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A new high-throughput optical sensor for captopril (CAP) is proposed. The sensor is based on the inhibitory effect of the analyte on the specific reaction of desferal with Fe(III) in an acidic medium. The whole analytical scheme was developed in micro-plates format combined with instrumental-free detection through an overhead book scanner. Dissolution testing was selected as an interesting application due to the generation of large amounts of samples during drug development. The method allowed the quantification of CAP up to 500 μM, with a lower limit of quantification LLOQ of 25 μM. 96 samples/standards could be processed simultaneously, obtaining a complete dissolution profile within 1 h (n = 12). Following validation, the obtained results were in accordance with the HPLC method recommended by the US Pharmacopeia. Finally, the greenness of the procedure was assessed by well-established tools such as the Green Analytical Procedure and Blue Applicability Grade indexes (77.5% score). [ABSTRACT FROM AUTHOR]

This paper presents a symmetric all-dielectric two-dimensional grating with high transmittance and high figure of merit based on cylindrical nanoarrays as a liquid sensing structure with small volume and high sensitivity. The device is optimized using the finite element method to calculate the transmissivity under TE/TM polarization. When the incident angle is 4 degrees, the transmissivity of the grating is nearly 1 with a full width at half maximum of 0.016 nm and a sensitivity of 256.2 nm/RIU. The high figure of merit is 16214.936, and the corresponding quality factor can reach 56572.438. The sensor characteristics of the incident angle on the device are analyzed, and the normalized electric field distribution indicates that the change of the incident angle has a significant modulation ability for the resonance energy distribution. The proposed sensor is independent of polarization state, easy to control and integrate, and has broad application prospects in fields such as liquid solution detection, ocean surveys, and position sensing.Article Highlights: Structural parameters can significantly change the full width at half maximum, sensitivity and FOM. Incident angle and transverse longitudinal displacement facilitate dynamic control of sensor performance. Realize the refractive index sensing of different liquid solutions. [ABSTRACT FROM AUTHOR]

Microplastics (MPs) are increasingly widespread in the environment, which raises questions about their potential effects at different biological levels. It is essential to assess the impacts on biodiversity, and it is also crucial to understand whether the presence of MPs can interfere with the biological traits of species of relevance in public health. Considering that the life-history traits of mosquitoes, such as size and the wingbeat frequency (WBF), are related to its vector competence, here, we study the effects of 106 particles L−1 (as expected concentration of MPs on the environment, using the polyethylene type) on WBF, as well as wing morphology, testing the Culicidae species found across all continents, Aedes aegypti, as an indicator. Results show that larvae survival and development were not affected by the tested concentration of MP. Geometric morphometrics showed some asymmetry in female mosquito wings, which were also smaller for individuals reared in MP suspension. As for WBF, results did not indicate any significant differences between females. Male mosquitoes, however, showed alterations in WBF and wing morphology, suggesting possible sex-specific reactions to microplastic exposure. Also, the combination of morphological parameters analyzed as covariates (wing centroid size and body weight) did not significantly affect WBF for both female and male mosquitoes. Overall, this study shows an inaugural investigation of the effects of MP on wing size and WBF on Ae. aegypti, shedding light on these parameters tested for a current pollution issue and its impact on a virus vector. [ABSTRACT FROM AUTHOR]

This study evaluated the possibility of using two complementary electronic sensors (rising plate meter (RPM) and active optical sensor (AOS)) to obtain a global indicator, pasture crude protein (CP) in kg ha−1. This parameter simultaneously integrates two essential dimensions: pasture dry matter availability (dry matter (DM) in kg ha−1) measured by RPM, and pasture quality (measured by AOS), and supports management decisions, particularly those related to the stocking rates, supplementation, or rotation of animals between grazing parks. The experimental work was carried out on a dryland biodiverse and representative pasture, and consisted of sensor measurements, followed by the collection of a total of 144 pasture samples, distributed between three dates of the pasture vegetative cycle of 2023/2024 (Autumn—December 2023; Winter—February 2024; and Spring—May 2024). These samples were subjected to laboratory reference analysis to determine DM and CP. Sensor measurements (compressed height (HRPM) in the case of RPM, and normalized difference vegetation index (NDVI) in the case of AOS) and the results of reference laboratory analysis were used to develop prediction models. The best correlations between CP (kg ha−1) and "HRPM × NDVI" were obtained in the initial and intermediate phases of the cycle (autumn: R2 = 0.86 and LCC = 0.80; and Winter; R2 = 0.74 and LCC = 0.81). In the later phase of the cycle (spring), the accuracy of the forecasting model decreased dramatically (R2 = 0.28 and LCC = 0.42), a trend that accompanies the decrease in the pasture moisture content (PMC) and CP. The results of this study show not only the importance of extending the database to other pasture types in order to enhance the process of feed supplement determination, but also the potential for the research and development of proximal and remote sensing tools to support pasture monitoring and animal production management. [ABSTRACT FROM AUTHOR]

A systematic investigation of optical, electrochemical, photophysical, and electrooptical properties of printable green color-emitting polymer (poly(9,9-dioctylfluorene-alt-bithiophene)) (F8T2) and spiro-copolymer (SPG-01T) was conducted to explore their potentiality as an emissive layer for wearable polymer light-emitting diode (PLED) applications. We compared the two photoactive polymers in terms of their spectral characteristics and color purity, as these are the most critical factors for wearable lighting sources and optical sensors. Low-cost, solution-based methods and facile architecture were applied to produce rigid and flexible light-emitting devices with high luminance efficiencies. Emission bandwidths, color coordinates, operational characteristics, and luminance were also derived to evaluate the device's stability. The tuning of emission's spectral features by layer thickness variation was realized and was correlated with the interplay between H-aggregates and J-aggregates formations for both conjugated polymers. Finally, we applied the functional green light-emitting PLED devices based on the two studied materials for the detection of Rhodamine 6G. It was determined that the optical detection of the R6G photoluminescence is heavily influenced by the emission spectrum characteristics of the PLED and changes in the thickness of the active layer. [ABSTRACT FROM AUTHOR]

