Optical Detection Research Articles

An intelligent device with double fluorescent carbon dots based on smartphone for visual and point-of-care testing of Copper(II) in water and food samples

The excessive presence of Cu2+ could be harmful to human health. Therefore, a ratiometric fluorescence sensor based on multicolor fluorescent carbon dots (CDs) was developed for Cu2+ detection. The blue and yellow carbon dots (B-CDs/Y-CDs) were synthesized by one-step hydrothermal method. After adding Cu2+, it is captured by the amino groups of B-CDs to form complexes, resulting in a strong fluorescence quenching via photoinduced electron transfer (PET). Meanwhile, the amino groups from Y-CDs also binds with Cu2+ that inhibit the internal PET thus enhancing the fluorescence of Y-CDs. The sensor has the merits in rapid, visual, and selective with a low limit of detection (LOD) at 2.29 nM. Furthermore, an intelligent device composed of portable optical detector and smartphone is constructed, which realizes the visual point-of-care testing (POCT) of Cu2+ with a LOD of 7.51 nM. The strategy provides an accessible approach for monitoring heavy metal pollution and food safety.

Retraction Note: Design of a real-time health monitoring and prediction system for table tennis players based on optical detection sensor networks

Retraction Note: Design of a real-time health monitoring and prediction system for table tennis players based on optical detection sensor networks

First Results from the Axion Dark-Matter Birefringent Cavity (ADBC) Experiment.

Axions and axionlike particles are strongly motivated dark-matter candidates that are the subject of many current ground based dark-matter searches. We present first results from the Axion Dark-Matter Birefringent Cavity (ADBC) experiment, which is an optical bow-tie cavity probing the axion-induced birefringence of electromagnetic waves. Our experiment is the first optical axion detector that is tunable and quantum noise limited, making it sensitive to a wide range of axion masses. We have iteratively probed the axion mass ranges 40.9-43.3 neV/c^{2}, 49.3-50.6 neV/c^{2}, and 54.4-56.7 neV/c^{2}, and found no dark-matter signal. On average, we constrain the axionlike particle and photon coupling at the level g_{aγγ}≤1.9×10^{-8} GeV^{-1}. We also present prospects for future axion dark-matter detection experiments using optical cavities.

Framework for UAV-based river flow velocity determination employing optical recognition

The determination of river velocity is important for hydromorphological analyses and river monitoring systems. Indirect measurements of river velocity using videos recorded by unmanned aerial vehicles (UAV) allow fast and cost-effective processing of information about the river stretch. This paper presents a method for computing flow velocity of the river surface using deep supervised model RAFT to determine the optical flow in combination with image pre-processing by convolutional operations. Moreover, the windiness coefficients and variance score were proposed to evaluate reliability of the collected data and the obtained results of optical flow detection. Various image pre-processing techniques were applied, namely the selection of the analysed area and the number of convolutional operations to select the one with the lowest variance score. This score represents the consistency of the river flow velocity during the video and can be used to filter out unreliable results. The numerical experiments were performed using the videos and directly measured velocity values of 4 shallow rivers in Lithuania collected during the field surveys. The optical velocity estimation method showed good correspondence to the directly measured values for the velocity range from 0 m/s to 0.8 m/s in the points with low variance score up to 0.192 that represents the first quartile of the variance. The optical flow method tends to underestimate the velocity up to 0.5 m/s for the quartiles with the higher variance scores. It was shown that in most cases the lowest variance score value was obtained using pre-processing techniques without convolutional operations. However, the need to analyse various pre-processing techniques arises from the different origin of the objects moving on the river surface.

Drip-Dry Strategy Assisted Blu-Ray Disc Biosensor for Fast Point of Care Testing.

Discs and numerous other consumer products have been developed for point of care testing (POCT) to replace traditional large and expensive biochemical devices in certain scenarios. Herein, we propose a drip-dry strategy (2D strategy) assisted Blu-ray disc (BD) biosensor, termed BDB, for rapid and portable POCT within 30 min with the cost of a single test < $1. The platform utilizes the covered area formed by the deposition of the substance to be measured on the activated BD surface after the evaporation of water and realizes the quantitative detection of the target through the error readout of free disc quality diagnosis software. As a proof of concept, we first demonstrated the feasibility of direct quantitative detection of substances in solution in a single system through the detection of pure proteins avoiding colorimetric reagent used in traditional optical detection. For the complex mixed systems, we then innovatively utilize the principle that soluble targets promote/inhibit the dissolution of insoluble precipitates to achieve specific detection of targets and successfully apply BDB to the indirect quantitative detection of glutathione (GSH) with LOD of 0.447 mM in the range of 2-16 mM and organophosphorus pesticides (OPs) with LOD of 2.122 × 10-7 M in the range of 1.289 × 10-7-1.289 × 10-4 M. The BDB is widely applicable, easy to operate, and less time-consuming, which is anticipated to provide an alternative method for early, on-site detection or screening.

