3+ to Au NCs causes aggregation of Au NCs, which leads to fluorescence quenching and scattering increasing. The presence of PPi can competitively bind Fe3+ to re-disperse the Au NCs and finally recover the fluorescence and reduce the scattering signal. The designed PPi sensor shows a high sensitivity with a linear range of 5-50 μM and a detection limit of 1.2 μM. In addition, the assay has excellent selectivity for PPi, which makes its application in real biological samples extremely valuable.

Development of a compact 406 nm diode laser-based cavity-enhanced spectrometer for high-sensitive detection of NO2 levels in exhaust gas

Nitrogen dioxide (NO2) is an important air pollutant due to its environmental impact and adverse effects on human health. It is released into the atmosphere primarily through anthropogenic activities. Here, we report on the development of a simple, compact, and cost-effective robust optical detection method exploiting cavity-enhanced absorption spectroscopy for high-sensitive and selective measurement of NO2 levels in real-time using a visible diode laser operating at 406 nm. A typical detection limit of ∼330 ppb for NO2 was achieved with an optimum acquisition time of ∼3.9 s, at optimal cavity pressure of 100 Torr. The sensor system demonstrates an effective optical path-length of 180 m in a high-finesse 50 cm long optical cavity in an interference-free spectral region and aerosol-free conditions. The spectrometer was optimized, calibrated, and demonstrated for the detection of NO2 levels in vehicular exhaust gases.

A non-invasive optical method for anaemia detection

The latest non-invasive biomedical electronic sensors are capable of providing continuous reliable information, for instance oxygenation level of blood, level of glucose etc. These biomedical sensors are in general based on the electro-chemical or spectral properties of the substances. The absorption of blood in infrared and visible range is prominently determined by haemoglobin. The coefficient of absorption for blood is different at different wavelengths. This optical absorption characteristic of the blood yields the vital information on the composition of the blood. Haemoglobin is primarily used to measure the status of anaemia, in developing countries like India and other African countries numerous people with greater health needs don’t have access to proper diagnostic facilities. Therefore, an introduction of portable, low cost and non-invasive Haemoglobin detector will give a vast opportunity for screening the population suffering with anaemia. The present article purposes a non-invasive method of haemoglobin detection comprising of an organic photovoltaic cell and three LED’s sources i.e., blue, green and red which are used with their respective radiation spectral range of 450–495 nm, 495–570 nm and 620–750 nm to illuminate an area of the skin on finger, this transmitted light after interacting with tissues is detected by an arrangement of Coumarin 30 : C60/NN′-QA/ZnPc active layer based organic solar cell. Thus, the approach provide in this article presents a simple, biocompatible and flexible means for assessing blood haemoglobin level by utilizing an multi spectral optical processing method. The method developed herein could further be integrated to wearable electronic devices.

A Synchronous and Accurate Detection Method for Gas Pipeline Leakage Position and Flow Rate Based on Double Fiber Bragg Gratings

Fast and accurate detection of pipeline leaks plays an important role in reducing economic losses and ensuring the safety of personnel. However, for the two important indicators of gas pipeline detection, how to effectively detect the leakage location and leakage rate simultaneously is a serious challenge. In this paper, we present an innovative optical fiber detection method based on double fiber Bragg gratings (FBGs) string to solve this problem. Combined with the theory of material mechanics and fluid mechanics, the binary equations are derived as the demodulation formula. In the detection, the corresponding physical quantities can be calculated by substituting the center wavelength of the two FBGs after drift. The experiments demonstrate that this sensor’s gas flow rate sensitivity in different positions can be up to 466.67 pm∙s/m. Meanwhile, at the same flow rate and different leakage positions, the sensor has sensitive symmetrical performance. The error results manifest that the velocity error is not more than 0.13 m/s, and the relative position detection error is not more than 0.167%. Overall, besides the extended measurement range and excellent linearity, our method also has the advantages of low production cost, simple structure and ease of production, which is more suitable for gas pipeline health monitoring in the future.

