Search Results (7,988)

This study presents an ultra-sensitive dual-core photonic crystal fiber-based surface plasmon resonance (PCF-SPR) sensor for the detection of waterborne pathogens through refractive index (RI) variation. The proposed sensor integrates a bimetallic coating of silver and titanium dioxide (Ag–TiO₂). Silver ensures sharp plasmonic resonance, and TiO₂ enhances chemical stability and coupling efficiency. This dual-core configuration allows for increased interaction between the core-guided modes and the plasmonic interface. As a result, the sensor’s sensitivity improves significantly. The sensor can accurately detect analytes with an RI value of 1.28 to 1.43. It demonstrates a maximum wavelength sensitivity (WS) of 107,000 nm/RIU, an amplitude sensitivity (AS) of 2209.21 RIU⁻¹, a wavelength resolution of 9.35 × 10⁻⁷ RIU, and a figure of merit (FOM) of about 520. These results support the sensor’s ability to identify the presence of different pathogenic contaminants, such as E. coli, Vibrio cholerae, and Bacillus anthracis, based on their unique RI properties. This optimized design, high resolution, and potential for real-time detection enable this sensor to be a promising solution for environmental monitoring applications. Full article

The aim of this study was to conduct an advanced analysis of the MEMS sensor, including both experimental tests and numerical simulations, in order to determine its mechanical properties and operational dynamics in detail. It is challenging to find publications in the literature that are not based on theoretical assumptions or general manufacturer data, which do not reflect the actual microstructural characteristics of the sensor. This study uses a numerical model developed in MATLAB/Simulink, which allows the experimentally determined material characteristics to be combined with predictive dynamic modelling. The model takes into account key mechanical parameters such as stiffness, damping and response to dynamic loads, and the built-in optimisation algorithm allows the structural parameters of the MEMS accelerometer to be estimated directly from experimental data. In addition, SEM microscopic studies and EDS chemical composition analysis provided detailed information on the sensor’s microstructure, allowing its impact on mechanical properties and dynamic parameters to be assessed. The integration of advanced experimental methods with numerical modelling has resulted in a model whose response closely matches the measurement results, which is an important step towards further research on design optimisation and improving the reliability of MEMS sensors in diverse operating conditions. Full article

Effective abnormal behavior detection in ship operations is essential for ensuring navigational safety and operational efficiency in marina ports. This study presents a hybrid method that integrates statistical analysis and neural network modeling to detect abnormal behavior based on data obtained through leisure boat sea trials. Detection criteria were established based on ship motion characteristics, operating area conditions, and the properties of the sea trial data. The method combines Rayda’s criterion and standard deviation thresholds to identify sudden changes in measured data, while a Long Short-Term Memory (LSTM) network is used to predict normal ship behavior. Deviations between predicted and measured values were evaluated using three thresholds (levels 1, 2, and 3), with level 3 effectively isolating the most significant abnormal data (representing 2–10% of the data). The proposed method is capable of successfully identifying sudden acceleration or deceleration, unusual course changes, extended stationary periods, deviations from expected routes, complex maneuvers, and track continuity issues. The results demonstrate that the proposed hybrid method can reliably distinguish abnormal ship behaviors based on real sea trial data. To separate true abnormalities from false alarms or sensor and environmental noise, its practical application on a real ship is planned as future work. This study provides a foundation for intelligent ship monitoring systems and supports the development of autonomous and semi-autonomous navigation technologies. Full article

Mercury’s severe toxicity and persistence demand fast, low-cost, and sustainable detection. In this work, a Juglans regia ethanolic extract is introduced as an efficient biogenic reducing and stabilizing agent for the green synthesis of silver nanoparticles (AgNPs). This plant-mediated route enables environmentally friendly nanoparticle formation with suitable optical properties for sensing applications. To overcome the poor visual selectivity observed in the colloidal AgNPs suspension, the nanoparticles were immobilized onto filter paper to produce a solid-phase colorimetric sensor. The paper-based platform exhibited a highly selective response toward Hg²⁺, showing complete suppression of the yellow coloration exclusively in the presence of Hg²⁺, even when challenged with a 200-fold excess of potentially interfering ions. Quantitative colorimetric analysis revealed a broad linear detection range from 1 × 10⁻⁸ to 1 × 10⁻³ mol dm⁻³ and an excellent limit of detection of 1.065 × 10⁻⁸ mol dm⁻³, with visible color changes consistent with the calculated values. The sensor’s performance was further validated using real tap water samples, with recovery values ranging from 96% to 102%, confirming minimal matrix interference and reliable quantification. Altogether, this study demonstrates that Juglans regia-mediated AgNPs, integrated into a simple paper-based format, provide a fully green, low-cost, and portable platform for sensitive and selective on-site detection of Hg²⁺ in environmental waters. Full article