Background: Disease-vector mosquito monitoring is an essential prerequisite to optimize control interventions and evidence-based risk predictions. However, conventional entomological monitoring methods are labor- and time-consuming and do not allow high temporal/spatial resolution. In 2022, a novel system coupling an optical sensor with machine learning technologies (VECTRACK) proved effective in counting and identifying Aedes albopictus and Culex pipiens adult females and males. Here, we carried out the first extensive field evaluation of the VECTRACK system to assess: (i) whether the catching capacity of a commercial BG-Mosquitaire trap (BGM) for adult mosquito equipped with VECTRACK (BGM + VECT) was affected by the sensor; (ii) the accuracy of the VECTRACK algorithm in correctly classifying the target mosquito species genus and sex; (iii) Ae. albopictus capture rate of BGM with or without VECTRACK. Methods: The same experimental design was implemented in four areas in northern (Bergamo and Padua districts), central (Rome) and southern (Procida Island, Naples) Italy. In each area, three types of traps—one BGM, one BGM + VECT and the combination of four sticky traps (STs)—were rotated each 48 h in three different sites. Each sampling scheme was replicated three times/area. Collected mosquitoes were counted and identified by both the VECTRACK algorithm and operator-mediated morphological examination. The performance of the VECTRACK system was assessed by generalized linear mixed and linear regression models. Aedes albopictus capture rates of BGMs were calculated based on the known capture rate of ST. Results: A total of 3829 mosquitoes (90.2% Ae. albopictus) were captured in 18 collection-days/trap/site. BGM and BGM + VECT showed a similar performance in collecting target mosquitoes. Results show high correlation between visual and automatic identification methods (Spearman Ae. albopictus: females = 0.97; males = 0.89; P < 0.0001) and low count errors. Moreover, the results allowed quantifying the heterogeneous effectiveness associated with different trap types in collecting Ae. albopictus and predicting estimates of its absolute density. Conclusions: Obtained results strongly support the VECTRACK system as a powerful tool for mosquito monitoring and research, and its applicability over a range of ecological conditions, accounting for its high potential for continuous monitoring with minimal human effort. [ABSTRACT FROM AUTHOR]

The Mexican bean beetle, Epilachna varivestis Mulsant (Coleoptera: Coccinellidae), is a key pest of beans, and early detection of bean damage is crucial for the timely management of E. varivestis. This study was conducted to assess the feasibility of using drones and optical sensors to quantify the damage to field beans caused by E. varivestis. A total of 14 bean plots with various levels of defoliation were surveyed aerially with drones equipped with red-blue-green (RGB), multispectral, and thermal sensors at 2 to 20 m above the canopy of bean plots. Ground-validation sampling included harvesting entire bean plots and photographing individual leaves. Image analyses were used to quantify the amount of defoliation by E. varivestis feeding on both aerial images and ground-validation photos. Linear regression analysis was used to determine the relationship of bean defoliation by E. varivestis measured on aerial images with that found by the ground validation. The results of this study showed a significant positive relationship between bean damages assessed by ground validation and those by using RGB images and a significant negative relationship between the actual amount of bean defoliation and Normalized Difference Vegetation Index values. Thermal signatures associated with bean defoliation were not detected. Spatial analyses using geostatistics revealed the spatial dependency of bean defoliation by E. varivestis. These results suggest the potential use of RGB and multispectral sensors at flight altitudes of 2 to 6 m above the canopy for early detection and site-specific management of E. varivestis , thereby enhancing management efficiency. [ABSTRACT FROM AUTHOR]

Ammonia gas is a colorless gas that is known for its pungent odor. It is commonly used in various industries, such as agriculture, refrigeration, and chemical manufacturing. This paper provides a comprehensive overview of various technologies employed in ammonia gas sensors. The objective is to compare and identify the optimum method to detect ammonia gas. The review encompasses catalytic gas sensors, metal oxide gas sensors, polymer conductivity gas sensors, optical gas sensors, and indirect gas sensors, detailing their respective operational principles. Additionally, the advantages and disadvantages of each technology for ammonia gas detection are outlined. All these technologies have been used for many applications and some of them have been commercialized. Some sensor characteristics suggestions are also stated in order to develop an improved optical ammonia sensor for industrial applications. [ABSTRACT FROM AUTHOR]

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This study focused on utilizing cellulose nanocrystal (CNC)–polyvinyl alcohol (PVA) composite in optical sensor applications to detect high humidity conditions and determine water concentration in ethanol. We focused on the composite's effectiveness in moisture absorption to demonstrate visual color change. We demonstrated that the different molecular weights of PVA significantly affect CNC's chiral nematic structure and moisture absorption capability. PVA with molecular weight 88 k–97 k exhibited the disintegration of its chiral nematic structure at 30 wt%, whereas low molecular weight PVA (n~1750) showed no structural disintegration even at 100 wt% concentration when analyzed through UV-Vis spectroscopy. Further, the thermal crosslinking of the CNC-PVA composite showed no significant loss of moisture sensitivity for all molecular weights of the PVA. We observed that the addition of PVA to the sulfated CNC obtained from sulfuric acid hydrolysis did not facilitate moisture absorption significantly. A CNC-PVA sensor was developed which can detect high humidity with 2 h. of exposure time. 2,2,6,6-tetramethylpiperidin-1-piperidinyloxy oxidized CNC (TEMPO-CNC) having carboxylic functionality was also used to prepare the CNC-PVA composite films for comparing the effect of functional groups on moisture sensitivity. Finally, we demonstrated a facile method for utilizing the composite as an optical sensor to detect water concentration in ethanol efficiently; thus, it can be used in polar organic solvent dehydration applications. [ABSTRACT FROM AUTHOR]

The ability to distribute entanglement between quantum nodes may unlock new capabilities in the future that include teleporting information across multinode networks, higher resolution detection via entangled sensor arrays, and measurements beyond the quantum limit enabled by networked atomic clocks. These new quantum networks also hold promise for the Aerospace community in areas such as deep space exploration, improved satellite communication, and synchronizing drone swarms. Although exciting, these applications are a long way off from providing a "real-world" benefit, as they have only been theoretically explored or demonstrated in small-scale experiments. An outstanding challenge is to identify near-term use cases for quantum networks; this may be an intriguing new area of interest for the aerospace community, as the quantum networking field would benefit from more multidisciplinary collaborations. This paper introduces quantum networking, discusses the difficulties in distributing entanglement within these networks, highlights recent progress toward this endeavor, and features two current case studies on mobile quantum nodes and an entangled clock network, both of which are relevant to the aerospace community. [ABSTRACT FROM AUTHOR]

