Search Results (426)

Synthetic aperture radar (SAR) systems are of paramount importance to remote sensing applications, including Earth observation and environmental monitoring. Accurate calibration of these systems is imperative to ensuring the accuracy and reliability of the acquired data. A central component of the calibration process is the antenna model, which serves as a fundamental reference for characterizing the radiation pattern, gain, and overall performance of SAR systems. The present paper sets out to describe the implementation and validation of a phased-array antenna model for Synthetic Aperture Radar Systems (SARAS) in MATLAB R2024a. The antenna model was developed for utilization in the Spanish Earth observation missions PAZ and PRECURSOR-ECO. The antenna model incorporates a number of functions, which are divided into two primary modules: the first of these is the antenna pattern generation (APG) module, and the second is the antenna excitation generation (AEG) module. The present document focuses on the AEG, the function of which is to generate patterns for all required beams. These patterns are optimized and matched to specific calculated masks using an ad hoc genetic algorithm (GA). In consideration of the aforementioned factors, the AEG module generates a set of complex excitations corresponding to the required beam from different satellite operational beams, based on several radiometrically defined parameters.  Full article

The development of gas sensors with high sensitivity and low operating temperatures is essential for practical applications in environmental monitoring and industrial safety. SnO₂-based gas sensors, despite their widespread use, often suffer from high working temperatures and limited sensitivity to H₂ gas, which presents significant challenges for their performance and application. This study addresses these issues by introducing a novel SnO₂-based sensor featuring a three-dimensional (3D) nanostructure, designed to enhance sensitivity and allow for room-temperature operation. This work lies in the use of a 3D anodic aluminum oxide (AAO) template to deposit SnO₂ nanoparticles through ultrasonic spray pyrolysis, followed by modification with platinum (Pt) nanoparticles to further enhance the sensor’s response. The as-prepared sensors were extensively characterized, and their H₂ sensing performance was evaluated. The results show that the 3D nanostructure provides a uniform and dense distribution of SnO₂ nanoparticles, which significantly improves the sensor’s sensitivity and repeatability, especially in H₂ detection at room temperature. This work demonstrates the potential of utilizing 3D nanostructures to overcome the traditional limitations of SnO₂-based sensors. Full article

Metal–Organic Frameworks (MOFs) have emerged as advanced porous crystalline materials due to their highly ordered structures, ultra-high surface areas, fine-tunable pore sizes, and massive chemical diversity. These features, arising from the coordination between an almost unlimited number of metal ions/clusters and organic linkers, have resulted in significant interest in MOFs for applications in gas storage, catalysis, sensing, energy, and biomedicine. Beyond their stand-alone properties and applications, recent research has increasingly explored the integration of MOFs with other substrates, particularly electrodes, polymeric thin films, and glass surfaces, to create synergistic effects that enhance material performance and broaden application potential. Coating MOFs onto these substrates can yield significant benefits, including, but not limited to, improved sensitivity and selectivity in electrochemical sensors, enhanced mechanical and separation properties in membranes, and multifunctional coatings for optical and environmental applications. This review provides a comprehensive and up-to-date summary of recent advances (primarily from the past 3–5 years) in MOF coating techniques, including layer-by-layer assembly, in situ growth, and electrochemical deposition. This is followed by a discussion of the representative applications arising from MOF-substrate coating and an outline of key challenges and future directions in this rapidly evolving field. This article aims to serve as a focused reference point for researchers interested in both fundamental strategies and applied developments in MOF surface coatings. Full article

The movement towards low-emission and sustainable building practices has driven increased use of natural, carbon-based materials such as wood. While these materials offer significant environmental advantages, their inherent flammability introduces new challenges for timber building safety. Despite advancements in fire protection standards and building regulations, the risk of fire incidents—whether from technical failure, human error, or intentional acts—remains. The rapid detection of fire onset is crucial for safeguarding human life, animal welfare, and valuable assets. This study investigates the potential of monitoring fire precursor gases emitted inside building structures during pre-ignition and early combustion stages. The research also examines the sensitivity and effectiveness of commercial smoke detectors compared with custom sensor arrays in detecting these emissions. A representative structural sample was constructed and subjected to a controlled fire scenario in a laboratory setting, providing insights into the integration of gas sensing technologies for enhanced fire resilience in sustainable building systems. Full article