Optical Image Sensors for Smart Analytical Chemiluminescence Biosensors.

Optical biosensors have emerged as a powerful tool in analytical biochemistry, offering high sensitivity and specificity in the detection of various biomolecules. This article explores the advancements in the integration of optical biosensors with microfluidic technologies, creating lab-on-a-chip (LOC) platforms that enable rapid, efficient, and miniaturized analysis at the point of need. These LOC platforms leverage optical phenomena such as chemiluminescence and electrochemiluminescence to achieve real-time detection and quantification of analytes, making them ideal for applications in medical diagnostics, environmental monitoring, and food safety. Various optical detectors used for detecting chemiluminescence are reviewed, including single-point detectors such as photomultiplier tubes (PMT) and avalanche photodiodes (APD), and pixelated detectors such as charge-coupled devices (CCD) and complementary metal-oxide-semiconductor (CMOS) sensors. A significant advancement discussed in this review is the integration of optical biosensors with pixelated image sensors, particularly CMOS image sensors. These sensors provide numerous advantages over traditional single-point detectors, including high-resolution imaging, spatially resolved measurements, and the ability to simultaneously detect multiple analytes. Their compact size, low power consumption, and cost-effectiveness further enhance their suitability for portable and point-of-care diagnostic devices. In the future, the integration of machine learning algorithms with these technologies promises to enhance data analysis and interpretation, driving the development of more sophisticated, efficient, and accessible diagnostic tools for diverse applications.

Optical detection and enumeration of Escherichia coli and Salmonella enterica using a low-magnification light microscope

A rapid and cost-effective method for detecting bacterial cells from surfaces is critical to food safety, clinical hygiene, and pharmacy quality. Herein, we established an optical detection method based on a gold chip coating with 3-mercaptophenylboronic acid (3-MPBA) to capture bacterial cells, which allows for the detection and quantification of bacterial cells with a standard light microscope under low-magnification (10×) objective lens. Then, integrate the developed optical detection method with swab sampling to detect bacterial cells loading on stainless-steel surfaces. Using Salmonella enterica (SE1045) and Escherichia coli (E. coli OP50) as model bacterial cells, we achieved a capture efficiency of up to 76.0 ± 2.0 % for SE1045 cells and 81.1 ± 3.3 % for E. coli OP50 cells at 103 CFU/mL upon the optimized conditions, which slightly decreased with the increasing bacterial concentrations. Our assay showed good linear relationships between the concentrations of bacterial cells with the cell counting in images in the range of 103 -107 CFU/mL for SE1045, and 103 -108 CFU/mL for E. coli OP50 cells. The limit of detection (LOD) was 103 CFU/mL for both SE1045 and E. coli OP50 cells. A further increase in sensitivity in detecting E. coli OP50 cells was achieved through a heat treatment, enabling the LOD to be reduced as low as 102 CFU/mL. Furthermore, a preliminary application succeeded in assessing bacterial contamination on stainless-steel surfaces following integration with the approximately 40 % recovery rate, suggesting prospects for evaluating the bacteria from surfaces. The entire process was completed within around 2 h, costing merely a few dollars per sample. Considering the low cost of standard light microscopes, our method holds significant potential for practical industrial applications in bacterial contamination control on surfaces, especially in low-resource settings.

Research on high precision localization of space target with multi-sensor association

In response to the challenges of acquiring spatial target position information and achieving high precision in existing methods, this paper proposes a multi-dimensional high-precision positioning method for spatial targets through multi-sensor fusion. Utilizing optical detection technology, the method extracts two-dimensional positional information of spatial targets on the observation plane. By deriving a fusion positioning formula for visible light and infrared based on the Gaussian mixture TPHD, the proposed method enhances positioning accuracy by 0.2 m compared to using visible light or infrared alone. Additionally, by integrating laser ranging for distance dimension information, precise target positioning in the world coordinate system is achieved. Outdoor experiments for spatial target positioning validate the method's effectiveness, utilizing visible light and infrared cameras along with laser ranging. Comparative analysis with a binary star angular measurement-only method demonstrates 17.9 % improvement in positioning accuracy, with the proposed method achieving 0.12 m accuracy for 5 cm spatial targets at 5 km distance.