[Display omitted] • Optical sensors are highly-promising for seed phenotype digitization. • Spectroscopy, digital imaging, and 3D reconstruction are primarily used digital techniques. • Optical sensors can detect both visible external and invisible internal phenotypes. • Matched optical sensors can effectively reduce resource loss in seed phenotype evaluation. • Future research should focus on phenotype equipment, platform, and data processing algorithms for automatic, integrated, and intelligent evaluation. The breeding of high-quality, high-yield, and disease-resistant varieties is closely related to food security. The investigation of breeding results relies on the evaluation of seed phenotype, which is a key step in the process of breeding. In the global digitalization trend, digital technology based on optical sensors can perform the digitization of seed phenotype in a non-contact, high throughput way, thus significantly improving breeding efficiency. This paper provides a comprehensive overview of the principles, characteristics, data processing methods, and bottlenecks associated with three digital technique types based on optical sensors: spectroscopy, digital imaging, and three-dimensional (3D) reconstruction techniques. In addition, the applicability and adaptability of digital techniques based on the optical sensors of maize seed phenotype traits, namely external visible phenotype (EVP) and internal invisible phenotype (IIP), are investigated. Furthermore, trends in future equipment, platform, phenotype data, and processing algorithms are discussed. This review offers conceptual and practical support for seed phenotype digitization based on optical sensors, which will provide reference and guidance for future research. The digital techniques based on optical sensors can perform non-contact and high-throughput seed phenotype evaluation. Due to the distinct characteristics of optical sensors, matching suitable digital techniques according to seed phenotype traits can greatly reduce resource loss, and promote the efficiency of seed evaluation as well as breeding decision-making. Future research in phenotype equipment and platform, phenotype data, and processing algorithms will make digital techniques better meet the demands of seed phenotype evaluation, and promote automatic, integrated, and intelligent evaluation of seed phenotype, further helping to lessen the gap between digital techniques and seed phenotyping. [ABSTRACT FROM AUTHOR]

Parts with a large depth-to-diameter ratio play a critical role in the military, aerospace, and automotive industries. However, accurately measuring their inner surface profile remains challenging owing to the lack of adequate and accurate sensors. We developed a multi-ring structured light system to obtain three-dimensional data of inner contours, such as inner diameters, which are crucial for ensuring component performance and safety. In this study, we proposed three simple yet effective techniques to improve the multi-ring beam structured measurement system. First, we designed a distortion correction method to calibrate the imaging system. Second, a two-step calibration approach was used to calibrate the multi-ring projection. Meanwhile, we benchmarked the effects of different light sources on image speckles. The calibration results demonstrated that the coefficient of determination (R-2) used for line fitting exceeded 0.999. Moreover, the measurement experimental results show that the uncertainty of less than 10 µm and the smallest measurable pipe inner diameter can reach 15 mm, demonstrating that our methods are promising for improving the accuracy of structured light optical sensing systems. This system satisfies the measurement requirements and can be immediately utilized to meet the high demand for inner contour measurements in industrial applications. [ABSTRACT FROM AUTHOR]

Diabetes is a chronic metabolic disorder characterized by prolonged elevated blood glucose levels. This research endeavours to assess the efficacy of a surface plasmon resonance (SPR)-based sensor for continuous diabetes monitoring. The proposed sensor structure follows the Kretschmann configuration, incorporating key components such as a prism, Silver/Copper, Cerium Oxide, black phosphorus (BP), and a specialized sensing medium. Within this investigation, two distinct sensor structures, denoted as Structure I and Structure II, have been meticulously constructed using the specified layers. The research employs advanced techniques, including the transfer matrix method and angular interrogation, to evaluate the SPR sensor's performance at a wavelength of 633 nm. The study rigorously analyses the detection capabilities for a specific biological sample, considering parameters such as sensitivity (S), detection accuracy (DA), quality factor (QF), and dip-of-figure of merit (DFOM). Notably, the glucose detection process achieves remarkable results, with Structure I and Structure II exhibiting maximum sensitivities of 217 degree/RIU and 217 degree/RIU, DA values of 0.41 and 0.315, QF values of 89.13 RIU−1 and 68.45 RIU−1, and DFOM values of 31,281.53 and 24,213.34, respectively. Ultimately, this research culminates in a comparative study, underscoring the potential of the proposed sensor as a high-performance tool for glucose level detection, thereby paving new avenues in the realms of biological and biomedical technologies. [ABSTRACT FROM AUTHOR]

Abstract This paper presents a symmetric all-dielectric two-dimensional grating with high transmittance and high figure of merit based on cylindrical nanoarrays as a liquid sensing structure with small volume and high sensitivity. The device is optimized using the finite element method to calculate the transmissivity under TE/TM polarization. When the incident angle is 4 degrees, the transmissivity of the grating is nearly 1 with a full width at half maximum of 0.016 nm and a sensitivity of 256.2 nm/RIU. The high figure of merit is 16214.936, and the corresponding quality factor can reach 56572.438. The sensor characteristics of the incident angle on the device are analyzed, and the normalized electric field distribution indicates that the change of the incident angle has a significant modulation ability for the resonance energy distribution. The proposed sensor is independent of polarization state, easy to control and integrate, and has broad application prospects in fields such as liquid solution detection, ocean surveys, and position sensing.

Abstract In recent years, following the outbreak of the COVID-19 pandemic, there has been a significant increase in cases of SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) and related deaths worldwide. Despite the pandemic nearing its end due to the introduction of mass-produced vaccines against SARS-CoV-2, early detection and diagnosis of the virus remain crucial in preventing disease progression. This article explores the rapid identification of SARS-CoV-2 by implementing a multimode plasmonic refractive index (MMRI) optical sensor, developed based on the split ring resonator (SRR) design. The Finite Difference Time Domain (FDTD) numerical solution method simulates the sensor. The studied sensor demonstrates three resonance modes within the reflection spectrum ranging from 800 nm to 1400 nm. Its material composition and dimensional parameters are optimized to enhance the sensor’s performance. The research indicates that all three resonance modes exhibit strong performance with high sensitivity and figures of merit. Notably, the first mode achieves an exceptional sensitivity of 557 nm/RIU, while the third mode exhibits a commendable sensitivity of 453 nm/RIU and a Figure of Merit (FOM) of 45 RIU−1. These findings suggest that the developed MMRI optical sensor holds significant potential for the early and accurate detection of SARS-CoV-2, contributing to improved disease management and control efforts.

