Search Results (69)

Owing to their high vertical resolution, remote sensing data from meteorological satellite hyperspectral infrared sounders are well-suited for the identification, monitoring, and early warning of high-impact weather events. The effective utilization of full field-of-view (FOV) observations from satellite infrared sounders in high-impact weather applications remains a major research focus and technical challenge worldwide. This study proposes a generalized variational retrieval framework to estimate full FOV cloud fraction and precipitable water vapor (PWV) from observations of the Geostationary Interferometric Infrared Sounder (GIIRS) onboard the Fengyun-4A (FY-4A) satellite. Based on this method, experiments are performed using high-frequency FY-4A/GIIRS observations during the landfall periods of Typhoon Lekima (2019) and Typhoon Higos (2020). A three-step channel selection strategy based on information entropy is first designed for FY-4A/GIIRS. A constrained generalized variational retrieval method coupled with a cloud cost function is then established. Cloud parameters, including effective cloud fraction and cloud-top pressure, are initially retrieved using the Minimum Residual Method (MRM) and used as initial cloud information. These parameters are iteratively optimized through cost-function minimization, yielding full FOV cloud fields and atmospheric profiles. Full FOV brightness temperature simulations are conducted over cloudy regions to quantitatively evaluate the retrieved cloud fractions, and the derived PWV is further applied to the identification and analysis of hazardous weather events. Experimental results demonstrate that incorporating cloud parameters as auxiliary inputs to the radiative transfer model improves the simulation of FY-4A/GIIRS brightness temperature in cloud-covered areas and reduces brightness temperature biases. Compared with ERA5 Total Column Water Vapour (TCWV) data, the PWV derived from full FOV profiles containing cloud parameter information shows closer agreement and, at certain FOVs, more effectively indicates the occurrence of high-impact weather events. The simplified methodology proposed in this study provides a robust basis for the future assimilation and operational utilization of infrared data over cloud-affected regions in numerical weather prediction models. Full article

Two fluorescent ureido-dihomooxacalix[4]arene derivatives containing naphthyl residues at the lower rim (1 and 2) were studied for the detection of nitroaromatic compounds (NACs) in solution and in vapour phases. Their affinity in solution was determined by UV-Vis absorption, fluorescence and NMR spectroscopy. For NAC vapour sensing, calixarenes were dispersed in a polytetrafluoroethylene (PTFE) matrix. Four new solvated crystals of dihomooxacalix[4]arene 2 were obtained and the solvent’s influence on its structural characteristics was investigated. The solvent-dependent structural variations observed in the crystal structures highlight the intrinsic flexibility of the calixarene framework. Such conformational adaptability, evident in the disruption and reorganization of hydrogen bonding and π–π interactions, is directly relevant to nitroaromatic sensing, where a rapid and reversible host response is crucial for effective detection. Theoretical calculations were also performed to provide further insights on the binding process. The corrected Stern–Volmer constants (K_SV) obtained showed that both receptors present selectivity for TNP and follow the same quenching order (TNP > NT > NB > DNT > TNT > DNB). Factors other than electron density distribution should dominate the quenching extent and therefore the values of the SV constants, which will be greatly overestimated if no correction to the inner filter effect is applied. Detection of NB and NT and vapours by both calixarenes produced a complete, very fast (2 to 5 s), and reversible quenching, indicating the potential use of this porous PTFE–calixarene matrix for the sensing of volatile NACs. Full article

