Search Results (1,022)

In the present study, the structural, electronic, optical, adsorption and sensitivity properties of BN and AlN nanoribbons towards nitrogen dioxide (NO₂) gas molecules were investigated via density functional theory (DFT), DFT-D3 dispersion correction and time-dependent DFT (TD-DFT). Six different NO₂ adsorption configurations were taken into account to evaluate the interaction between NO₂ molecules and the BN and AlN nanoribbon surface. Three adsorption configurations were considered for each nanoribbon, resulting in six adsorption configurations in total. The adsorption energy calculations indicated stronger chemosorption on the AlN nanoribbon surface than the BN nanoribbon surface, while BN nanoribbons gave a stronger optical response than AlN. The charge transfer (CT) results conclude that the NO₂ gas molecule acts like an electron donor, while it behaves like an electron acceptor on the AlN nanoribbon surface. The sensitivity (S) values confirm that the BN nanoribbon exhibits high sensing performance across all adsorption configurations, while the AlN nanoribbon shows the highest sensitivity for the H3 configuration. Furthermore, due to the chemisorption nature between BN and AlN nanoribbons’ surfaces, the band gap energy becomes narrower after interaction. For example, the band gap of the BN nanoribbons decreases from 6.2 eV to around 0.5 eV after NO₂ adsorption, showing electron excitation and improving the electron sensing performance. Overall, the evaluated results indicate that AlN nanoribbons are promising candidates for adsorption-based NO₂ gas sensors, while BN nanoribbons show superior potential for optical NO₂ sensing applications. Full article

Triethylamine (TEA) is a common industrial contaminant and an important indicator of seafood spoilage. Therefore, determination of rapid and selective TEA is of great significance. This review article critically compares tungsten oxide (WO₃)- and molybdenum oxide (MoO₃)-based chemiresistive sensors by relating their crystal structure, surface chemistry, defect states, morphology, and interfacial electronic properties to TEA-sensing performance. Pristine WO₃- and MoO₃-based sensors generally operate at approximately 133–325 °C and provide sub-ppm detection, whereas doping, noble-metal sensitization, heterojunction formation, and light activation can reduce the operating temperature to 100–180 °C and extend detection into the low-ppb range. WO₃-based sensors have exhibited a response of 1100 to 20 ppm TEA at 160 °C, with an estimated detection limit of 5 ppb, whereas modified MoO₃-based sensors have also achieved decent detection limit of 1.7 ppb. WO₃ is particularly responsive to phase, facet, work-function, and catalytic-interface engineering, whereas α-MoO₃ benefits from its anisotropic structure, variable Mo valence, and favorable Lewis acid–base interactions with amines. Noble metals enhance gas sensing through catalytic and electronic sensitization, dopants regulate adsorption and defect chemistry, and n-n or p-n heterojunctions amplify resistance changes through depletion-layer modulation. Despite considerable advances in sensitivity, humidity interference, high power consumption, slow recovery, baseline drift, and limited long term stability remain unresolved. Future advances may require standardized performance assessment, operando mechanistic studies, humidity-resistant low-power devices, and validation under realistic seafood-storage and industrial conditions. Full article

Herein, nitrogen-doped wrinkled multilayer graphene sheets (N-doped graphene) are synthesized via a facile solvothermal route followed by NH₃ atmosphere annealing at different temperatures. Systematic characterization by SEM, XRD, FTIR, Raman, and XPS confirms the successful incorporation of nitrogen with tunable configurations, i.e., pyridinic N, pyrrolic N, and graphitic N, whose relative fractions are strongly dependent on annealing temperature. Room-temperature gas sensing tests toward NH₃ reveal that the G-600 (N-doped graphene annealed at 600 °C) sensor exhibits the highest response (4.76 toward 300 ppm NH₃), about 7.8 times that of G-400 (a counterpart sample thermally treated at 400 °C), along with excellent selectivity, reproducibility, and stability. Density functional theory (DFT) calculations demonstrate that pyridinic N provides the strongest adsorption affinity for NH₃ and the largest charge transfer, whereas graphitic N ensures superior electrical conductivity. The optimal performance of G-600 arises from a synergistic effect between abundant pyridinic N active sites for enhanced NH₃ adsorption and sufficient graphitic N for efficient charge transport. This work not only elucidates the mechanism of nitrogen-configuration-governed sensing behavior but also offers a rational strategy for designing high-performance room-temperature NH₃ sensors based on N-doped graphene. Full article