Abstract Background Disease-vector mosquito monitoring is an essential prerequisite to optimize control interventions and evidence-based risk predictions. However, conventional entomological monitoring methods are labor- and time-consuming and do not allow high temporal/spatial resolution. In 2022, a novel system coupling an optical sensor with machine learning technologies (VECTRACK) proved effective in counting and identifying Aedes albopictus and Culex pipiens adult females and males. Here, we carried out the first extensive field evaluation of the VECTRACK system to assess: (i) whether the catching capacity of a commercial BG-Mosquitaire trap (BGM) for adult mosquito equipped with VECTRACK (BGM + VECT) was affected by the sensor; (ii) the accuracy of the VECTRACK algorithm in correctly classifying the target mosquito species genus and sex; (iii) Ae. albopictus capture rate of BGM with or without VECTRACK. Methods The same experimental design was implemented in four areas in northern (Bergamo and Padua districts), central (Rome) and southern (Procida Island, Naples) Italy. In each area, three types of traps—one BGM, one BGM + VECT and the combination of four sticky traps (STs)—were rotated each 48 h in three different sites. Each sampling scheme was replicated three times/area. Collected mosquitoes were counted and identified by both the VECTRACK algorithm and operator-mediated morphological examination. The performance of the VECTRACK system was assessed by generalized linear mixed and linear regression models. Aedes albopictus capture rates of BGMs were calculated based on the known capture rate of ST. Results A total of 3829 mosquitoes (90.2% Ae. albopictus) were captured in 18 collection-days/trap/site. BGM and BGM + VECT showed a similar performance in collecting target mosquitoes. Results show high correlation between visual and automatic identification methods (Spearman Ae. albopictus: females = 0.97; males = 0.89; P

Background: The breeding of high-quality, high-yield, and disease-resistant varieties is closely related to food security. The investigation of breeding results relies on the evaluation of seed phenotype, which is a key step in the process of breeding. In the global digitalization trend, digital technology based on optical sensors can perform the digitization of seed phenotype in a non-contact, high throughput way, thus significantly improving breeding efficiency. Aim of review: This paper provides a comprehensive overview of the principles, characteristics, data processing methods, and bottlenecks associated with three digital technique types based on optical sensors: spectroscopy, digital imaging, and three-dimensional (3D) reconstruction techniques. In addition, the applicability and adaptability of digital techniques based on the optical sensors of maize seed phenotype traits, namely external visible phenotype (EVP) and internal invisible phenotype (IIP), are investigated. Furthermore, trends in future equipment, platform, phenotype data, and processing algorithms are discussed. This review offers conceptual and practical support for seed phenotype digitization based on optical sensors, which will provide reference and guidance for future research. Key scientific concepts of review: The digital techniques based on optical sensors can perform non-contact and high-throughput seed phenotype evaluation. Due to the distinct characteristics of optical sensors, matching suitable digital techniques according to seed phenotype traits can greatly reduce resource loss, and promote the efficiency of seed evaluation as well as breeding decision-making. Future research in phenotype equipment and platform, phenotype data, and processing algorithms will make digital techniques better meet the demands of seed phenotype evaluation, and promote automatic, integrated, and intelligent evaluation of seed phenotype, further helping to lessen the gap between digital techniques and seed phenotyping.

This study focused on utilizing cellulose nanocrystal (CNC)–polyvinyl alcohol (PVA) composite in optical sensor applications to detect high humidity conditions and determine water concentration in ethanol. We focused on the composite’s effectiveness in moisture absorption to demonstrate visual color change. We demonstrated that the different molecular weights of PVA significantly affect CNC’s chiral nematic structure and moisture absorption capability. PVA with molecular weight 88 k–97 k exhibited the disintegration of its chiral nematic structure at 30 wt%, whereas low molecular weight PVA (n~1750) showed no structural disintegration even at 100 wt% concentration when analyzed through UV-Vis spectroscopy. Further, the thermal crosslinking of the CNC-PVA composite showed no significant loss of moisture sensitivity for all molecular weights of the PVA. We observed that the addition of PVA to the sulfated CNC obtained from sulfuric acid hydrolysis did not facilitate moisture absorption significantly. A CNC-PVA sensor was developed which can detect high humidity with 2 h. of exposure time. 2,2,6,6-tetramethylpiperidin-1-piperidinyloxy oxidized CNC (TEMPO-CNC) having carboxylic functionality was also used to prepare the CNC-PVA composite films for comparing the effect of functional groups on moisture sensitivity. Finally, we demonstrated a facile method for utilizing the composite as an optical sensor to detect water concentration in ethanol efficiently; thus, it can be used in polar organic solvent dehydration applications.

Abstract Extracellular vesicles (EVs) are promising tools for the early diagnosis of diseases, and bacterial membrane vesicles (MVs) are especially important in health and environment monitoring. However, detecting EVs or bacterial MVs presents significant challenges for the clinical translation of EV-based diagnostics. In this Review, we provide a comprehensive discussion on the basics of nanoplasmonic sensing and emphasize recent developments in nanoplasmonics-based optical sensors to effectively identify EVs or bacterial MVs. We explore various nanoplasmonic sensors tailored for EV or bacterial MV detection, emphasizing the application of localized surface plasmon resonance through gold nanoparticles and their multimers. Additionally, we highlight advanced EV detection techniques based on surface plasmon polaritons using plasmonic thin film and nanopatterned structures. Furthermore, we evaluate the improved detection capability of surface-enhanced Raman spectroscopy in identifying and classifying these vesicles, aided by plasmonic nanostructures. Nanoplasmonic sensing techniques have remarkable precision and sensitivity, making them a potential tool for accurate EV detection in clinical applications, facilitating point-of-care molecular diagnostics. Finally, we summarize the challenges associated with nanoplasmonic EV or bacterial MV sensors and offer insights into potential future directions for this evolving field. Graphical Abstract