Thanks to both endogenous and exogenous antioxidants (AOs), the antioxidant defense system ensures redox homeostasis, which is crucial for protecting the body from oxidative stress and maintaining overall health. The food industry also exploits the antioxidant properties to prevent or delay the oxidation of other molecules during processing and storage. There are many classical methods for assessing antioxidant capacity/activity, which are based on mechanisms such as hydrogen atom transfer (HAT), single electron transfer (SET), electron transfer with proton conjugation (HAT/SET mixed mode assays) or the chelation of selected transition metal ions (e.g., Fe²⁺ or Cu¹⁺). The antioxidant capacity (AOxC) index value can be expressed in terms of standard AOs (e.g., Trolox or ascorbic acid) equivalents, enabling different products to be compared. However, there is currently no standardized method for measuring AOxC. Nanoparticle sensors offer a new approach to assessing antioxidant status and can be used to analyze environmental samples, plant extracts, foodstuffs, dietary supplements and clinical samples. This review summarizes the available information on nanoparticle sensors as tools for assessing antioxidant status. Particular attention has been paid to nanoparticles (with a size of less than 100 nm), including silver (AgNPs), gold (AuNPs), cerium oxide (CeONPs) and other metal oxide nanoparticles, as well as nanozymes. Nanozymes belong to an advanced class of nanomaterials that mimic natural enzymes due to their catalytic properties and constitute a novel signal transduction strategy in colorimetric and absorption sensors based on the localized surface plasmon resonance (LSPR) band. Other potential AOxC sensors include quantum dots (QDs, <10 nm), which are particularly useful for the sensitive detection of specific antioxidants (e.g., GSH, AA and baicalein) and can achieve very good limits of detection (LOD). QDs and metallic nanoparticles (MNPs) operate on different principles to evaluate AOxC. MNPs rely on optical changes resulting from LSPR, which are monitored as changes in color or absorbance during synthesis, growth or aggregation. QDs, on the other hand, primarily utilize changes in fluorescence. This review aims to demonstrate that, thanks to its simplicity, speed, small sample volumes and relatively inexpensive instrumentation, nanoparticle-based AOxC assessment is a useful alternative to classical approaches and can be tailored to the desired aim and analytes. Full article

Harmful substances in food and agricultural environments pose significant risks to human health, necessitating the development of sensitive detection technologies. Electrochemical sensors are ideal for rapid monitoring because of their low cost, high efficiency, and portability. Recently developed laser-induced graphene (LIG)-based electrochemical sensors have demonstrated exceptional potential owing to the unique structural properties and outstanding electrochemical performance of LIG. In this review, the key factors influencing the LIG material characteristics during fabrication are discussed. Then, LIG-based electrochemical sensors are systematically categorized as pristine LIG and nanomaterial-functionalized, biomaterial-modified, and polymer-functionalized electrochemical sensors, and their application in the detection of functional components, additives, and agrochemicals in food products, and the detection of environmental pollutants, is comprehensively analyzed. Finally, the current challenges and the directions for future development are discussed. Full article

Autonomous vehicle (AV) accidents introduce uncertainty in liability attribution, as responsibility is divided between humans and automated systems. The 2018 Arizona crash highlighted growing societal concerns about accountability. To address these issues, prior studies proposed investigation processes considering perception sensors, driving control systems, communication infrastructure, and cybersecurity. However, conducting such investigations requires integrating large-scale data from multiple sources, including vehicle sensors, onboard recorders, V2X communications, and road infrastructure. Raw data often lack descriptive information, limiting their use in real investigations. This study establishes a structured mapping framework linking investigation procedures, responsible entities, items, and data across accident phases. With this backdrop, an autonomous driving–specific metadata schema extending DCAT was designed, comprising 10 Classes and 76 Properties. To demonstrate its applicability, a prototype data catalog user interface (UI) was conceptualized with data discovery and visualization examples. The proposed schema strengthens accountability and interoperability by explicitly aligning responsibilities and data relationships. It enables precise event localization and effective linkage of heterogeneous data. Future work will refine the schema by incorporating DSSAD, V2X, and security log data, and develop a user-tested UI prototype as a practical support tool for AV accident investigation. Full article