Perovskite materials have emerged as promising candidates for gas sensing owing to their tunable structures, adjustable compositions, rich defect chemistry, and efficient charge transport properties. These characteristics enable the effective regulation of active sites, oxygen vacancies, heterointerfaces, and band alignment, thereby enhancing gas adsorption and sensing performance. This review summarizes recent advances in perovskite-based gas sensors, focusing on synthesis and fabrication strategies, structural engineering, sensing mechanisms, theoretical simulations, and intelligent sensing applications. The effects of doping, defect engineering, morphology control, and heterojunction construction on sensitivity, selectivity, response and recovery behavior, humidity tolerance, and stability are discussed. In addition, the roles of first-principles calculations and artificial intelligence in elucidating sensing mechanisms, identifying gases, predicting concentrations, and suppressing interference are highlighted. Finally, the remaining challenges and future perspectives are discussed to guide the development of stable, low-power, selective, and intelligent perovskite-based sensing systems. Full article

The unique contributions of 2D Ti₃C₂ MXenes surface, electrical, and chemical features play a crucial role in determining toxic and flammable gas-sensing behavior. Specifically, its high electrical conductivity (metallic nature), layered nanosheet structure (nanosheets), and surface termination groups (–O, –F, and –OH) collectively contribute to excellent hydrogen (H₂) and ammonia (NH₃) gas-sensing behavior. This review systematically explores the impact of pristine and modified Ti₃C₂ MXene, including its interfaces with various metals and metal oxides for enhancing H₂ and NH₃ detection. Furthermore, the significance of room temperature operation and flexible gas sensing mechanisms is explored. Notably, integration of Ti₃C₂ MXene and sulfur nanosheets demonstrates rapid response and recovery times with detection limits at ppt level. Ti₃C₂ MXene-based interfaces also exhibit excellent long-term stability under various relative humidity conditions. The selective surface termination groups (–OH and –O) facilitate the formation of hydrogen bonds with NH₃ molecules for enhancing gas adsorption and sensing selectivity. In addition, the expansion of the interlayer spacing plays a vital role in improving the gas-sensing performance. Partial oxidation of Ti₃C₂ MXene into TiO₂ increases the interlayer distance, promoting faster diffusion of gas molecules and quicker sensor response. Overall, the intrinsic properties of Ti₃C₂ MXene and its composites significantly achieve high-performance room-temperature H₂ and NH₃ gas-sensing performance. Full article

Metal oxide nanoparticles have been the subject of intense research interest because of their remarkable physicochemical properties, such as their high surface area, particle size tunability, outstanding chemical stability, optical activity, catalytic efficiency, and antimicrobial behavior. These properties make them very useful in environmental, biomedical, energy, sensing, agricultural and industrial applications. The chosen synthesis method is important in controlling the morphology, crystallinity, surface charge, band gap and overall performance of metal oxide nanoparticles. They have been prepared using various physical, chemical and biological means, such as sol–gel, co-precipitation, hydro/solvothermal, microwave-assisted, sonochemical, combustion and green synthesis. Of these, green synthesis is gaining more interest as it employs plant extracts, microorganisms, and other biological materials as reducing agents, stabilizing and capping agents that make the process more eco-friendly and cost-effective. Recent advancements in the synthesis and application of metal oxide nanoparticles are discussed. There is an emphasis on the major synthesis routes, the main factors that influence the formation of nanoparticles, the characterization techniques used, and the structure–property relationships uncovered. A special focus is given to the influence of synthesis parameters, such as the type of precursor and the pH, temperature, reaction time, solvents and capping agents, on the properties of nanoparticles. In addition, the uses of metal oxide nanoparticles in photocatalysis, wastewater treatment, antimicrobial activity, drug delivery, biosensing, energy storage, gas sensing, and agriculture are also included. Finally, present challenges, toxicity issues, the problems of large-scale production, and future research directions are discussed to support the practical and sustainable uses of metal oxide nanoparticles. Full article

