Nanoplasmonic NO2 Sensor with a Sub-10 Parts per Billion Limit of Detection in Urban Air

Determination of the sensing properties of the fluorescence-based sensor for atmospheric NO2 gas

Air pollution in urban areas poses a serious threat to human health and therefore the studies about the development of low cost and sensitive sensors to monitor the air quality with high spatial and low temporal resolution continue to be an extensive area in literature. In this study, oxime modified poly(4-(1-pyrenyl) styrene) (P(PySt)-NOX) probes were synthesized to use as a sensor to detect NO2 gas in ambient air. The structural characterization results showed that the probe was successfully synthesized. The sensitivity, selectivity, repeatability, and aging tests were performed during the study, and it was observed that P(PySt)-NOX loaded sensor is sensitive to NO2 for concentrations below 100 ppb. The selectivity measurements were performed against O3 and SO2 which are common interfering gases in ambient air, and it was shown that the sensor is selective to NO2. Additionally, according to the aging tests performed in laboratory for 23 days, it was observed that the sensor is stable in this time interval. The studies showed the sensor synthesized and designed in this study is suitable for NO2 concentration measurements in ambient air where the concentration levels of NO2 is below 100 ppb.

W18O49 Nanofibers Functionalized with Graphene as a Selective Sensing of NO2 Gas at Room Temperature

Recent trends in two-dimensional (2D) graphene have demonstrated significant potential for gas-sensing applications with significantly enhanced sensitivity even at room temperature. Herein, this study presents fabrication of distinctive gas sensor based on one-dimensional (1D) W18O49 nanofibers decorated 2D graphene, specifically coated on copper (Cu)-based interdigitated electrodes formed by DC sputtering, which can selectively detect NO2 gas at room temperature. The sensor device fabricated using W18O49/Gr1.5% (i.e., W18O49 nanofibers hybrid nanocomposite with 1.5 wt % graphene) displays excellent overall sensing performance at 27 °C (room temperature) with high response (∼150-160 times) to NO2 gas. The W18O49/Gr1.5%-based sensor device reflects the highly selective detection toward NO2 gas among various gases with quick response time of 3 s and speedy recovery in 6 s. The limit of detection of ∼0.3 ppm with excellent reproducibility and stability for 3 months in all weather conditions (tested in humidity conditions 20-97%) are superior features of the device under test. However, W18O49/Gr3% displayed higher selectivity for NO2 but resulted with comparatively reduced sensitivity than W18O49/Gr1.5% sensor. The enhanced sensing performance could be attributed to the graphene content to decorate the nanofibers on it, oxygen vacancies/defects, and the contacts between the sensing material and Cu. This favorable synthesis and properties of self-assembled hybrid composite materials provide a potential utilization for detecting NO2 gas in environmental safety inspection.

Unlocking Predictive Capability and Enhancing Sensing Performances of Plasmonic Hydrogen Sensors via Phase Space Reconstruction and Convolutional Neural Networks

This study innovates plasmonic hydrogen sensors (PHSs) by applying phase space reconstruction (PSR) and convolutional neural networks (CNNs), overcoming previous predictive and sensing limitations. Utilizing a low-cost and efficient colloidal lithography technique, palladium nanocap arrays are created and their spectral signals are transformed into images using PSR and then trained using CNNs for predicting the hydrogen level. The model achieves accurate predictions with average accuracies of 0.95 for pure hydrogen and 0.97 for mixed gases. Performance improvements observed are a reduction in response time by up to 3.7 times (average 2.1 times) across pressures, SNR increased by up to 9.3 times (average 3.9 times) across pressures, and LOD decreased from 16 Pa to an extrapolated 3 Pa, a 5.3-fold improvement. A practical application of remote hydrogen sensing without electronics in hydrogen environments is actualized and achieves a 0.98 average test accuracy. This methodology reimagines PHS capabilities, facilitating advancements in hydrogen monitoring technologies and intelligent spectrum-based sensing.

New Approach for the Detection of Sub-ppm Limonene: An Investigation through Chemoresistive Metal-Oxide Semiconductors

R-(+)-limonene, one of the major constituents of citrus oils, is a monoterpene that is widely used as a fragrance additive in cosmetics, foods, and industrial solvents. Nowadays, its detection mainly relies on bulky and expensive analytical methods and only a few research works proved its revelation through affordable and portable sensors, such as electrochemical and quartz crystal microbalance sensors. In response to the demand for effective miniaturized sensing devices to be integrated into Internet of Things systems, this study represents a pioneering investigation of chemoresistive gas sensor capabilities addressed to R-(+)-limonene detection. An array of seven metal-oxide sensors was exploited to perform a complete electrical characterization of the target analyte. The experimental evidence allowed us to identify the WO₃-based sensor as the most promising candidate for R-(+)-limonene detection. The material was highly sensitive already at sub-ppm concentrations (response of 2.5 at 100 ppb), consistent with applicative parameters, and it resulted in selective vs. different gases at a lower operating temperature (200 °C) than the other sensors tested. Furthermore, it exhibited a humidity-independent behavior under real-life conditions (relative humidity > 20%). Finally, the WO₃ sensor also demonstrated a remarkable cross-selectivity, thus enabling its exploitation in cutting-edge applications.