This paper presents the development and validation of an IoT-enabled temperature-sensing device for real-time monitoring of the thermal insulation properties of glass windows. The system integrates contact and non-contact temperature sensors into a compact PCB platform equipped with WiFi connectivity, enabling seamless integration into smart home and building management frameworks. By continuously assessing window insulation performance, the device addresses the challenge of energy loss in buildings, where glazing efficiency often degrades over time. The collected data can be transmitted to cloud-based services or local IoT infrastructures, allowing for advanced analytics, remote access, and adaptive control of heating, ventilation, and air-conditioning (HVAC) systems. Experimental results demonstrate the accuracy and reliability of the proposed system, confirming its potential to contribute to energy conservation and sustainable living practices. Beyond energy efficiency, the device provides a scalable approach to environmental monitoring within the broader future internet ecosystem, supporting the evolution of intelligent, connected, and human-centered living environments. Full article

In this article, the authors present the impact of laser treatment on the structure of magnetic composite microfibers. Changes occurring on the surface can have a significant impact on the conductive properties of functional materials produced on a micro- and nanoscale. The fibers presented are functional materials that gain technical applications when combined with other materials. In this case, we refer to the concept of textronics, i.e., the combination of textiles with electronics to create various types of flexible sensors. The authors performed microscopic analysis to observe the changes occurring in the materials. For this purpose, scanning electron microscope and atomic force microscope were used. Full article

Rydberg atoms are neutral atoms excited to high principal quantum number states, which endows them with exaggerated properties such as large electric dipole moments, long lifetimes, and extreme sensitivity to external electromagnetic fields. These characteristics form the foundation of Rydberg atom-based sensors, an emerging class of quantum devices capable of optically detecting electric fields across frequencies from DC to the terahertz regime. Rydberg-based electrometry operates through both Autler–Townes (AT) splitting of resonant Rydberg transitions and Stark-shift measurements for high-frequency or far-detuned fields, enabling broadband field sensing from DC to the THz regime. Using ladder-type electromagnetically induced transparency (EIT) and AT splitting, these sensors enable non-invasive, SI-traceable measurements of field amplitude, frequency, phase, and polarization. Recent developments have demonstrated broadband electric field probes, voltage calibration standards, and compact RF receivers based on thermal vapor cells and integrated photonic architectures. Furthermore, innovations in multi-photon EIT, superheterodyne readout, and multi wave mixing have expanded the dynamic range and bandwidth of Rydberg-based electrometry. Despite challenges related to environmental perturbations, linewidth broadening, and laser stabilization, ongoing advances in atomic control, hybrid photonic integration, and EIT-based readout promise scalable, chip-compatible sensors. This review summarizes the physical principles, experimental progress, and emerging applications of Rydberg atom-based sensing, emphasizing their potential for next generation quantum metrology, wireless communication, and precision field mapping. Full article

The use of satellite-based remote sensing imagery for water quality monitoring of inland and coastal waters has become widespread over the last few decades, with the expansion of, and investment in, operational Earth-observing missions. Satellite-based sensors are uniquely suited to provide synoptic, system-wide water quality parameter estimates that supplement traditional field-based sampling methods. The remote sensing of water quality parameter estimates is particularly valuable in systems with high temporal and spatial variability, as well as in areas that are difficult to access, or where agencies lack funding for routine monitoring. However, optically complex inland and coastal waters pose additional challenges for developing robust remote sensing retrieval models for optical properties and water quality parameters. One of the biggest challenges is collecting high quality field measurements that are used to calibrate and validate the retrieval algorithms. Here, we present the current status of satellite missions, field methods that include instruments used and commonly measured parameters, and repositories of historical field data that are relevant to inland and coastal water studies. We then present data requirements for model validation and highlight gaps in validation coverage. Finally, we provide considerations for future field campaigns to improve coordination with remote sensing data collection and ensure that field data is well suited for use in model or algorithm development. Full article