Geological storage is an integral element of the green energy transition. Geological formations, such as aquifers, depleted reservoirs, and hard rock caverns, are used mainly for the storage of hydrocarbons, carbon dioxide and increasingly hydrogen. However, potential adverse effects such as ground movements, leakage, seismic activity, and environmental pollution are observed. Existing research focuses on monitoring subsurface elements of the storage, while on the surface it is limited to ground movement observations. The review was carried out based on 191 research contributions related to geological storage. It emphasizes the importance of monitoring underground gas storage (UGS) sites and their surroundings to ensure sustainable and safe operation. It details surface monitoring methods, distinguishing geodetic surveys and remote sensing techniques. Remote sensing, including active methods such as InSAR and LiDAR, and passive methods of multispectral and hyperspectral imaging, provide valuable spatiotemporal information on UGS sites on a large scale. The review covers modelling and prediction methods used to analyze the environmental impacts of UGS, with data-driven models employing geostatistical tools and machine learning algorithms. The limited number of contributions treating geological storage sites holistically opens perspectives for the development of complex approaches capable of monitoring and modelling its environmental impacts. Full article

Efficient detection of toxic and flammable vapors remains a major technological challenge, especially for environmental and industrial applications. This paper reports on the fabrication technology and gas-sensing properties of nanostructured Ga₂O₃/GaS_0.98Se_0.02. The β-Ga₂O₃ nanowires/nanoribbons with inclusions of Ga₂S₃ and Ga₂Se₃ microcrystallites were obtained by thermal treatment of GaS_0.98Se_0.02 slabs in air enriched with water vapors. The microstructure, crystalline quality, and elemental composition of the obtained samples were investigated using electron microscopy, X-ray diffraction, and Raman spectroscopy. The obtained structures show promising results as active elements in gas sensor applications. Vapors of methanol (CH₃OH), ethanol (C₂H₅OH), and acetone (CH₃-CO-CH₃) were successfully detected using the nanostructured samples. The electrical signal for gas detection was enhanced under UV light irradiation. The saturation time of the sensor depends on the intensity of the UV radiation beam. Full article

Volatile organic compounds (VOCs) are presently posing a rather considerable threat to both human health and environmental sustainability. Among these, n-butanol is commonly identified as bringing potential hazards to environmental integrity and individual health. This study presents the creation of a highly sensitive n-butanol gas sensor utilizing cobalt-doped zinc oxide (ZnO) derived from a metal–organic framework (MOF). A series of x-Co/MOF-ZnO (x = 1, 3, 5, 7 wt%) nanomaterials with varying Co ratios were generated using the homogeneous co-precipitation method and assessed for their gas-sensing performances under a low operating temperature (191 °C) and UV excitation (220 mW/cm²). These findings demonstrated that the 5-Co/MOF-ZnO sensor presented the highest oxygen vacancy (O_v) concentration and the largest specific surface area (SSA), representing the optimal reactivity, selectivity, and durability for n-butanol detection. Regarding the sensor’s response to 100 ppm n-butanol under UV excitation, it achieved a value of 1259.06, 9.80 times greater than that of pure MOF-ZnO (128.56) and 2.07 times higher than that in darkness (608.38). Additionally, under UV illumination, the sensor achieved a rapid response time (11 s) and recovery rate (23 s). As a strategy to transform the functionality of ZnO-based sensors for n-butanol gas detection, this study also investigated potential possible redox reactions occurring during the detection process. Full article

Ammonia, as a toxic and corrosive gas, is widely present in industrial emissions, agricultural activities, and disease biomarkers. Detecting ammonia is of vital importance to environmental safety and human health. Sensors based on MXene have become an effective means for detecting ammonia gas due to their unique hierarchical structure, adjustable surface chemical properties, and excellent electrical conductivity. This study reviews the latest progress in the use of MXene and its composites for the low-temperature detection of ammonia gas. The strategies for designing MXene composites, including heterojunction engineering, surface functionalization, and active sites, are introduced, and their roles in improving sensing performance are clarified. These methods have significantly improved the ability to detect ammonia, offering high selectivity, rapid responses, and ultra-low detection limits within the low-temperature range. Successful applications in fields such as industrial safety, food quality monitoring, medical diagnosis, and agricultural management have demonstrated the multi-functionality of this technology in complex scenarios. The challenges related to the material’s oxidation resistance, humidity interference, and cross-sensitivity are also discussed. This study aims to briefly describe the reasonable design based on MXene sensors, aiming to achieve real-time and energy-saving environmental and health monitoring networks in the future. Full article