A nanostructured sensing platform was developed by integrating gold-decorated lignin nanoparticles (AuLNPs) into electrospun polylactic acid (PLA) fibre mats. The composite material combines the high surface-to-volume ratio of PLA nanofibres with the chemical functionality of lignin—a polyphenolic biopolymer rich in hydroxyl and aromatic groups—enabling selective interactions with volatile amines through hydrogen bonding and Van der Waals forces. The embedded gold nanoparticles (AuNPs) further enhance the sensor’s electrical conductivity and provide catalytic sites for improved analyte interaction. The sensor exhibited selective adsorption of amine vapours, showing particularly strong affinity for dimethylamine (DMA), with a limit of detection (LOD) of approximately 440 ppb. Relative humidity (RH) was found to significantly influence sensor performance by facilitating amine protonation, thus promoting interaction with the sensing surface. The developed sensor demonstrated excellent selectivity, sensitivity and reproducibility, highlighting its potential for real-time detection of amines in environmental monitoring, industrial safety and healthcare diagnostics. Full article

Manganese dioxide (MnO₂) has drawn attention as a sensitiser to be incorporated in graphene-based chemoresistive sensors thanks to its promising properties. In this regard, a rGO@MnO₂ sensing material was prepared and deposited on two different substrates (silicon and Kapton). The effect of the substrate nature on the morphology and sensing behaviour of the rGO@MnO₂ material was thoroughly analysed and reported. These sensors were exposed to different dilutions of NO₂ ranging from 200 ppb to 1000 ppb under dry and humid conditions (25% RH and 70% RH) at room temperature. rGO@MnO₂ deposited on Kapton showed the highest response of 6.6% towards 1 ppm of NO₂ under dry conditions at RT. Other gases or vapours such as NH₃, CO, ethanol, H₂ and benzene were also tested. FESEM, HRTEM, Raman, XRD and ATR-IR were used to characterise the prepared sensors. The experimental results showed that the incorporation of nanosized MnO₂ in the rGO material enhanced its response towards NO₂. Moreover, this material also showed very good responses toward NH₃ both under dry and humid conditions, with the rGO@MnO₂ sensor on silicon showing the highest response of 18.5% towards 50 ppm of NH₃ under 50% RH at RT. Finally, the synthetised layers showed no cross-responsiveness towards other toxic gases. Full article

A styrene-butadiene-styrene co-polymer matrix nanocomposite filled with graphene nanoplatelets was studied to prepare chemiresistive volatile organic compounds (VOCs) room temperature sensors with considerable response and selectivity. Nanofiller concentration was estimated from the electrical conductivity percolation behaviour of the nanocomposite. Fabricated sensors provided selective relative responses to representative VOCs differing by orders of magnitude. Maximum observed average relative responses upon exposure to saturated vapours of the tested VOCs were ca. 23% for ethanol, 1600% for acetone, and the giant values were 9 × 10⁶% for n-heptane and 10 × 10⁶% for toluene. The insensitivity of the sensor to the direct saturated water vapour exposure was verified. Although high humidity decreases the sensor’s response, it paradoxically enhances the resolution between hydrocarbons and polar organics. The non-trivial sensing mechanism is explained using the Hansen solubility parameters (HSP), enabling a rational design of new sensors; thus, the HSP-based class of sensors is outlined. Full article