Qualitative and Quantitative Assessments of Apple Quality Using Vis Spectroscopy Combined with Improved Particle-Swarm-Optimized Neural Networks.

Exploring a cost-effective and high-accuracy optical detection method is of great significance in promoting fruit quality evaluation and grading sales. Apples are one of the most widely economic fruits, and a qualitative and quantitative assessment of apple quality based on soluble solid content (SSC) was investigated via visible (Vis) spectroscopy in this study. Six pretreatment methods and principal component analysis (PCA) were utilized to enhance the collected spectra. The qualitative assessment of apple SSC was performed using a back-propagation neural network (BPNN) combined with second-order derivative (SD) and Savitzky-Golay (SG) smoothing. The SD-SG-PCA-BPNN model's classification accuracy was 87.88%. To improve accuracy and convergence speed, a dynamic learning rate nonlinear decay (DLRND) strategy was coupled with the model. After that, particle swarm optimization (PSO) was employed to optimize the model. The classification accuracy was 100% for testing apples via the SD-SG-PCA-PSO-BPNN model combined with a Gaussian DLRND strategy. Then, quantitative assessments of apple SSC values were performed. The correlation coefficient (r) and root-square-mean error for prediction (RMSEP) in testing apples were 0.998 and 0.112 °Brix, surpassing a commercial fructose meter. The results demonstrate that Vis spectroscopy combined with the proposed synthetic model has significant value in qualitative and quantitative assessments of apple quality.

Creation and repair of luminescence defects in hexagonal boron nitride by irradiation and annealing for optical neutron detection

Hexagonal boron nitride (hBN) is promising for applications in neutron detection and quantum sensing. Here we created spin-dependent luminescence defects in hBN using 50 keV helium ion beam. The irradiated hBN flakes with a dose around 2 × 1014–1 × 1015/cm2 have the maximum photoluminescence (PL) intensity. The PL spectra are in the range of 700–1000 nm with a peak around 818 nm at 297 K after irradiation with a dose of less than 2 × 1014/cm2, which can be eliminated by high temperature annealing at 1097 K due to defects repair according to Raman spectra. However, the PL peaks exhibit a redshift from 818 nm to 830 nm when the irradiation dose is no less than 1 × 1015/cm2. Combining with constrained density functional theory calculations, it is found that high dose irradiation can cause local lattice swelling and further induce the redshift of PL spectra by 12 nm/0.33% strain. Furthermore, we proposal a novel optical neutron detection method by recording the intensity and position of PL signal of luminescence defects induced by neutron-10B nuclear reaction daughter particles. This work would be helpful to create luminescence defects in hBN for quantum sensing, and develop a novel neutron detector.

Research progress on minimally invasive and non-invasive blood glucose detection methods

Blood glucose monitoring has become the weakest point in the overall management of diabetes in China. Long-term monitoring of blood glucose levels in diabetic patients has become an important means of controlling the development of diabetes and its complications, so that technological innovations in blood glucose testing methods have far-reaching implications for accurate blood glucose testing. This article discusses the basic principles of minimally invasive and non-invasive blood glucose testing assays, including urine glucose assays, tear assays, methods of extravasation of tissue fluid, and optical detection methods, etc., focuses on the advantages of minimally invasive and non-invasive blood glucose testing methods and the latest relevant results, and summarizes the current problems of various testing methods and prospects for future development trends.