Emergent Technologies in Human Detection for Disaster Response: A Critical Review

In the face of natural disasters, the rapid detection of trapped victims is crucial for effective search and rescue (SAR) operations. This review critically examines the emergent technologies in human detection that are pivotal in disaster response. Current methodologies for human detection encompass a variety of techniques: Radar, Artificial intelligence (AI), Drones, Robotics, Gas sensors, Acoustic, Infrared, and Optical detection. These methods are specifically designed to detect human presence in disaster scenarios by leveraging principles from electromagnetic, acoustic, AI-based algorithms, gas sensors, and optical detection. However, these technologies face challenges and limitations. They often depend on environmental conditions, encounter obstacles that affect their penetration capabilities, and have limited spatial resolution due to complex backgrounds. This paper aims to provide a comprehensive overview of the state-of-the-art in human-detection technologies, assess their impact on SAR missions, and offer insights into future advancements that could further enhance the survivability of disaster-stricken individuals.

DA-YOLOv7: A Deep Learning-Driven High-Performance Underwater Sonar Image Target Recognition Model

Affected by the complex underwater environment and the limitations of low-resolution sonar image data and small sample sizes, traditional image recognition algorithms have difficulties achieving accurate sonar image recognition. The research builds on YOLOv7 and devises an innovative fast recognition model designed explicitly for sonar images, namely the Dual Attention Mechanism YOLOv7 model (DA-YOLOv7), to tackle such challenges. New modules such as the Omni-Directional Convolution Channel Prior Convolutional Attention Efficient Layer Aggregation Network (OA-ELAN), Spatial Pyramid Pooling Channel Shuffling and Pixel-level Convolution Bilat-eral-branch Transformer (SPPCSPCBiFormer), and Ghost-Shuffle Convolution Enhanced Layer Aggregation Network-High performance (G-ELAN-H) are central to its design, which reduce the computational burden and enhance the accuracy in detecting small targets and capturing local features and crucial information. The study adopts transfer learning to deal with the lack of sonar image samples. By pre-training the large-scale Underwater Acoustic Target Detection Dataset (UATD dataset), DA-YOLOV7 obtains initial weights, fine-tuned on the smaller Smaller Common Sonar Target Detection Dataset (SCTD dataset), thereby reducing the risk of overfitting which is commonly encountered in small datasets. The experimental results on the UATD, the Underwater Optical Target Detection Intelligent Algorithm Competition 2021 Dataset (URPC), and SCTD datasets show that DA-YOLOV7 exhibits outstanding performance, with mAP@0.5 scores reaching 89.4%, 89.9%, and 99.15%, respectively. In addition, the model maintains real-time speed while having superior accuracy and recall rates compared to existing mainstream target recognition models. These findings establish the superiority of DA-YOLOV7 in sonar image analysis tasks.

Fluorescence Carbon Dots from Blood-Berries for Sensing Cr6+ Ions in Water and Application in White Light Emitting Diode.

Conventional techniques for identifying heavy metal ions in water are laborious and time-consuming. Therefore, it is necessary to create innovative sensing technologies that can detect with greater sensitivity and speed. Although there have been reports of optical-based assays utilising fluorescent nanomaterials, these assays usually rely on variations in signal strength. However, this approach has significant drawbacks when it comes to environmental monitoring. Fluorescence carbon dots (CDs) have been prepared by facile synthesis from Blood berries. A homemade heavy metal optical detector is constructed to accurately identify heavy metal ions, exclusively Cr6+ ions in a water medium. Their optical emission signature varies based on the specific chromium ions in solution, and the emission intensity also changes depending on its concentration. The quenching behaviour is attributed to the interaction between the metallic cations and the fluorescent surface states of the carbon dots. Another application is the encapsulation of CDs in PVDF polymer to form a flexible film and use it as a phosphor for LED conversion.