In this work, we report on the synthesis of four morphologies of ZnO, namely, nanoparticles, nanorods, nanosheets, and nanoflowers, from a single precursor Zn(CH₃COO)₂·2H₂O under different reaction conditions. The synthesised nanostructured materials were characterised using powder X-ray diffraction (XRD), Fourier transform infrared (FTIR) and Raman spectroscopy, UV–Vis, XPS analysis, transmission electron microscopy (TEM), scanning electron microscopy (SEM), and nitrogen sorption at 77 K. The XRD, FTIR, and Raman analyses did not reveal any significant differences among the nanostructures, but differences in the electronic properties were noted among the different morphologies. The TEM and SEM analyses confirmed the four different morphologies of the ZnO nanostructures. The textural characteristics revealed that the specific surface areas were different, being 1.3, 6.7, 12.7, and 26.8 m²/g for the nanoflowers, nanoparticles, nanorods, and nanosheets, respectively. The ZnO nanostructures were then mixed with carbon nanoparticles (CNPs) and cellulose acetate (CA) to make nanocomposites that were then used as sensing materials in solid-state sensors to detect methanol, ethanol, and isopropanol vapour at room temperature. The sensors’ responses were recorded in relative resistance. When detecting methanol, 6 out of 12 sensors were responsive, and the most sensitive sensor was the composite with a mass ratio of 1:1:1 of ZnO nanorods:CNPs:CA with a sensitivity of 0.7740 Ω ppm⁻¹. Regarding the detection of ethanol vapour, 9 of the 12 sensors were responsive, and the 3:1:1 mass ratio with ZnO nanoparticles was the most sensitive at 4.3204 Ω ppm⁻¹. Meanwhile, with isopropanol, 5 out of the 12 sensors were active and, with a sensitivity of 3.4539 Ω ppm⁻¹, the ZnO nanoparticles in a 3:1:1 mass ratio were the most sensitive. Overall, the response of the sensors depended on the morphology of the nanostructured ZnO materials, the mass ratio of the sensing materials in the composites, and the type of analyte. The sensing mechanism was governed by the surface reaction on the sensing materials rather than pores hindering the analyte molecules from reaching the active site, since the pore size is larger than the kinetic diameter of the analyte molecules. Generally, the sensors responded well to the ethanol analyte, rather than methanol and isopropanol. This is due to ethanol molecules displaying a more enhanced electron-donating ability. Full article

Plaster is a construction material widely used for the production of prefabricated parts in building construction due to its high capacity for hygrothermal regulation, its good mechanical performance, and its fireproof nature, among other factors. Its historical use has been linked to ornamental elements, although more recent research is oriented towards the industrialisation of plaster composites and the design of prefabricated parts for false ceilings and interior partitions. In this work, the behaviour against water of four new plaster-based composite materials is studied, using additions of two types of super absorbent polymers (sodium polyacrylate and potassium polyacrylate) and a lightening material (vermiculite) in their manufacturing process. In addition, the transmission of water vapour through the samples was studied together with the water absorption capacity of the samples in order to check the suitability of the use of plaster-based materials exposed to these environments. The results of this study show that composites with the addition of super absorbent polymers as well as vermiculite significantly improve their water performance compared to traditional materials up to 7.3% water absorption with a minimal (13%) reduction in mechanical strength compared to current materials with similar additions. In this sense, a plaster material is obtained with wide possibilities of application in the construction sector that favours the development of sustainable and quality buildings, in line with Goal 9 for Sustainable Development included in the 2030 Agenda. Full article

Sensor arrays are currently attracting the interest of researchers due to their potential of overcoming the limitations of single sensors regarding selectivity, required by specific applications. Among the materials used to develop sensor arrays, graphene has not been so far extensively exploited, despite its remarkable sensing capability. Here we present the development of a graphene-based sensor array prepared by dropcasting nanostructure and nanocomposite graphene solution on interdigitated substrates, with the aim to investigate the capability of the array to discriminate several gases related to specific applications, including environmental monitoring, food quality tracking, and breathomics. This goal is achieved in two steps: at first the sensing properties of the array have been assessed through ammonia exposures, drawing the calibration curves, estimating the limit of detection, which has been found in the ppb range for all sensors, and investigating stability and sensitivity; then, after performing exposures to acetone, ethanol, 2-propanol, sodium hypochlorite, and water vapour, chemometric tools have been exploited to investigate the discrimination capability of the array, including principal component analysis (PCA), linear discriminant analysis (LDA), and Mahalanobis distance. PCA shows that the array was able to discriminate all the tested gases with an explained variance around 95%, while with an LDA approach the array can be trained to accurately recognize unknown gas contribution, with an accuracy higher than 94%. Full article