Hydrogen sulfide (H₂S) is a highly toxic and corrosive gas generated in numerous industrial and environmental processes; rapid, sensitive detection at low ppm levels is therefore crucial for ensuring occupational safety and protecting public health. This work explores the effect of grafting various loadings of pendant aniline tetramer pendants (PEDA) onto electroactive poly(amic acid) (EPAA) films and evaluates their performance as H₂S gas sensors. Comprehensive characterization including ion trap mass spectrometry (Ion trap MS), Fourier-transform infrared spectroscopy (FTIR), cyclic voltammetry (CV), and four-probe conductivity measurements, confirmed successful PEDA incorporation and revealed enhanced electrical conductivity with increasing PEDA content. Gas sensing tests revealed that EPAA3 (3 wt% PEDA) achieved the best overall performance toward 10 ppm H₂S, producing a 591% response with a rapid 108 s response time. Selectivity studies showed that the response of EPAA3 to H₂S exceeded those for SO₂, NO₂, NH₃, and CO by factors of five to twelve, underscoring its excellent discrimination against common interferents. Repeatability tests over five successive cycles gave a relative standard deviation of just 7.4% for EPAA3, and long-term stability measurements over 16 days in ambient air demonstrated that EPAA3 retained over 80%. These findings establish that PEDA-grafted PAA films combine the processability of poly(amic acid) with the sharp, reversible redox behavior of pendant aniline tetramers, delivering reproducible, selective, and stable H₂S sensing. EPAA3, in particular, represents a balanced composition that maximizes sensitivity and durability, offering a promising platform for practical environmental monitoring and industrial safety applications. Full article

Detecting volatile organic compounds (VOCs) is essential for health, environmental protection, and industrial safety. VOCs contribute to air pollution, pose health risks, and can indicate leaks or contamination in industries. Applications include air quality monitoring, disease diagnosis, and food safety. This paper focuses on polymer-based hybrid sensor arrays (HSAs) utilizing interdigitated electrode (IDE) geometries for VOC detection. Achieving high selectivity and sensitivity in gas sensing remains a challenge, particularly in complex environments. To address this, we propose HSAs as an innovative solution to enhance sensor performance. IDE-based sensors are designed and fabricated using the Polysilicon Multi-User MEMS process (PolyMUMPs). Experimental evaluations are performed by exposing sensors to VOCs under controlled conditions. Traditional multi-sensor arrays (MSAs) achieve 82% prediction accuracy, while virtual sensor arrays (VSAs) leveraging frequency dependence improve performance: PMMA-VSA and PVP-VSA predict compounds with 100% and 98% accuracy, respectively. The proposed HSA, integrating these VSAs, consistently achieves 100% accuracy in compound identification and concentration estimation, surpassing MSA and VSA performance. These findings demonstrate that proposed polymer-based HSAs and VSAs, particularly with advanced IDE geometries, significantly enhance selectivity and sensitivity, advancing e-Nose technology for more accurate and reliable VOC detection across diverse applications. Full article

Blue light is a significant environmental cue influencing plant photomorphogenesis and regulating plant growth and development. The COP9 signaling complex (CSN), a multi-subunit protein complex, plays a pivotal role in regulating photomorphogenesis, with CSN2 being identified as a key subunit essential for the assembly and function of the CSN. This study investigated the role of OsCSN2 in rice under blue-light conditions. Utilizing OsCSN2 knockout (KO) mutant plants and transgenic overexpression (OE) lines for wild-type (WT) and mutated versions of OsCSN2, we observed significant suppression of the overall seedling phenotype under blue light, indicating that OsCSN2 acts as a negative regulator of blue light-mediated morphogenesis. Further analysis revealed that exogenous application of gibberellin (GA₃) and the GA synthesis inhibitor paclobutrazol (PAC) modulated seedling elongation in response to blue light, particularly affecting plant height, coleoptile, and first incomplete leaf length without altering root growth. This suggests that OsCSN2 mediates the inhibitory effects of blue light on aboveground development through the gibberellin signaling pathway. On day 9, the analyses of endogenous GA₃ levels combined with Western blotting (WB) and quantitative real-time PCR (qRT-PCR) revealed that OsCSN2 senses blue light signals through cryptochrome 2 (CRY2), influences the expression of COP1 and BBX14, and highlights its role in the photoreceptive signaling pathway. This regulation ultimately influences the degradation of SLR1 within the GA signaling pathway, affecting rice seedling growth and development. Our findings also highlight the differential roles of OsCSN1 and OsCSN2 within the CSN in modulating rice seedling photomorphogenesis, thereby providing new insights into the intricate regulatory mechanisms governing plant responses to blue light. Full article