Semiconducting MOFs on ultraviolet laser-induced graphene with a hierarchical pore architecture for NO2 monitoring

Due to rapid urbanization worldwide, monitoring the concentration of nitrogen dioxide (NO₂), which causes cardiovascular and respiratory diseases, has attracted considerable attention. Developing real-time sensors to detect parts-per-billion (ppb)-level NO₂ remains challenging due to limited sensitivity, response, and recovery characteristics. Herein, we report a hybrid structure of Cu₃HHTP₂, 2D semiconducting metal-organic frameworks (MOFs), and laser-induced graphene (LIG) for high-performance NO₂ sensing. The unique hierarchical pore architecture of LIG@Cu₃HHTP₂ promotes mass transport of gas molecules and takes full advantage of the large surface area and porosity of MOFs, enabling highly rapid and sensitive responses to NO₂. Consequently, LIG@Cu₃HHTP₂ shows one of the fastest responses and lowest limit of detection at room temperature compared with state-of-the-art NO₂ sensors. Additionally, by employing LIG as a growth platform, flexibility and patterning strategies are achieved, which are the main challenges for MOF-based electronic devices. These results provide key insight into applying MOFtronics as high-performance healthcare devices.

Environmental formaldehyde sensing at room temperature by smartphone-assisted and wearable plasmonic nanohybrids

Formaldehyde is a toxic and carcinogenic indoor air pollutant. Promising for its routine detection are gas sensors based on localized surface plasmon resonance (LSPR). Such sensors trace analytes by converting tiny changes in the local dielectric environment into easily readable, optical signals. Yet, this mechanism is inherently non-selective to volatile organic compounds (like formaldehyde) and yields rarely detection limits below parts-per-million concentrations. Here, we reveal that chemical reaction-mediated LSPR with nanohybrids of Ag/AgOx core-shell clusters on TiO2 enables highly selective formaldehyde sensing down to 5 parts-per-billion (ppb). Therein, AgOx is reduced by the formaldehyde to metallic Ag resulting in strong plasmonic signal changes, as measured by UV/Vis spectroscopy and confirmed by X-ray diffraction. This interaction is highly selective to formaldehyde over other aldehydes, alcohols, ketones, aromatic compounds (as confirmed by high-resolution mass spectrometry), inorganics, and quite robust to relative humidity changes. Since this sensor works at room temperature, such LSPR nanohybrids are directly deposited onto flexible wristbands to quantify formaldehyde between 40-500 ppb at 50% RH, even with a widely available smartphone camera (Pearson correlation coefficient r = 0.998). Such chemoresponsive coatings open new avenues for wearable devices in environmental, food, health and occupational safety applications, as demonstrated by an early field test in the pathology of a local hospital.

High switching ratio and inorganic gas sensing performance in BeN4based nanodevice: a first-principles study

Recently, Dirac material BeN₄has been synthesized by using laser-heated diamond anvil-groove technology (Bykovet al2021Phys. Rev. Lett.126175501). BeN₄layer, i.e. beryllonitrene, represents a qualitatively class of two-dimensional (2D) materials that can be built of a metal atom and polymeric nitrogen chains, and hosts anisotropic Dirac fermions. Enlighten by this discovered material, we study the electronic structure, anisotropic transport properties and gas sensitivity of 2D BeN₄using the density functional theory combined with non-equilibrium Green's function method. The results manifest that the 2D BeN₄shows a typical semi-metallic property. The electronic transport properties of the intrinsic BeN₄devices show a strong anisotropic behavior since electrons transmitting along the armchair direction is much easier than that along the zigzag direction. It directly results in an obvious switching characteristic with the switching ratio up to 10⁵. Then the adsorption characteristics indicate that H₂S, CO, CO₂and H₂molecules are physisorption, while the NH₃, NO, NO₂, SO₂molecules are chemisorption. Among these chemisorption cases, the 2D gas sensor devices show an extremely high response for SO₂recognition, and the high anisotropy of the original 2D BeN₄device still maintains after adsorbing gas molecules. Finally, high switching ratio and inorganic gas sensing performance of BeN₄monolayer could be clearly understood with local density of states, bias-dependent spectra, scattered state distribution. In general, the results indicate that the designed BeN₄devices have potential practical application in high-ratio switching devices and high gas-sensing molecular devices.