In this work, a flexible, stretchable, tough, highly ionic conductive, and anti-freezing hydrogel based on acrylamide/two-dimensional transition metal carbide (MXene)/montmorillonite (MMT) was precisely designed. In the hydrogel, MXene and MMT acted as both cross-linking agents and conductive fillers, delivering high stretchability (1037%) with a strength of up to approximately 67 kPa and high conductivity. As a result, the usual trade-off between conductivity and mechanical properties of hydrogels could be alleviated to some extent. Therefore, the hydrogel could be used as an electrolyte for supercapacitors (SCs) and strain sensors to monitor physical signals. The hydrogel-based SC exhibited outstanding electrochemical performance over a wide temperature range. Moreover, it could easily withstand various deformations, such as bending, twisting, and compression. The hydrogel also exhibited excellent sensing properties, with a short tensile response time and a high-sensitivity factor (GF = 14.8) in the 0–400% range (0 denotes the original state, where both the strain and stretch are zero as there is no deformation at this point). Due to its high conductivity, the prepared hydrogel could be used as a flexible electrode to replace commercial electrodes and record electromyographic (EMG) signals. This work proposes a novel approach for balancing the conductivity and mechanical strength of hydrogels. Full article

Scandium-modified carbon dots (Sc-oCDs) were synthesized in this work through a solid-phase approach. The prepared Sc-oCDs exhibited excitation-independent emission properties, as well as photostability against pH, ionic strength, and UV irradiation. Their fluorescence quantum yields significantly exceeded those of unmodified counterparts, confirming effective Sc modification. The Sc-oCDs also possessed upconversion fluorescence at 542 nm with 980 nm excitation. Additionally, the as-prepared Sc-oCDs functioned as an effective fluorescent sensor for Cu²⁺, demonstrating selective fluorescence quenching. A linear correlation was observed between the quenching efficiency and Cu²⁺ concentration from 1 to 600 μM, achieving a detection limit of 0.167 μM. Operating via dynamic quenching, this sensing system achieved highly selective and rapid (<1 min) detection of Cu²⁺, enabling sensitive Cu²⁺ monitoring in aqueous samples. Full article

The market for bioactive compounds of natural origin has expanded greatly over the past few years. These compounds can be found as individual supplements or food additives. Due to the importance of this market, incorrect data on their composition can often be found. Therefore, monitoring their concentration is of great importance. Although there are various methods for their selective and sensitive determination, electrochemical sensors represent an important tool in this field. With the development of nanotechnology, additional importance has been given to these sensors. Strictly controlled synthesis procedures can yield nanomaterials with unique morphological properties and significantly improved electrocatalytic capabilities. The integration of two or more nanomaterials in the form of a nanocomposite and/or nanohybrids allows for the synergistic effect of each of the components. Thus, excellent final characteristics are obtained in the field of electrochemical sensors, such as improved sensor stability, selectivity, and lower detection limits. In recent years, various forms of carbon nanomaterials, polymer films, metal and metal oxide nanoparticles (or simply metal/metal oxide nanoparticles), MOFs, porous nanomaterials, MXenes, and others with clearly defined characteristics represent an important step forward in this field. Carefully prepared, these materials achieve strong interactions with selected analytes, which results in significant progress in analytical methods for monitoring biologically active compounds. Therefore, this review summarizes the latest trends in this field, focusing on the method of material preparation, final morphology and electrocatalytic properties, selectivity, and sensitivity. Conclusions and expected future directions in this field are also given in order to improve current analytical performance. Full article

This work presents a systematic experimental investigation of tapered fiber Bragg gratings (tFBGs) fabricated from standard SMF-28 fiber with waist diameters ranging from 30 to 115 µm. The effects of taper geometry on strain and temperature sensitivities were evaluated using UV inscription through two phase masks to ensure reproducibility. The maximum strain sensitivity achieved was 25.38 ± 0.06 pm/N for the 30 µm waist, corresponding to 20.84 ± 0.05 pm/µε—an enhancement of more than 1600% compared to a standard untapered FBG. In contrast, the thermal sensitivity remained nearly constant at ~12.5 pm/°C for all diameters, confirming that the temperature response is governed by the intrinsic thermo-optic and thermal-expansion properties of silica and is not significantly affected by taper geometry. The measured strain sensitivity exhibited a clear inverse-square dependence on the waist diameter, in excellent agreement with a simple axial-stress model. Consistent Bragg responses obtained using different phase-mask pitches further validated the repeatability of both the tapering and inscription processes. These results demonstrate that tapering standard telecom fiber provides a low-cost, scalable, and robust method to significantly enhance FBG strain sensitivity while preserving thermal stability, enabling compact and high-performance sensors for structural and industrial monitoring applications. Full article