Metabolomics research is gaining traction lately as there is a growing interest in studying the global relationship between human diseases and the metabolite network. The presence and concentration of beneficial gut-derived metabolites depends on the individual's microbiota composition and diet, with direct metabolite-based supplementation being an appealing option for those unable to produce them. This work serves as an approach in the direct detection of gut-derived metabolites through a smartphone-based approach, as a faster and cheaper alternative to more traditional techniques such as chromatography or the study of gut bacteria culture. Urolithin, a beneficial gut microbial metabolite, was successfully detected with our developed smartphone-based optical assay with low limits of detection of 0.257–0.422 μM that were comparable to those measured with a fluorescence spectrophotometer or even better than some reported HPLC methods. On top of a good sensitive detection with a reduced analysis time, the proposed "turn off-to-on" fluorescence sensing strategy that employed graphene quantum dots coupled with copper-(II) ions also distinguished urolithin metabotypes and exhibited good selectivity in the presence of other reducing compounds and phenolic analogues. Our developed approach has demonstrated its versatility in direct gut-derived metabolite detection in commercial dietary supplements, making it a user-friendly tool for food and pharmaceutical product analysis. [ABSTRACT FROM AUTHOR]

This study presents a new method for detecting and monitoring heavy metal ions in water samples. The method uses liquid crystal‐based optical sensors and a molecular probe called dodecyl‐N‐iminodiacetic acid (DIDAA). The probe's hydrophilic polar diacetate head group acts as a chelator for heavy metal ions, while its hydrophobic non‐polar tail aligns the liquid crystal molecules. When heavy metal ion‐contaminated water samples are introduced, the LC alignment is rapidly disrupted, resulting in bright optical signals. The sensor has a detection limit of 0.1, 0.3, 1.0, and 5.0 μM for for Mercury (Hg2+), Copper (Cu2+), Cadmium (Cd2+), and Lead (Pb2+) respectively. The diacetate probe remains effective even after multiple uses and was not affected by changes in pH. Its activity could persist for over 5 days. Furthermore, this sensor could be reversed and reused to detect HMIs in the presence of EDTA, making it a potential candidate for developing logic gates at the molecular level. [ABSTRACT FROM AUTHOR]

Today, humidity sensors have become an integral part of the daily lives. In particular, humidity sensors using an electronic measuring principle have become the standard. Although these sensors have proven to be a stable measurement method, they have some disadvantages, such as their long response time or the danger of using them in explosive environments. This work introduces photonic crystals as an alternative optical measurement approach. The novel technology of ultra‐fast two‐photon polymerisation printing is combined with a thin‐film deposition process, namely iCVD. This allows to print large area high‐precision 3D templates, which are subsequently coated with a humidity responsive hydrogel thin film (p(HEMA) of 20 nm.The limits of 2PP technology are being pushed allowing the production ofs table and periodic large‐area 3D structures. The flexible customization of hydrogels for ambient conditions make them exceptionally promising for a wide range of sensing applications. Additionally, optical methods for measuring humidity seem to be an excellent alternative to overcome the limitations for current state of the art humidity sensors. The optical detection of changes in ambient air humidity is achieved by observing color changes of the printed structure within the visible wavelength range. [ABSTRACT FROM AUTHOR]

In recent decades, the dynamics of road vehicle traffic have significantly evolved, compelling traffic engineers to develop innovative traffic monitoring solutions, especially for dense road networks. Traditional methods for measuring traffic volume along road sections may no longer suffice for modern traffic control systems. This is particularly true for induction loops, a widely used method since the last century. In contrast, measuring techniques using microwaves or visible light offer better accuracy but are often hindered by the high cost of sensors. This paper presents new techniques for measuring traffic flow and other parameters that adapt to changing traffic dynamics using low-cost optical distance sensors. Our study demonstrates that the integration of multiple monitoring approaches enhances measurement accuracy, contingent on the dynamics and specific characteristics of the traffic. The results indicate that cheap optical distance sensors are particularly well suited for use in smart city road networks. [ABSTRACT FROM AUTHOR]

Copper (Cu2+) is a transition metal ion extensively distributed in numerous foodstuffs of both animals and vegetables. An excess intake of Cu2+ ions cause injury, pneumonitis, a disorder in the nervous system, and gastrointestinal problems. Hence, we have developed a simple and novel Schiff base‐based fluorescence sensor for the detection of Cu2+ ions. The sensor, ‐3‐(1H‐indol‐3‐yl)‐2‐((4‐nitrobenzylidene) amino)propanoic acid (INAP), was synthesized from tryptophan and nitrobenzaldehyde by the reflux method and characterized by various analytical methods. The prepared INAP acted as a chemical sensor and displayed outstanding sensitivity and choosiness characteristics for Cu2+ ions an aqueous solvent. In the presence of Cu2+, it demonstrated a fluorescence change in an aqueous medium with a "turn‐off" phenomenon via complex‐mediated energy transfer characteristics, and the method of continuous variation suggested a 1 : 2 complex formation of the metal ion with INAP. The LOD of the sensor system was calculated to be 1.3 μM for the Cu2+ ion. In addition, the INAP fluorescent probe was applied to tap water samples and found acceptable recoveries. These results suggest that the newly fabricated sensor system would be explored as a chemosensor for the recognition of Cu2+ ions in environmental samples. [ABSTRACT FROM AUTHOR]

Many odors, like perfumes, are complex mixtures of chiral and achiral molecules where the cost‐efficient (enantio−)selective sensing represents a major technical challenge. Here, we present a colorimetric sensor array of surface‐mounted metal‐organic‐framework (SURMOF) films in Fabry‐Pérot (FP) cavities. The optical properties of the FP‐SURMOF films with different chiral and achiral structures are affected by the (enantio−)selective adsorption of the analytes in the SURMOF pores, resulting in different responses to the analyte molecules. The read‐out of the sensor array is performed by the digital camera of a common smartphone, where the RGB values are determined. By analyzing the sensor array data with simple machine learning algorithms, the analytes are discriminated. After demonstrating the enantioselective response for a pair of pure chiral odor molecules, we apply the sensor array to detect and discriminate a large number (16) of common commercial perfumes and eau de toilettes. While our untrained human nose is not able to discriminate all perfumes, the presented colorimetric sensor array can classify all perfumes with great classification accuracy. Moreover, the sensor array was used to identify unlabeled samples correctly. We foresee such an FP‐chiral‐SURMOF‐based sensor array as a powerful approach toward inexpensive selective odors sensing applications. [ABSTRACT FROM AUTHOR]