Near-field beam shaping for phased-array antennas operating in the Fresnel region is a challenging non-convex electromagnetic synthesis problem, requiring coherent control of the radiated fields while accounting for the distinct positions, radiation patterns, and polarization states of individual array elements. This paper presents a physics-informed optimization framework for near-field beam shaping based on a unified vector formulation that enables the direct coherent summation of the electromagnetic fields radiated by array elements despite their distinct local spherical coordinate systems. Unlike conventional formulations that rely on repeated transformations between local spherical and global Cartesian coordinate systems, the proposed representation preserves the physical polarization properties of the electromagnetic field while providing a rigorous framework for near-field beam synthesis. To optimize the electromagnetic energy distribution over finite target surfaces rather than a single focal point, an analytical near-field point-focusing solution is integrated into the optimization process through a physically informed initialization strategy. The resulting non-convex optimization problem is solved using a genetic algorithm (GA) to determine the element phase distribution that maximizes electromagnetic energy within the prescribed target region while minimizing undesired field leakage. The proposed methodology is validated through full-wave electromagnetic simulations and extensive experimental measurements using a dedicated phased-array platform, including the design, fabrication, characterization, and calibration of the antenna array and phase-control network. The results demonstrate flexible near-field beam shaping and controlled energy focusing over finite target regions. The proposed framework is applicable to biomedical radar sensing, near-field synthetic aperture radar (SAR) illumination, wireless power transfer (WPT), high-power microwave (HPM) systems, and near-field millimeter-wave communications. Full article

Rapid room-temperature identification of gases and volatile organic compounds remains challenging for compact sensing platforms, particularly when chemically related analytes must be discriminated using accessible sensing materials. In this work, we evaluate whether magneto-optical surface plasmon resonance (MOSPR), combined with multi-spot sensing and conventional SPR readout from the same chip, can provide complementary response features for improved gas/VOC discrimination. The sensing spots are made from accessible chemicals and nanoparticles with plasmonic and magnetic properties. The sensor chip consists of a multilayer structure of metallic materials with both plasmonic and magnetic properties featuring enhanced sensitivity and stability. Measurements are made using a custom-built MOSPR instrument at relevant analyte concentrations. Analyte-specific sensor channels were selected for concentration-dependent calibration while the complete multivariate data were first explored using principal component analysis for supervised analyte classification. The combined 16-feature MOSPR/SPR model achieved an overall accuracy of 88.3% and a balanced accuracy of 87.6% under leave-one-concentration-block-out cross-validation compared with 66.2% and 65.7%, respectively, for the SPR measurement alone. These results show that MOSPR provides response information that encompasses and extends that obtained from conventional SPR measurements, thereby improving analyte discrimination. The proposed approach may provide a basis for future environmental monitoring and industrial process control, including real-time monitoring of harmful gaseous emissions pending further validation under application-specific conditions. Full article

Natural and human-induced disasters can cause significant loss of life and property, particularly at the building level, highlighting the need for effective early detection, real-time monitoring, and rapid post-disaster response. Current disaster management approaches largely rely on citizen reports and manual observations, which may lead to delays and inefficient resource allocation, especially in large-scale events. This study proposes a secure, modular, multi-layer disaster monitoring and decision-support architecture that integrates sensor-based building-edge monitoring units deployed at both the building and apartment levels with a central emergency monitoring system. The architecture comprises three main layers: edge sensing, secure cellular communication, and central decision-making. Building-edge monitoring units collect data related to structural motion and inclination indicators, fire, flooding, and gas leaks, perform preliminary processing, and transmit aggregated data securely to the central system. Communication security is ensured through a certificate-based authentication mechanism supported by a dedicated certificate authority, reducing the risk of unauthorized access and fraudulent data injection. The central system performs automated event detection and separately evaluates physical building condition and communication status, enabling prioritized response planning. To evaluate feasibility, a two-building prototype was implemented and tested through scenario-based experiments involving two independently operating building-edge monitoring units connected to the same central monitoring system. The prototype demonstrated concurrent secure data acquisition and central aggregation from two buildings; however, district- and regional-scale performance requires further validation through larger-scale controlled load tests and field deployments. Under laboratory conditions, the prototype demonstrated sensor-data acquisition, authenticated transmission, and centralized event classification. End-to-end latency and building-edge monitoring unit power consumption were also measured; however, the prototype was not validated under environmental conditions representative of real disasters. Overall, the findings suggest that sensor-based, secure, and centralized monitoring systems may complement traditional disaster management approaches. Full article