Optical Methods of Error Detection in Additive Manufacturing: A Literature Review

Additive Manufacturing (AM) has been a growing industry, specifically when trying to mass produce products more cheaply and efficiently. However, there are too many current setbacks for AM to replace traditional production methods. One of the major problems with 3D printing is the high error rate compared to other forms of production. These high error rates lead to wasted material and valuable time. Furthermore, even when parts do not result in total failure, the outcome can often be less than desirable, with minor misprints or porosity causing weaknesses in the product. To help mitigate error and better understand the quality of a given print, the field of AM monitoring in research has been ever-growing. This paper looks through the literature on two AM processes: fused deposition modeling (FDM) and laser bed powder fusion (LBPF) printers, to see the current process monitoring architecture. The review focuses on the optical monitoring of 3D printing and separates the studies by type of camera. This review then summarizes specific trends in literature, points out the current limitations of the field of research, and finally suggests architecture and research focuses that will help forward the process monitoring field.

Simple Method for Optical Detection and Characterization of Surface Agents on Conjugated Gold Nanoparticles.

In this article, we propose a simple method to calculate electrical permittivity and refractive index of surface agents of gold nanoparticles (Au NPs), in which it is possible to find the refractive index of surface agents shell by using the absorption peak of the gold nano-colloid. One of the usual tests for detection of surface agents is colorimetric methods based on the change of color of Au NPs. The color change is mainly due to the shift of localized surface plasmon resonance which is related to electrical interactions of surface agents. Although there are many mathematical models for simulating the absorption spectrum and calculating the plasmonic peak, using them is not simple and possible for everyone due to the need for programming. Here, the necessary simulations have been performed for different values ​​of refractive index of surface agents and particle size, and absorption peaks have been obtained. Using numerical methods, a simple formula is obtained between the wavelength of plasmonic peak, the ratio of hydrodynamic diameter to Feret size of the particles, and the refractive index of the surface agents. This method can help researchers to obtain the refractive index and consequently the type or concentration of surface agents around Au NPs without the need for programming or complex mathematical operations. It can also open new horizons in analyzing colorimetric diagnosis of biological agents such as viral antibodies, antigens, and other biological agents.

A Novel Hybrid Optic Disc Detection and Fovea Localization Method Integrating Region-Based Convnet and Mathematical Approach

A Novel Hybrid Optic Disc Detection and Fovea Localization Method Integrating Region-Based Convnet and Mathematical Approach

The inhibitory effect and mechanism of small molecules on acetic anhydride-induced BSA acetylation and aggregation

Protein acetylation is a significant post-translational modification, and hyperacetylation results in amyloid aggregation, which is closely related to neurodegenerative diseases (Alzheimer's disease, Huntington's disease, and so on). Therefore, it is significant to inhibit the hyperacetylation of proteins and their induced aggregation. In the present study, we aimed to explore the anti-acetylation and anti-amyloid properties of five small molecules (gallic acid, menadione, resveratrol, apigenin, and quercetin) in the process of acetic anhydride-induced protein hyperacetylation and its aggregation. Optical detection methods, such as SDS-PAGE, inverted fluorescence microscopy, and endogenous fluorescence spectroscopy, were used to investigate the effects of small molecules on protein acetylation, aggregation, and structure. In addition, fluorescence quenching and molecular docking techniques were used to explore the relationship between small molecules and acetylation. The results showed that gallic acid (200 μM), menadione (100 μM), quercetin (40 μM), resveratrol (5 μM), and apigenin (20 μM) (unmodified rates were 61.12 %, 67.76 %, 65.11 %, 62.66 %, and 67.81 %, respectively) had strong inhibitory effects on acetylation, and there was no significant difference (P < 0.05). In addition, gallic acid (200 μM), menadione (100 μM), and resveratrol (5 μM) (inhibition rates of 29.89 %, 26.53 %, and 26.09 %, respectively) had more substantial inhibitory effects on protein aggregation, indicating that the five small molecules could inhibit acetic anhydride-induced hyperacetylation and protein aggregation. The underlying mechanism might be that it could inhibit hyperacetylation and resist amyloid aggregation by interacting with proteins to occupy acetylation sites. Collectively, our findings showed that gallic acid, menadione, and resveratrol could potentially prevent and treat neurodegenerative diseases, such as Alzheimer's disease, by inhibiting acetylation and acetylation-induced aggregation.