The Loess Plateau is one of the three most severely affected geological disaster areas in China. Water sensitivity is the most significant feature of the loess. Under the action of continuous heavy rainfall, rainwater infiltrates the loess, resulting in a rapid increase in soil saturation and changes in soil moisture. This affects the shear strength of the soil and induces shallow loess landslides. Therefore, it is significant to our country’s disaster prevention and mitigation efforts to effectively monitor the deformation and inducement of such landslides. At present, the global navigation satellite system (GNSS) is widely used in the field of landslide disaster monitoring as a technical means to directly obtain real-time three-dimensional vector deformation of the surface. At the same time, GNSS can also provide a steady stream of L-band microwave signals to obtain surface environmental information, such as soil moisture around the station. In past landslide disaster monitoring research, GNSS was only used to provide three-dimensional deformation information, and its ability to provide environmental information around the station was almost completely ignored. This study proposes a ground-based GNSS remote sensing comprehensive monitoring system integrating “three-dimensional deformation and soil moisture content” combined with a rainfall-type shallow loess landslide event in Linxia City. The ability of ground-based GNSS to comprehensively monitor shallow loess landslide disasters was analysed. Experiments show that GNSS can provide high-precision deformation time series characteristics and monitor the changes in soil moisture content around the station at the same time; the two have a certain response relationship, which can comprehensively evaluate the stability of shallow loess landslides. As heavy rainfall is a key factor affecting the change in soil water content, this study adds the atmospheric water vapour content calculated by ground-based GNSS refraction remote sensing in the discussion chapter and analyses the relationship between precipitable water vapour and rainfall in this area to give full play to ground-based GNSS remote sensing. In the role of landslide disaster monitoring, we hope to build a more comprehensive ground-based GNSS remote sensing monitoring system to better serve the monitoring of landslide disasters. Full article

The Central Andes in northwestern Argentina are characterized by steep topographic and climatic gradients. The humid foreland areas at 1 km asl elevation rapidly rise to over 5 km in the eastern Cordillera, and they form an orographic rainfall barrier on the eastern windward side. This topographic setting combined with seasonal moisture transport through the South American monsoon system leads to intense rainstorms with cascading effects such as landsliding and flooding. In order to better quantify the dynamics of water vapour transport, we use high-temporal-resolution global navigation satellite system (GNSS) remote sensing techniques. We are particularly interested in better understanding the dynamics of high-magnitude storms with high water vapour amounts that have destructive effects on human infrastructure. We used an existing GNSS station network with 12 years of time series data, and we installed two new ground stations along the climatic gradient and collected GNSS time series data for three years. For several stations we calculated the GNSS signal delay gradient to determine water vapour transport direction. Our statistical analysis combines in situ rainfall measurements and ERA5 reanalysis data to reveal the water vapour transport mechanism for the study area. The results show a strong relationship between altitude and the water vapour content, as well as between the transportation pathways and the topography. Full article

The selective sensing of gaseous target molecules is a challenge to analytical chemistry. Selectivity may be achieved in liquids by several different methods, but many of these are not suitable for gas-phase analysis. In this review, we will focus on molecular imprinting and its application in selective binding of volatile organic compounds and atmospheric pollutants in the gas phase. The vast majority of indexed publications describing molecularly imprinted polymers for gas sensors and vapour monitors have been analysed and categorised. Specific attention was then given to sensitivity, selectivity, and the challenges of imprinting these small volatile compounds. A distinction was made between porogen (solvent) imprinting and template imprinting for the discussion of different synthetic techniques, and the suitability of each to different applications. We conclude that porogen imprinting, synthesis in an excess of template, has great potential in gas capture technology and possibly in tandem with more typical template imprinting, but that the latter generally remains preferable for selective and sensitive detection of gaseous molecules. More generally, it is concluded that gas-phase applications of MIPs are an established science, capable of great selectivity and parts-per-trillion sensitivity. Improvements in the fields are likely to emerge by deviating from standards developed for MIP in liquids, but original methodologies generating exceptional results are already present in the literature. Full article