Enhancing chiral molecule detection: A weak measurement approach utilizing two-dimensional information

This study addresses the critical need for high purity chiral molecules in biological systems by overcoming the challenges associated with the quantitative detection of chiral molecules and their enantiomeric mixtures. We developed an innovative detection approach that leverages the two-dimensional information gleaned from natural optical rotation (NOR) and Faraday optical rotation (FOR) under magnetic fields in chiral molecules, combined with an ultrahigh-resolution weak measurement sensor. This novel weak measurement system achieves unparalleled accuracy in detecting spin angles, with a precision of 1.86 × 10−5°. Notably, our method introduces no chemical reactions or interference with the substances under test. It offers enhanced discrimination capabilities through the dual-dimensional analysis of both natural and Faraday optical rotation, alongside a simple and compact sensor design. Conclusively, our study introduces a novel, high-precision, and multi-dimensional optical detection paradigm for chiral molecules. By incorporating Faraday rotation in the presence of a magnetic field, we expand the informational dimensionality accessible to the original weak measurement sensor, facilitating the quantitative analysis of chiral molecules and their enantiomers. This breakthrough not only furnishes a novel instrument for the exploration and development of chiral pharmaceuticals but also propels the advancement of weak measurement sensing technology forward.

Integrated Light Sources Based on Micro‐Ring Resonators for Chip‐Based LiDAR

AbstractThe micro‐ring resonator (MRR) is a crucial element in integrated photonics. It allows for the realization of various optical devices, including integrated filters, modulators, micro‐ring laser cavities, detectors, optical logic switches, and nonlinear optical devices. The development of integrated photonics has enabled the integration of these devices with other components into a photonic chip to perform specific functions. For instance, widely tunable MRR‐based lasers have been integrated with optical phased arrays (OPAs), detectors, and other elements to form a fully integrated LiDAR engine. Advances in nanofabrication have facilitated the miniaturization of nanophotonic phased arrays and on‐chip lasers. MRR‐based integrated external cavity lasers (ECLs) and integrated optical frequency combs (OFCs) have significantly enhanced the scanning and detection capabilities of LiDAR recently. Additionally, their size and power consumption have been continuously reduced, rendering them suitable for chip‐scale integration. This paper systematically reviews the major advancements of MRR‐based integrated lasers for chip‐scale LiDAR.

Photoacoustic Imaging Sensors Based on Integrated Photonics: Challenges and Trends

AbstractUltrasound and photoacoustic imaging are important imaging modalities with significant applications in clinical diagnosis and biomedical research. However, current capacitive and piezoelectric ultrasound detectors face challenges related to sensitivity and bandwidth, particularly at higher frequencies. These challenges can hinder their ability to achieve high spatial resolution and deep penetration for imaging purposes. Optical ultrasound sensors offer high sensitivity and show great potential for developing ultrasound/photoacoustic imaging systems. Among all methods of optical ultrasound detection, integrated photonics, with its superior advantages in miniaturization, sensitivity, and integration capability with electronics, could be next‐generation photoacoustic/ultrasound imaging technology. This review explores the device structure designs and applications of ultrasound/photoacoustic sensing based on integrated photonics, analyzes their performance metrics as ultrasound detectors, and discusses some perspectives on future developments and trends in this field.

Retraction Note: Application of optical imaging detection based on IoT devices in sports dance data monitoring and simulation

Retraction Note: Application of optical imaging detection based on IoT devices in sports dance data monitoring and simulation

High-Sensitivity Janus Sensor Enabled by Multilayered Metastructure Based on the Photonic Spin Hall Effect and Its Potential Applications in Bio-Sensing.

The refractive index (RI) of biological tissues is a fundamental material parameter that characterizes how light interacts with tissues, making accurate measurement of RI crucial for biomedical diagnostics and environmental monitoring. A Janus sensor (JBS) is designed in this paper, and the photonic spin Hall effect (PSHE) is used to detect subtle changes in RI in biological tissues. The asymmetric arrangement of the dielectric layers breaks spatial parity symmetry, resulting in significantly different PSHE displacements during the forward and backward propagation of electromagnetic waves, thereby realizing the Janus effect. The designed JBS can detect the RI range of 1.3~1.55 RIU when electromagnetic waves are incident along the +z-axis, with a sensitivity of 96.29°/refractive index unit (RIU). In the reverse direction, blood glucose concentrations are identified by the JBS, achieving a sensitivity of 18.30°/RIU. Detecting different RI range from forward and backward scales not only overcomes the limitation that single-scale sensors can only detect a single RI range, but also provides new insights and applications for optical biological detection through high-sensitivity, label-free and non-contact detection.