Density Functional Theory (DFT) calculations were applied at the B3LYP/6-311G+(d,p) level to examine how nitrogen (N) and boron (B) and combined nitrogen/boron doping (N/B) affected the electronic properties and chemical behavior of graphene oxide (GrO). The work aimed to measure how global reactivity descriptors, including ionization potential, chemical hardness, and electrophilicity, changed when dopants entered the system while evaluating their prediction accuracy for gas sensing performance against NH₃ and H₂O and CO₂. The results show that undoped GrO exhibits a HOMO/LUMO gap value of 2.9059 eV while the introduction of dopants increases reactivity through gap reduction because N-doping decreased the gap to 1.3622 eV, B-doping reduced it to 1.3388 eV, and co-doping (GrO-NB) led to a gap of 1.9897 eV. The TDM analysis and the gas interaction energy gap results show that GrO-NB-H₂O exhibits the strongest interaction which results in chemical reactivity through its lowest ΔE of 1.9565 eV, establishing itself as a highly sensitive water vapor sensor when compared with NH₃ and CO₂. With adsorption energies of −0.1986, −0.1742, and −0.0735 eV for NH₃, H₂O, and CO₂, respectively, the N/B co-doped graphene oxide demonstrated favorable and reversible physisorption, underscoring its potential for gas sensing applications. The results offer an essential understanding of how N/B co-doping influences the electronic and adsorption characteristics of graphene oxide, thereby supporting its potential use in graphene-based sensing technologies. Full article

Recent demand for reliable, low-power, and cost-effective gas sensors has spurred research into chemiresistive materials that operate under ambient conditions. PEDOT and PEDOT:PSS combined with semiconductor metal oxides (SMOs) have attracted attention due to their complementary properties: polymer flexibility and stability, alongside oxide reactivity and robustness. This review highlights the integration of PEDOT and PEDOT:PSS with n- and p-type SMOs, concentrating on fabrication techniques, sensing mechanisms, and performance indicators, such as sensitivity, selectivity, and response time. Emphasis is placed on heterojunction engineering, morphology control, and the influence of particle size and environmental factors. Despite notable progress, challenges persist in long-term stability, selectivity in mixed gases, and performance under varying conditions. Interface engineering and composite optimisation show promise, with potential applications in environmental monitoring, industrial safety, and wearable diagnostics. Full article

Exhaled breath analysis has emerged as a promising non-invasive approach for disease diagnosis, leveraging gas sensors for their high sensitivity, portability, and real-time monitoring capabilities. Two-dimensional nanomaterials, such as graphene, transition metal dichalcogenides (TMDs), MXenes, black phosphorus, and metal–organic frameworks (MOFs), exhibit exceptional gas-sensing properties due to their atomic-scale thickness, ultra-large specific surface area, and tunable electronic structures. These characteristics enable enhanced gas adsorption and room-temperature operation, making them ideal for detecting ppb-level biomarkers like acetone, ammonia, and nitric oxide in breath. However, sensors based on pristine 2D materials face challenges including slow response/recovery kinetics, poor stability, weak humidity resistance, and limited selectivity in complex breath environments. To address these limitations, functionalization strategies have been developed to engineer material properties. Key approaches include heteroatom doping to modulate electronic band structures, heterojunction construction to facilitate charge transfer and improve selectivity, and noble metal decoration for catalytic enhancement of gas adsorption. Additionally, light irradiation has been employed to regulate the carrier concentration on the surface of sensitive materials. These strategies significantly boost sensor performance, achieving ppb-level detection limits, robust humidity resistance, and rapid response. Future directions involve integrating functionalized 2D materials into wearable, multiplexed sensor arrays for simultaneous biomarker detection, coupled with machine learning for real-time diagnostic platforms. Full article