Intelligent cementitious materials integrated with carbon nanofibers (CNFs) have the potential to be used as sensors in structural health monitoring (SHM). The difficulty in dispersing CNFs in cement-based matrices, however, limits the sensitivity to deformation (gauge factor) and strength. Here, we synthesise CNF by chemical vapour deposition on the surface of calcium oxide (CaO) and, for the first time, investigate this amphiphilic carbon nanomaterial for self-sensing in mortar. SEM, TEM, TGA, Raman and VSM were used to characterise the produced CNF@CaO. In addition, the electrical resistivity of the mortar, containing different concentrations of CNF with and without CaO, was measured using the four-point probe method. Furthermore, the piezoresistive response of the composite was quantified by means of compressive loading. The synthesised CNF was 5–10 μm long with an average diameter of ~160 nm, containing magnetic nanoparticles inside. Thermal decomposition of the CNF@CaO compound indicated that 26% of the material was composed of CNF; after CaO removal, 84% of the material was composed of CNF. The electrical resistivity of the material drops sharply at concentrations of 2% by weight of CNF and this drop is even more pronounced for samples with 1.2% by weight of washed CaO. This indicates a better dispersion of the material when the CaO is removed. The sensitivity to deformation of the sample with 1.2% by weight of CNF@CaO was quantified as a gauge factor (GF) of 1552, while all other samples showed a GF below 100. Its FCR amplitude can vary inversely up to 8% by means of cyclic compressive loading. The method proposed in this study provides versatility for the fabrication of carbon nanofibers on a tailored substrate to promote self-sensing in cementitious materials. Full article

Anthropogenic toxic vapour and gases are a worldwide threat for human health and to the environment. Therefore, it is crucial to develop highly sensitive devices that guarantee their rapid detection. Here, we prepared redox-switchable colloids by the in-situ reduction of 2,3,5-triphenyl-2H-tetrazolium (TTC) into triphenyl formazan (TF) stabilised with Pluronic F127 in aqueous media. The colloids were readily embedded in polydimethylsiloxane (PDMS) to produce a selective colour-switchable membrane for nitrogen dioxide (NO₂) detection. We found that the TTC reduction resulted in the production of red-coloured colloids with zeta potential between −1 to 3 mV and hydrodynamic diameters between 114 to 305 nm as hydrophobic dispersion in aqueous media stabilised by Pluronic at different molar concentrations. Moreover, the embedded colloids rendered highly homogenous red colour gas-permeable PDMS elastomeric membrane. Once exposed to NO₂, the membrane began to bleach after 30 s due to the oxidation of the embedded TF and undergo a complete decolouration after 180 s. Such features allowed the membrane integration in a low-cost sensing device that showed a high sensitivity and low detection limit to NO₂. Full article

Thyroid autoimmunity in Graves’ disease (GD) is accompanied by Graves’ orbitopathy (GO) in 40% of the cases. Orbital fibroblasts (OF) play a key role in the pathogenesis and cigarette smoking is a known deteriorating factor. Alongside conventional cigarettes (CC) new alternatives became available for smokers, including heated tobacco products (HTP) and E-cigarettes (ECIG). We aimed to study the cellular effects of smoke extracts (SE) in orbital fibroblasts. Primary OF cultures from GO and NON-GO orbits were exposed to different concentrations of SE (1%, 50%) and the changes were followed using Real Time Cell Electronic Sensing (RT-CES). Untreated GO and NON-GO cells had different maximum cell index (CI) values of 3.3 and 2.79 respectively (p < 0.0001). CC, HTP and ECIG treated NON-GO fibroblasts exhibited peak CIs of 2.62, 3.32 and 3.41 while treated GO cells’ CIs were higher, 5.38, 6.25 and 6.33, respectively (p < 0.0001). The metabolic activity (MTT) decreased (p < 0.001) and hyaluronan production doubled (p < 0.02) after 50% of CC SE treatment in all cell cultures. GO fibroblasts were more sensitive to low concentration SE then NON-GO fibroblasts (p < 0.0001). The studied SEs exerted different effects. RT-CES is a sensitive technique to detect the effects of very low concentration of SE on fibroblasts. Full article