Gas Detection Research Articles

Emerging Horizons in Gas Sensing: Exploring the Potential of MXenes and MBenes.

This review article is focused on the development and application of two types of emerging two-dimensional (2D) materials, namely MXenes and MBenes, in the field of gas detection. Owing to its excellent electrical conductivity, specific surface area, and tunable surface functionality, MXenes have demonstrated high sensitivity and rapid response in detecting a variety of gases, such as volatile organic compounds (VOCs), nitrogen dioxide (NO2), and ammonia (NH3). MBenes are relatively newly discovered materials with excellent electronic stability and gas adsorption capabilities. Both of these materials demonstrate significant potential in improving sensor selectivity and stability through surface functionalization and heterostructure designs. However, despite the impressive gas detection performance of these materials, challenges remain in achieving long-term stability, cost-effectiveness, and commercialization. We summarize the prominent research insights on these materials and offer an outlook on future research directions and potential applications. With ongoing research and technological advancements, MXenes and MBenes are anticipated to have a substantial impact in critical areas such as environmental monitoring and industrial safety.

A Novel Mechanism Based on Oxygen Vacancies to Describe Isobutylene and Ammonia Sensing of p-Type Cr2O3 and Ti-Doped Cr2O3 Thin Films

Gas sensors based on metal oxide semiconductors (MOS) have been widely used for the detection and monitoring of flammable and toxic gases. In this paper, p-type Cr2O3 and Ti-doped Cr2O3 (CTO) thin films were synthesized using an aerosol-assisted chemical vapor deposition (AACVD) method. Detailed analysis of the thin films deposited, including structural information, their elemental composition, oxidation state, and morphology, was investigated using XRD, Raman analysis, SEM, and XPS. All the gas sensors based on pristine Cr2O3 and CTO exhibited a reversible response and good sensitivity to isobutylene (C4H8) and ammonia (NH3) gases. Doping Ti into the Cr2O3 lattice improves the response of the CTO-based sensors to C4H8 and NH3. We describe a novel mechanism for the gas sensitivity of p-type metal oxides based on variations in the oxygen vacancy concentration.

Gas classification and concentration prediction in open environments using class anchor clustering-initialized temporal convolutional network

Identifying target gases and predicting their concentrations in open environments are critical tasks, particularly due to fluctuating environmental conditions and the presence of unknown gases. This study aims to address these challenges by developing a model that improves both gas classification and concentration prediction. We introduce two key components: Quantile-Dynamic Associated Features (Q-DAF) and the Class Anchor Clustering-Initialized Temporal Convolutional Network (CAC-InitTCN). Q-DAF dynamically enhances gas signal feature extraction, optimizing the ability of CAC-InitTCN to handle complex and changing gas environments. CAC-InitTCN is designed to efficiently process time-series data, allowing it to manage gas concentration fluctuations while mitigating the interference of unknown gases. CAC-InitTCN was evaluated on two distinct datasets, achieving classification accuracy rates of 93.62 % and 98.05 %, respectively. In gas concentration prediction tasks, the model demonstrated RMSE values of 0.2102 and 0.0392, and R2 scores of 0.9085 and 0.9784, after data normalization. These results demonstrate the capability of CAC-InitTCN in handling real-time gas fluctuations and recognizing unknown gases, making it a promising approach for open-environment gas detection.

Strain and External Electric Field Engineering of S-Terminated MXene on Selective and Sensitive Detection of N-Containing Compound Gases: A Computational Study.

