A Portable Micro-Gas Chromatography with Integrated Photonic Crystal Slab Sensors on Chip

Identification of Different Classes of VOCs Based on Optical Emission Spectra Using a Dielectric Barrier Helium Plasma Coupled with a Mini Spectrometer

In this study, a micro helium dielectric barrier discharge (μHDBD) plasma device fabricated using 3D printing and molding techniques was coupled with a mini spectrometer to detect and identify different classes of volatile organic compounds (VOCs) using optical emission spectrometry (OES). We tested 11 VOCs belonging to three different classes (straight-chain alkanes, aromatics, and polar organic compounds). Our results clearly demonstrate that the optical emission spectra of different classes of VOCs show clear differences, and therefore, can be used for identification. Additionally, the emission spectra of VOCs with a similar structure (such as n-pentane, n-hexane, n-heptane, n-octane, and n-nonane) have similar optical emission spectrum shape. Acetone and ethanol also have similar emission wavelengths, but they show different line intensities for the same concentrations. We also found that the side-chain group of aromatics will also affect the emission spectra even though they have a similar structure (all have a benzene ring). Moreover, our μHDBD-OES system can also identify multiple compounds in VOC mixtures. Our work also demonstrates the possibility of identifying different classes of VOCs by the OES shape.

Enhanced Fano resonances in a silicon nitride photonic crystal nanobeam-assisted micro ring resonator for dual telecom band operation

Silicon-based Micro Ring Resonators (MRR) are a powerful tool for the realization of label free optical biosensors. The sharp edge of a Fano resonance in a Silicon Nitride (Si3N4) platform can boost photonic sensing applications based on MRRs. In this work, we demonstrate enhanced Fano resonance features for a Si3N4 Micro Ring Resonator assisted by a Photonic Crystal Nanobeam (PhCN-MRR) operating in the TM-like mode at the O-band wavelengths. Our findings show that the fabricated PhCN-MRR results in increased asymmetric resonances for TM-like mode compared with TE-like mode operation in the C-band. As a result, a versatile and flexible design to realize Fano resonance with polarization dependent asymmetry in the C and O telecom bands is presented.

Metalloporphyrin-Based Metal-Organic Frameworks for the Ultrasensitive Chemiresistive Detection of NO2: Effect of the Central Metal on Tuning the Sensing Performance

The highly sensitive and selective detection of trace hazardous gases at room temperature is very promising for health protection and environmental safety. Herein, chemiresistive sensors for NO2 were fabricated based on self-assembled films of the four metalloporphyrin (MPor)-based metal-organic frameworks PCN-222-M (M = Cu, Ni, Co, Fe) by the quasi-Langmuir-Shäfer method. It is found that the relative responses of the four PCN-222-M films are linearly related to the NO2 concentration, and the PCN-222-Cu possessed an unprecedented high response to NO2 with a sensitivity of 2209% ppm-1 in the 4-20 ppb range and a low limit of detection (LOD) of 0.93 ppb, achieving the best performance reported so far for NO2 detection at room temperature. Meanwhile, PCN-222-Ni showed the fastest recovery among the four PCN-222-M films, which can be used for the rapid detection of NO2. Excellent reproducibility, stability, selectivity, and moisture resistance are shown for both PCN-222-Cu and PCN-222-Ni. Combining the experimental study and density functional theory (DFT) calculation, the essential roles of MPor units and the MPor/Zr6 cluster hybrid material in tuning the Fermi level and the electron transfer between PCN-222-M and NO2 were further proved. These were less considered topics in previous studies on MOFs. This work explores the application of MPor-based MOFs in gas sensing by selecting appropriate MPor units, thus providing guidance for the development of MOF-based chemiresistive sensors.

Repetitive Direct Comparison Method for Odor Sensing

Olfactory sensors are one of the most anticipated applications of gas sensors. To distinguish odors-complex mixtures of gas species, it is necessary to extract sensor responses originating from the target odors. However, the responses of gas sensors tend to be affected by interfering gases with much higher concentrations than target odor molecules. To realize practical applications of olfactory sensors, extracting minute sensor responses of odors from major interfering gases is required. In this study, we propose a repetitive direct comparison (rDC) method, which can highlight the difference in odors by alternately injecting the two target odors into a gas sensor. We verified the feasibility of the rDC method on chocolates with two different flavors by using a sensor system based on membrane-type surface stress sensors (MSS). The odors of the chocolates were measured by the rDC method, and the signal-to-noise ratios (S/N) of the measurements were evaluated. The results showed that the rDC method achieved improved S/N compared to a typical measurement. The result also indicates that sensing signals could be enhanced for a specific combination of receptor materials of MSS and target odors.

Green Synthesis of Metal Oxides Semiconductors for Gas Sensing Applications

During recent decades, metal oxide semiconductors (MOS) have sparked more attention in various applications and industries due to their excellent sensing characteristics, thermal stability, abundance, and ease of synthesis. They are reliable and accurate for measuring and monitoring environmentally important toxic gases, such as NO₂, NO, N₂O, H₂S, CO, NH₃, CH₄, SO₂, and CO₂. Compared to other sensing technologies, MOS sensors are lightweight, relatively inexpensive, robust, and have high material sensitivity with fast response times. Green nanotechnology is a developing branch of nanotechnology and aims to decrease the negative effects of the production and application of nanomaterials. For this purpose, organic solvents and chemical reagents are not used to prepare metal nanoparticles. On the contrary, the synthesis of metal or metal oxide nanoparticles is done by microorganisms, either from plant extracts or fungi, yeast, algae, and bacteria. Thus, this review aims at illustrating the possible green synthesis of different metal oxides such as ZnO, TiO₂, CeO₂, SnO₂, In₂O₃, CuO, NiO, WO_3, and Fe₃O₄, as well as metallic nanoparticles doping.