This paper presents a new approach to particle detection using an active microresonator operating in the transparency regime. Simulations demonstrate that when particles interact with the microresonator surface, they induce optical losses. To compensate for these losses, the optical gain is amplified to restore the transparency regime. Simulation results show a linear relationship between nanoparticle concentration and the pump power required to compensate for optical losses. By the use of microresonator with a very high quality factor, this approach offers an accurate and sensitive method for detecting nanoparticles, without the need for complex equipment. [ABSTRACT FROM AUTHOR]

An environmentally conscious methodology is investigated for the precise and discerning identification of trace concentrations of gold ions in diverse matrices. A novel optical sensor membrane is proposed for the determination of Au3+ ions, utilizing the immobilization of β-2-hydroxybenzyl-3-methoxy-2-hydroxyazastyrene (HMHS) entrapped in polyvinyl chloride (PVC). The sensor incorporates sodium tetraphenylborate (Na-TPB) as the ionic additive and dibutyl phthalate (DBP) as a plasticizer. Under optimal conditions, the suggested sensor exhibits a linear calibration response to Au3+ ions within a concentration range of 5.0 to 165 ng mL−1. Detection and quantification limits are specified as 1.5 and 4.8 ng mL−1, respectively, with a rapid response time of 5.0 min. Upon presentation, this optical sensor not only affirms high reproducibility, stability, and an extended operational lifespan but also showcases exceptional selectivity for Au3+ ions. Notably, no discernible interference is observed when assessing the potential influence of other cations and anions on Au3+ ion detection. The adaptability of this optical sensor is validated through its successful application in determining Au3+ ion concentrations across various sample types, including water, environmental, cosmetics, and soil matrices. [ABSTRACT FROM AUTHOR]

In this article, a surface plasmon resonance (SPR) sensor based on photonic crystal fiber (PCF) is simulated and analyzed by finite element method (FEM). Gold and titanium oxide (TiO2) are used as plasmonic layers. The TiO2 layer is placed under the gold layer to increase the sensitivity of this sensor. The sensor's top and bottom surfaces are polished, and the plasmonic layer is placed on both these surfaces. Unlike sensors with typical external circular coating, less plasmonic material is used. Additionally, unlike internal coating sensors, there is no issue of partial air holes coating and achieving a uniform thickness of the plasmonic layer. Also using two plasmonic levels can expand the range of refractive index (RI) detection. The sensor's structure creates birefringence, allowing complete coupling between the core mode and both plasmonic layers. This results in more reliable detection ability. By optimizing the dimensions and arrangement of air holes and the sensor's structure, the ability to detect unknown analytes in the ultra-wide range of refractive index of 1.21–1.41 with the maximum wavelength sensitivity (WS) of 61,000 nm / RIU , the maximum amplitude sensitivity (AS) of 1294.29 RIU - 1 , the maximum figure of merit (FOM) of 657.14 RIU - 1 and the sensor resolution (SR) of 4.35 × 10–6 RIU have been obtained. This sensor operates in the visible to near-infrared wavelength range. During its design, feasibility in construction was taken into consideration, along with reducing the complexity and multiplicity of structural parameters. As a result, the sensor delivers excellent performance in detection parameters and is a suitable option for RI detection applications like organic chemicals and biosensing. [ABSTRACT FROM AUTHOR]

This paper presents a graphene–gold-metasurface sensor designed for rapid and precise detection of heavy metals, particularly Cu2+ and Mg2+ ions, in water samples. By employing COMSOL simulations, the sensor's performance across various cases was comprehensively analyzed. The sensor demonstrates an optimized sensitivity of 1140 GHz/RIU for Cu2+ detection and 1149 GHz/RIU for Mg2+ detection. Furthermore, this sensor achieves minimum figure of merit (FOM) of 2.781 RIU−1 and 2.855 RIU−1 for Cu2+and Mg2+ detection, respectively, showcasing its superior performance in sensing these metal ions. Also the highest quality factors (Q factors) of 11.244 for Cu2+ detection and Q factor 11.247 for Mg2+ detection are attained. The proposed sensor structure additionally demonstrates very low detection limits- which is 0.466 for Cu2+ and 0.485 for Mg2+ detection-and this implies it can detect trace amounts without any difficulty. The excellent promising features of this sensor position it as a self directed candidate for detection of Cu2+ and Mg2+ ions with high accuracy and sensitivity. These solid applications act as the gateway to the monitoring of environmental cleanliness among other applications. Additionally,the proposed sensor can also be used as a 2-bit encoder. [ABSTRACT FROM AUTHOR]

The article proposes the simulation of a 2D photonic crystal structure for the diagnosis of different cancerous and tumour cell detection. The race-track microring resonator (RT-MRR)-based structure has been modelled using FDTD simulation platform. The variation in the index of refraction of the normal and the infected cells has been observed. This difference primes to the alteration in the strength of the light intensity and aids to notice for the detection of cells. The model is sensitive, reliable, simple, and compact and may be included in different sensing applications. [ABSTRACT FROM AUTHOR]

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Extracellular vesicles (EVs) are promising tools for the early diagnosis of diseases, and bacterial membrane vesicles (MVs) are especially important in health and environment monitoring. However, detecting EVs or bacterial MVs presents significant challenges for the clinical translation of EV-based diagnostics. In this Review, we provide a comprehensive discussion on the basics of nanoplasmonic sensing and emphasize recent developments in nanoplasmonics-based optical sensors to effectively identify EVs or bacterial MVs. We explore various nanoplasmonic sensors tailored for EV or bacterial MV detection, emphasizing the application of localized surface plasmon resonance through gold nanoparticles and their multimers. Additionally, we highlight advanced EV detection techniques based on surface plasmon polaritons using plasmonic thin film and nanopatterned structures. Furthermore, we evaluate the improved detection capability of surface-enhanced Raman spectroscopy in identifying and classifying these vesicles, aided by plasmonic nanostructures. Nanoplasmonic sensing techniques have remarkable precision and sensitivity, making them a potential tool for accurate EV detection in clinical applications, facilitating point-of-care molecular diagnostics. Finally, we summarize the challenges associated with nanoplasmonic EV or bacterial MV sensors and offer insights into potential future directions for this evolving field. [ABSTRACT FROM AUTHOR]