Gas sensors are used for monitoring hazardous gases and vapors. With the emergence of S-terminated MXene synthesis, herein, we explore the sensing ability of Ti3C2S2 toward N-containing gases, including NH3, NO, NO2, trimethylamine (TMA), and nicotine (NT), using first-principles calculations and a statistical thermodynamic model. We find that Ti3C2S2 exhibits high selectivity to TMA, NO, and NT with moderate adsorption energies of -0.610, -0.490, and -0.476 eV, respectively, minimizing environmental noise from ambient gases. The electronic structure of Ti3C2S2 subtly alters upon adsorption of TMA, NO, and NT, facilitating detectable signals in the sensing device. However, the adsorption of NO2 and NH3 is less pronounced due to weak physisorption (<0.3 eV). Employing engineering strategies including biaxial strain and an external electric field greatly enhances the selectivity and sensitivity of NO2 (NH3) detection by boosting adsorption strength up to -0.351 eV with ε = 5% (-0.370 eV with |E⃗| = 0.6 V/ Å). In addition, the moderate adsorption energies of the gases result in a suitable recovery time in the range of milliseconds, leading to high reusability of the sensing device. The estimated adsorption densities suggest potential coverage of these N-containing molecules even at low concentrations and room temperature. Computational analysis of the sensing capability of Ti3C2S2 using the nonequilibrium Green's function method indicates that it is a promising gas-sensing material. In addition, mechanical modifications, electric field adjustments, and gate voltage alterations could be used to obtain effective sensing materials for N-containing gas detection.

All Puffed Up: Exploring Ultra-diffuse Galaxy Origins Through Galaxy Interactions

We present new follow-up observations of two ultra-diffuse galaxies (UDGs) selected for their distorted morphologies and tidal features, suggestive of tidal influence. Using Hubble Space Telescope Advanced Camera for Surveys F555W and F814W imaging, we identify 8 ± 2 globular clusters in KUG 0203-Dw1 and 6 ± 2 in KDG 013, abundances typical for normal dwarf galaxies of similar stellar mass. Jansky Very Large Array data reveal a clear H i detection of KUG 0203-Dw1 with a gas mass estimate of logMHI/M⊙≲7.4 and evidence of active stripping by the host, while KDG 013 has no clear gas detection. The UDGs likely originated as normal dwarf galaxies that have been subjected to significant stripping and tidal heating, causing them to become more diffuse. These two UDGs complete a sample of five exhibiting tidal features in the full Canada–France–Hawaii Telescope Legacy Survey area (∼1502 deg). These tidally influenced UDGs exhibit diverse properties; one stands out as a potential result of a dwarf merger, while the remainder suggest tidal heating origins. We also cannot conclusively rule out that these galaxies became UDGs in the field before processing by the group environment, underscoring the need for broader searches of diffuse galaxies to better understand the impact of galaxy interactions.

Parameter Optimization of Semiconductor Gas Sensor under AC Impedance Measurement.

Semiconductor gas sensors were confirmed to perform high linearity and a stable baseline under alternating current (AC) impedance measurements. However, a procedure to determine the optimal parameters of AC impedance measurements is still lacking. Taking the detection of SF6 decomposition gas as an example, this work has established a model of semiconductor gas sensors under AC impedance measurement. Employing four types of sensors to detect three gases (H2S, SO2, and CO), the effectiveness of the optimization method has been validated, as well. With the high linearity and stable baseline obtained from AC impedance measurement, it enables rapid correction of temperature drift within environmental temperatures ranging from 10 to 30 °C. Overall, the proposed method can provide a novel approach to inhibit the drift failure of semiconductor gas sensors.

Olfactory Visualization Sensing Array Made with CelluMOFs to Predict Fruit Ripeness Using Deep Learning.