Efficient management of groundwater resources is essential for environmental sustainability. This study introduces the development and application of a digital twin (DT) for confined aquifers to optimise water extraction and ensure long-term sustainability. A resilience-based control model was implemented to manage the Morroa Aquifer (Colombia). This model integrated historical, hydrogeological, and climatic data acquired from in-situ sensors and satellite remote sensing. Several heuristic methods were employed to optimise the parameters of the objective function, which focused on managing water extraction in aquifer wells: grid search, genetic algorithms (GA), and particle swarm optimisation (PSO). The results indicated that the PSO algorithm yielded the lowest root mean square error (RMSE), achieving an optimal extraction rate of 8.3 l/s to maintain a target dynamic water level of 58.5 m. Furthermore, the model demonstrated the unsustainability of current extraction rates, even under high-rainfall conditions, highlighting the necessity for revising existing water extraction strategies to safeguard aquifer sustainability. To showcase its practical functionality, a DT prototype was deployed in a well within the Morroa piezometric network (Sucre, Colombia). This prototype utilised an ESP32 microcontroller and various sensors (DS18B20, SKU-SEN0161, SKU-DFR0300, SEN0237-A) to monitor water level, pH, dissolved oxygen, and temperature. The implementation of this DT proved to be a crucial tool for the efficient management of water resources. The proposed methodology provided key information to support decision-making by environmental management entities, thereby optimising monitoring and control processes. Full article

It is a well-known fact that proper nutrition is essential for human beings to live healthy lives. For thousands of years, it has been considered that dates are one of the best nutrient providers. To have better-quality dates and to enhance the shelf life of dates, it is vital to preserve dates in optimal conditions that contribute to food security. Hence, it is crucial to know the shelf life of different types of dates. In current practice, shelf life assessment is typically based on manual visual inspection, which is subjective, error-prone, and requires considerable expertise, making it difficult to scale across large storage facilities. Traditional cold storage systems, whilst being capable of monitoring temperature and humidity, lack the intelligence to detect spoilage or predict shelf life in real-time. In this study, we present a novel IoT-based shelf life estimation system that integrates multichannel gas sensors and a lightweight machine learning model deployed on an edge device. Unlike prior approaches, our system captures the real-time emissions of spoilage-related gases (methane, nitrogen dioxide, and carbon monoxide) along with environmental data to classify the freshness of date fruits. The model achieved a classification accuracy of 91.9% and an AUC of 0.98 and was successfully deployed on an Arduino Nano 33 BLE Sense board. This solution offers a low-cost, scalable, and objective method for real-time shelf life prediction. This significantly improves reliability and reduces postharvest losses in the date supply chain. Full article

Acetone detection is crucial for non-invasive health monitoring and environmental safety, so there is an urgent demand to develop high-performance gas sensors. Here, platinum (Pt)-functionalized layered flower-like nickel ferrite (NiFe₂O₄) sheets were efficiently fabricated via facile hydrothermal synthesis and wet chemical reduction processes. When the Ni/Fe molar ratio is 1:1, the sensing material forms a Ni/NiO/NiFe₂O₄ composite, with performance further optimized by tuning Pt loading. At 1.5% Pt mass fraction, the sensor shows a high acetone response (R_g/R_a = 58.33 at 100 ppm), a 100 ppb detection limit, fast response/recovery times (7/245 s at 100 ppm), and excellent selectivity. The enhancement in performance originates from the synergistic effect of the structure and Pt loading: the layered flower-like morphology facilitates gas diffusion and charge transport, while Pt nanoparticles serve as active sites to lower the activation energy of acetone redox reactions. This work presents a novel strategy for designing high-performance volatile organic compound (VOC) sensors by combining hierarchical nanostructured transition metal ferrites with noble metal modifications. Full article

Hydrogen is gaining prominence as a clean energy vector, yet its extreme flammability demands robust detection solutions for industrial safety. In this study, we present the development and experimental validation of a microwave hydrogen gas sensor based on a patch-type microstrip antenna with a silver sensing element. The device operates at 5.99 GHz and was tested under controlled environmental conditions (humidity: 20 ± 0.4%, temperature: 27 ± 0.2 °C). Hydrogen exposure induces measurable shifts in the antenna’s resonant frequency due to dielectric modulation of the silver layer. The sensor exhibited a linear sensitivity of 3 kHz/ppm in the 310–600 ppm concentration range, with a residual standard deviation of 31.1 kHz and a calculated limit of detection (LOD) of approximately 31 ppm. The reflection coefficient remained below −10 dB throughout, confirming that the antenna maintains functional RF performance during sensing. These results demonstrate the sensor’s dual functionality for gas detection and communication, offering a compact and scalable platform for hydrogen safety monitoring. Full article