This article shows an all-dielectric metasurface consisting of "H"-shaped silicon disks with tilted splitting gaps, which can detect the temperature and refractive index (RI). By introducing asymmetry parameters that excite the quasi-BIC, there are three distinct Fano resonances with nearly 100% modulation depth, and the maximal quality factor (Q-factor) is over 104. The predominant roles of different electromagnetic excitations in three distinct modes are demonstrated through near-field analysis and multipole decomposition. A numerical analysis of resonance response based on different refractive indices reveals a RI sensitivity of 262 nm/RIU and figure of merit (FOM) of 2183 RIU−1. This sensor can detect temperature fluctuations with a temperature sensitivity of 59.5 pm/k. The proposed metasurface provides a novel method to induce powerful TD resonances and offers possibilities for the design of high-performance sensors. [ABSTRACT FROM AUTHOR]

In this study, we present a glucose sensor that utilises photonic crystal fibre. The proposed sensor was analysed and demonstrated numerically. A unique structure was infiltrated into the first ring of holes with glucose, serving as the test analyte. We achieved an exceptionally high average spectral sensitivity. Three different wavelengths, 1.1, 1.3 and 1.55 µm, were selected for this investigation. Notably, while the reported sensitivity was already high when the remaining gaps within the structure were filled with air, it was significantly higher when the holes were infiltrated with water at a wavelength of 1.55 µm, calculated to be 0.11493 ps/(nm·km)/(g/l). We anticipate that this sensor will prove to be a valuable tool for glucose sensing and could contribute to further advancements in non-invasive glucose measurement. [ABSTRACT FROM AUTHOR]

An optoelectronic sensor was developed to measure the in-plane displacement between two parallel surfaces. This sensor used a photodetector, which was placed on one of the parallel surfaces, to measure the intensity of the red (R), green (G), blue (B), and white/clear (C) light spectra of a broad-spectrum light that was reflected off a color grid on the opposing surface. The in-plane displacement between these two surfaces caused a change in the reflected RGB and C light intensity, allowing the prediction of the displacement direction and magnitude by using a polynomial regression prediction algorithm to convert the RGB and C light intensity to in-plane displacement. Results from benchtop experiments showed that the sensor can achieve accurate displacement predictions with a coefficient of determination R2 > 0.97, a root mean squared error (RMSE) < 0.3 mm, and a mean absolute error (MAE) < 0.36 mm. By measuring the in-plane displacement between two surfaces, this sensor can be applied to measure the shear of a flexible layer, such as a shoe's insole or the lining of a limb prosthesis. This sensor would allow slippage detection in wearable devices such as orthotics, prostheses, and footwear to quantify the overfitting or underfitting of these devices. [ABSTRACT FROM AUTHOR]

In this work, we studied the effect noble metal thicknesses, namely gold (Au), silver (Ag), and copper (Cu) on the surface plasmon resonance (SPR) characteristics for sensitive optical sensor and biosensor applications. SPR spectra for Au, Ag and Cu were widely studied in the Fresnel equation to calculate the total reflection, the wavelength (λ) range from 500 nm to 700 nm with the angle of incidence () ranging from 0∘ to 90∘ and thickness of the film (d) reaching from 30 nm to 70 nm. Analysis simulation (in MATLAB) has been made for SPR of three metals placed on the N_LASF9 glass prism and the sensing medium is the air. The properties of the angle of resonance SPR have been calculated from plotted reflectance via incident angle SPR . The results give efficient detection in a change of reflection (R) and full half width maximum FWHM. The minimum reflection was obtained (0.003 a.u.) at wavelength 700 nm and thickness d = 50 nm for gold Au at Δ n = 0.0. The best FWHM was recorded at the wavelength (500 nm) at thickness (70 nm) for silver at Δ n = 0.0, which was equal (0.1 nm). [ABSTRACT FROM AUTHOR]

Terahertz waveguides and resonators have brought numerous applications from biomedical to modern communications. In this paper, we have demonstrated numerically a straight semiconductor-insulator-semiconductor(SIS) waveguide attached to a split ring resonator, which acts as a terahertz frequency filter and can be used for refractive index sensing. The device's transmission properties have been studied using the finite element method. To fix the third dimension of the device, that is the depth of the waveguide the effective mode index and power density calculations are done for the propagating mode. The frequency tuning of the filter is achieved by changing the geometric parameters of the waveguide and resonator system such as ring radii and split width. Both the symmetric and antisymmetric modes of the split ring show almost the same rate of change of resonance frequency with the change in geometric parameters. To demonstrate the importance of the split position, the transmittance is studied by placing the split at different positions on the ring. We obtained the same transmittance for the split at left and right positions, whereas the split at the top and bottom shows different transmittance similar to the transmittance of a ring resonator. The symmetric and antisymmetric modes of the split ring are calculated for refractive index sensing and the highest sensitivity of 0.741 THz/ refractive index unit (RIU) for the symmetric mode as expected. [ABSTRACT FROM AUTHOR]

Utilizing the self-organization of materials to make systematic and ordered wrinkled patterns can be very useful for optical, electronic, adhesives and many other applications. In this work, we have demonstrated the fabrication of a self-organized, linearly ordered, wrinkled pattern developed in the polystyrene (PS) thin film by controlled buckling in the film. Buckling was induced in the thin film by bending an elastic polydimethylsiloxane (PDMS) substrate along the two sides producing variable stress along both sides of the bending axis. Controlling of the self-organized patterns in the PS thin film was obtained by varying stress in the elastic PDMS substrate and thin-film thickness of PS. Theoretical analysis and experimental results were compared, and the developed structure was demonstrated to be used as a smart optical filter giving different intensities of diffused light for different positions of the substrate. [ABSTRACT FROM AUTHOR]