Multimodal optical detection, identification and reduction of Cr(VI) with carbon dots and its PVA/polyNIPAM spheres based 2D luminescent photonic structures

Multiple emissive carbon dots (CDs) were synthesized through a one-step solvothermal acid-assisted method using citric acid and urea. Three main emission bands were observed at ∼431 nm, ∼501 nm, and ∼622 nm, corresponding to excitation wavelengths of 360 nm, 430 nm, and 550 nm, respectively. Simultaneous detection through salient discernible features of three metal ions has been achieved. Emission of CDs with Fe(III) shows reduction in intensity at 360 nm and 550 nm wavelengths and an enhancement of photoluminescence (PL) intensity at an excitation wavelength of 430 nm. Al(III) revealed turn-on PL signals, along with a redshift when excited at 360 and 430 nm, and turn-off intensity at excitation of 550 nm. Under all the excitation wavelengths, Cr(VI) exhibits PL quenching accompanied with an additional red shift. This sensor enhances the accuracy and reliability of the probe through multiple distinctive and characteristic responses for all the three ions for which the probes were selective. Apart from the optical detection at a certain wavelength, the Cr(VI) reduction to the less toxic Cr(III) through as-prepared CDs could be monitored at three different excitation wavelengths. The Fe(III) and Cr(VI) detection in solid state has also been demonstrated through 2D luminescent photonic structures formed with CDs-PVA (poly-vinyl alcohol)-polyNIPAM (poly (N-isopropylacrylamide)) composites that can possibly be used for anticounterfeiting applications.

Analyzing Emulsion Dynamics via Direct Visualization and Statistical Methodologies.

Analytical centrifugation is a powerful technique that leverages the principles of centrifugal force and optical detection to characterize emulsion droplets in a label-free and high-throughput manner. Other advantages include minimal sample preparation effort and compatibility with a wide range of emulsion formulations. However, the resulting data can be rather complex and, thus, difficult to fully understand and interpret. To tackle this, we developed two analytical methodologies that enable an easy and intuitive understanding of the data as well as an objective, quantitative analysis and validated them using six model emulsions employing different surfactants. Through their application, insights with unprecedented clarity into dynamic emulsion behavior, stability mechanisms, and emulsion-based processes can be gained, facilitating advancements in fields such as food science, pharmaceuticals, and materials engineering.

Texture-Induced Strain in a WS2 Single Layer to Monitor Spin-Valley Polarization.

Nanoscale-engineered surfaces induce regulated strain in atomic layers of 2D materials that could be useful for unprecedented photonics applications and for storing and processing quantum information. Nevertheless, these strained structures need to be investigated extensively. Here, we present texture-induced strain distribution in single-layer WS2 (1L-WS2) transferred over Si/SiO2 (285 nm) substrate. The detailed nanoscale landscapes and their optical detection are carried out through Atomic Force Microscopy, Scanning Electron Microscopy, and optical spectroscopy. Remarkable differences have been observed in the WS2 sheet localized in the confined well and at the periphery of the cylindrical geometry of the capped engineered surface. Raman spectroscopy independently maps the whole landscape of the samples, and temperature-dependent helicity-resolved photoluminescence (PL) experiments (off-resonance excitation) show that suspended areas sustain circular polarization from 150 K up to 300 K, in contrast to supported (on un-patterned area of Si/SiO2) and strained 1L-WS2. Our study highlights the impact of the dielectric environment on the optical properties of two-dimensional (2D) materials, providing valuable insights into the selection of appropriate substrates for implementing atomically thin materials in advanced optoelectronic devices.

Tunable pattern recognition of optical QPSK data using optical correlation and direct detection.

Performing pattern recognition via correlation in the optical domain has potential advantages, including: (i) high-speed operation at the line rate and (ii) tunability and scalability by operating on the optical wave properties. Such pattern recognition might be performed on quadrature-phase-shift-keying (QPSK) data transmitted over an optical network, which generally requires using coherent detection to distinguish the phase levels of the correlator output. To enable simpler detection, we combine optical correlation with optical biasing to experimentally demonstrate tunable and scalable QPSK pattern recognition using direct detection. The pattern is applied by adjusting the relative phases of the local pumps. Delayed QPSK signals, a coherent bias tone, and local pumps undergo nonlinear wave-mixing in a periodically poled lithium niobate (PPLN) waveguide to perform optical correlation and biasing. The biased correlator output is captured using direct detection, where the highest power level corresponds only to the pattern. Multiple QPSK pattern recognitions are achieved error-free over 3072 symbols using power thresholding values of (i) 0.78 at a 5-Gbaud rate and 0.73 at a 10-Gbaud rate for 2-symbol pattern recognition and (ii) 0.81 at a 5-Gbaud rate and 0.79 at a 10-Gbaud rate for 3-symbol pattern recognition.