In our day-to-day lives, we are regularly exposed to a wide spectrum of dangerous gases. Their origins vary, ranging from industrial activities to objects found within our very homes. Naturally, there is an interest in developing cost-efficient and durable devices that can successfully track these gases within our environment. One such candidate is represented by chemoresistive gas sensors based on metal oxides. This is due to their simple architecture and the possibility of scaling down their size, making them valid contenders for future advancements in portable gas sensors. This review focuses on chemoresistive gas sensors that have been obtained through different Physical Vapor Deposition (PVD) methods, which are easily scalable for potential technological transfer towards commercialization or are already exploited at the industrial level, and how varying different deposition parameters impacts the structure of the active material, thus modifying the gas sensing properties of the device. In this review, we report results obtained for different metal oxides: WO₃, ZnO, CeO₂, TiO₂, NiO, and SnO₂. The main findings of these studies revealed that the sensor’s response was highly impacted by oxygen deficiencies within the deposited material, the specific surface area, and the thickness of the film. Moreover, this study also delves into different strategies of functionalization that result in improved gas sensing properties. Thus, we herein report how tailoring functional properties modifies the gas sensing performance of different metal oxides. Full article

Copper oxide (CuO) has emerged as a promising p-type semiconductor for a wide range of applications, including gas sensing and photoelectric devices. This is due to its narrow band gap, high chemical stability and low cost. In recent years, increasing attention has been paid to the development of high-quality CuO thin films with precisely controlled structural and electronic properties. Among various fabrication techniques, atomic layer deposition (ALD) provides unique advantages like excellent thickness control, conformality and tunability of film composition at the atomic scale. This review provides a comprehensive overview of CuO thin films with a particular focus on ALD-based fabrication approaches. First, conventional deposition methods are briefly discussed. Next, the fundamentals of ALD processes for CuO growth are presented including precursor chemistry, reaction mechanisms and the influence of key process parameters. Special attention is given to the correlation between deposition conditions and the resulting structural, optical and electrical properties of the films. Subsequently, the impact of these properties on device performance is analyzed in the context of gas sensing and photoelectric applications. Finally, current challenges and future perspectives are outlined, emphasizing the need for improved control over phase composition, defect engineering, and integration with nanostructured systems. Full article

Silicon carbide (SiC) nanowires possess unique one-dimensional structural features, excellent mechanical strength, thermal stability and wide bandgap properties, showing great potential in high-temperature electronics, catalysis, sensing and composite reinforcement. Nevertheless, pristine SiC nanowires suffer from inert surface activity, weak interfacial compatibility and limited optoelectronic and catalytic performance. Surface coating and heterojunction engineering are effective strategies to address these deficiencies. This review systematically summarizes the synthesis routes of pristine SiC nanowires, including carbothermal reduction, chemical vapor deposition, template-assisted growth and molten salt synthesis, as well as their morphological regulation, physicochemical properties and inherent limitations. Meanwhile, typical coating methods such as wet chemical, hydrothermal, CVD and PIP are elaborated, and the influences of coating thickness, uniformity, adhesion and lattice/thermal compatibility on performance are summarized. The classification and interfacial charge mechanism of Type II, Z-scheme and Schottky heterojunctions are discussed, and the advances of coated SiC nanowires in photodetection, photocatalysis, gas sensing, electromagnetic shielding and energy storage are reviewed. Current challenges including coating stability, scalable preparation and integration bottlenecks are pointed out, and future research directions focusing on interface control, multifunctional integration and AI-assisted material design are prospected. Full article