The increasing demand for optical sensors is driven by their wide applications, making surface plasmon resonance (SPR) play a crucial role in this field. In this study, a multilayered thin film consisting of tantalum pentoxide (Ta2O5) and silver (Ag) deposited on a glass prism was used to study SPR. The Ag layer thickness was fixed at 50 nm, while the Ta2O5 layer thickness varied from 0 to 70 nm. The Kretschmann configuration was employed to assess the sensitivity of air and gases with different refractive indices. Therefore, different layer thicknesses along with different wavelengths and angles were investigated. MATLAB software was employed to simulate and analyze SPR with a half-sphere prism to extend the incident angle. The simulation conditions with Fresnel equations were used to calculate the reflectivity and transmittance coefficients for the studied sample. The results revealed that the best output was at a Ta2O5 thickness of 50 nm to get optimal full width at half maximum of 2.4 and sensitivity factor of 162.5. This device works in the visible and infrared regions. [ABSTRACT FROM AUTHOR]

Biochemical sensors have important applications in biology, chemistry, and medicine. Nevertheless, many biochemical sensors are hampered by intricate techniques, cumbersome procedures, and the need for labeling. In the past two decades, it has been discovered that liquid crystals can be used to achieve the optical amplification of biological interactions. By modifying recognition molecules, a variety of label-free biochemical sensors can be created. Consequently, biochemical sensors based on the amplification of liquid crystals have become one of the most promising sensors. This paper describes in detail the optical sensing principle of liquid crystals, sensing devices, and optical detection technologies. Meanwhile, the latest research findings are elucidated. Finally, the challenges and future research directions are discussed. [ABSTRACT FROM AUTHOR]

A photosensitive TFT sensor called bias TFT fabricated using simple amorphous silicon process in this paper. The photosensitive current of bias TFT is linearly related to the brightness of the top light source and inversely proportional to the size of the bias region. The photosensitivity current can be up to 10E‐8 amperes under 100 nits illumination. Among four shapes of bias TFTs, L‐type TFTs have the highest photo current. [ABSTRACT FROM AUTHOR]

An innovative and exceptionally responsive optical sensing device engineered to selectively identify Bi(III) ions in water-based solutions. The sensing component, 5-(2′,4′-dimethylphenylazo)-6-hydroxypyrimidine-2,4-dione (DMPAHPD), is incorporated into a plasticized polyvinyl chloride (PVC) membrane. The sensor demonstrates an exceptional selectivity for Bi(III) within a broad dynamic range spanning from 7.5 × 10−10 to 4.2 × 10−5 M at pH 2.25. Notably, it achieves lower quantification and detection limits of 7.25 × 10−10 and 2.15 × 10−10 M, respectively. The optode membrane’s response to Bi(III) proves to be entirely reversible, demonstrating remarkable selectivity for Bi(III) ions over a diverse range of other cations and anions. The sensor exhibits favorable performance characteristics, including good reversibility, a wide dynamic range, a prolonged lifespan, sustained response stability over the long term, and high reproducibility. This visual chemical sensor exhibits potential for real-world usage, offering consistent outcomes when assessing Bi(III) levels in matrices such as water, soil, plants, biological and synthetic mixtures. Importantly, the sensor’s performance is comparable to corresponding data achieved from inductively coupled plasma atomic emission spectroscopy (ICP-AES).

The characteristics of a differentially-operated optical displacement sensor developed for wind-tunnel using magnetic suspension are studied both analytically and experimentally. The target sensor measures the three-dimensional displacement of the suspended object (floator) from the variations of the shadow of the floator. It is composed of eight optical systems. First, the output characteristics of the fabricated sensor are measured. As to linearity, it is good in the direction of light (x-axis) but inferior in the other directions (y and z axes). In addition, interferences among the axes are observed. Because the differences in characteristics among the optical systems cause such errors, adjustments by software are carried out. They reduce the nonlinearity and interferences. However, residual errors still remain. To clarify the reasons, the output characteristics are studied analytically by investigating the movement of the shadow of the floator and the variations of the illuminated area on the lenses. The results suggest that nonlinearity and interaxial interferences exist on some extent in the sensor, which was observed in the experiments.

This work presents the simulation and experimental results of a surface plasmon resonance (SPR) sensor made of a hard polymer-clad fiber. The cladding of the fiber is removed, and then a bimetallic film of nanometer thickness is deposited around the fiber core to create a ten-centimeter-long sensing surface. An optical sensor based on thin film combinations of silver and aluminum has a detection capability of about 3×10-6 (dB/RIU), allowing high sensitivity of easily fabricated optical sensors. This leads us to believe that the proposed SPR sensor can be used to detect biological targets during the clinical diagnosis of diseases, e.g., heart disease, Alzheimer’s disease, cardiovascular disease, and stroke.

In this paper, the Zn0.95Cu0.05O/p-Si heterojunction with lateral photovoltaic effect (LPE) is prepared that has the tuning effect and switching behavior of sunlight field. The dependence of the lateral photovoltage (LPV) on the laser position shows high sensitivity (20 mV mm−1) and strict linearity. Interestingly, the LPV eventually decreased to 0 mV as the sunlight intensity increased to 48 mW, under the constant laser intensity and position, indicating the application potential of a photo-switch. This light field effect results from the irradiation of sunlight, which changes the position of quasi-Fermi level, reduces the drive power for carriers by the space charge region in the heterojunction, and increases the concentration of carriers resulting in increased the scattering between carriers to decrease the lifetime of carriers produced by the laser. This work can expand the application of LPE in the field of multifunctional devices such as photo-switches, position sensors and self-powered devices.

Optical sensors provide a fast and real-time approach to detect benzene, toluene, ethylbenzene, and xylenes (BTEX) in environmental monitoring and industrial safety. However, detecting the concentration of a particular gas in a mixture can be challenging. Here, we develop a machine-learning model that can precisely measure BTEX concentrations simultaneously based on an absorption spectroscopy gas sensing system. The convolutional neural network (CNN) is utilized to identify the absorbance spectra for each volatile, along with their concentrations in a mixture. A synthetic data set is generated using a series of physics-based simulations to create the predictive model. The data set consists of the overall absorbance of numerous random BTEX mixtures over time, based on various percentages of the permissible exposure limit (PEL). It is worth noting that benzene has a negligible absorbance (very low PEL, 1–5 ppm) compared to other volatile gases, which makes it difficult to detect. To address this challenge, we introduce a 3-stage solution to accurately discriminate between all BTEX species, regardless of their concentration levels. As a result, the R-squared above 0.99 for toluene, ethylbenzene, and o-xylene, and the R-squared above 0.96 for benzene, is achieved, indicating the model's capability to predict BTEX concentrations.