Developing a colorimetry-based artificial scent screening system (i.e., an olfactory visual sensing system) with high sensitivity and accurate pattern recognition for detecting fruit ripeness remains challenging. In this work, we construct a flexible dye/CelluMOFs-based sensor array with improved sensitivity for on-site detection of characteristic gases of fruits and integrate a densely connected convolutional network (DenseNet) into the sensor array, enabling it to recognize unique scent fingerprints and categorize the ripeness of fruits. In the system, CelluMOFs are synthesized through in situ growth of γ-cyclodextrin metal-organic frameworks (γ-CD-MOFs) on flexible fiber filter paper to fabricate a uniform, flexible and porous dye/CelluMOFs sensitive membrane. Compared to the pristine filter paper, the CelluMOFs exhibit increased porosity with a 62 times higher specific surface area and a 3-fold increase in dye loading capacity after 12 h of adsorption. The prepared dye/CelluMOFs sensing film shows outstanding mechanical and detection stability with negligible deviation after 100 cycles of rubbing. The colorimetric visualization arrays with multiple colorimetric dye/CelluMOFs chips, enable the sensitive recognition and detection of nine kinds of characteristic fruit odors and achieve a high response at 8-1500 ppm of trans-2-hexenal, showcasing remarkably low gas detection thresholds. On the basis of the ppm-level limit of detection with high sensitivity, the fabricated colorimetric sensor arrays are typically used for in situ assessment of fruit ripeness by integrating DenseNet. This approach achieves a satisfactory classification accuracy of 99.09% on the validation set, enabling high-precision prediction of fruit ripeness levels.

A TDLAS gas detection method based on digital signal modulation

This research presents a novel TDLAS gas concentration detection method based on digital modulation. The method inherits the advantage of a simple system structure from Direct Absorption Spectroscopy, as well as the excellent sensitivity of Wavelength Modulation Spectroscopy. A low-frequency sawtooth wave is employed to drive the laser, resulting in a digital direct absorption spectrum signal. By constructing a cosine modulation sequence in the time domain and performing linear interpolation on the direct absorption spectrum, it successfully converts to a wavelength-modulated absorption spectrum and simultaneously generates a digital reference signal at double the frequency. Ultimately, phase-locked amplification technology can be used to calculate the amplitude of the second harmonic. Since both the modulation and reference signals are generated digitally, they ensure a strict frequency-doubling relationship and phase correlation, which not only reduces the complexity of the hardware system but also effectively minimizes system errors. Because digital technology generates both the modulation and reference signals, it ensures that they have the same phase and a strict frequency-doubling relationship. Experimental results demonstrate that, when fitted by a cubic polynomial, the second harmonic amplitude and the gas concentration have a correlation coefficient (R2) as high as 0.99999 and a root mean square error as low as 0.0011. This proves the method's great accuracy and reliability in practical applications.

Optimizing Low-Cost Gas Analysis with a 3D Printed Column and MiCS-6814 Sensor for Volatile Compound Detection.

This paper explores an application of 3D printing technology on the food industry. Since its inception in the 1980s, 3D printing has experienced a huge rise in popularity. This study uses cost-effective, flexible, and sustainable components that enable specific features of certain gas chromatography. This study aims to optimize the process of gas detection using a 3D printed separation column and the MiCS-6814 sensor. The principle of the entire device is based on the idea of utilizing a simple capillary chromatographic column manufactured by 3D printing for the separation of samples into components prior to their measurement using inexpensive chemiresistive sensors. An optimization of a system with a 3D printed PLA block containing a capillary, a mixing chamber, and a measuring chamber with a MiCS-6814 sensor was performed. The optimization distributed the sensor output signal in the time domain so that it was possible to distinguish the peak for the two most common alcohols, ethanol and methanol. The paper further describes some optimization types and their possibilities.

A Review on Photoacoustic Spectroscopy Techniques for Gas Sensing.

The rapid growth of industry and the global drive for modernization have led to an increase in gas emissions, which present significant environmental and health risks. As a result, there is a growing need for precise and sensitive gas-monitoring technologies. This review delves into the progress made regarding photoacoustic gas sensors, with a specific focus on the vital components of acoustic cells and acoustic detectors. This review highlights photoacoustic spectroscopy (PAS) as an optical detection technique, lauding its high sensitivity, selectivity, and capability to detect a wide range of gaseous species. The principles of photoacoustic gas sensors are outlined, emphasizing the use of modulated light absorption to generate heat and subsequently detect gas pressure as acoustic pressure. Additionally, this review provides an overview of recent advancements in photoacoustic gas sensor components while also discussing the applications, challenges, and limitations of these sensors. It also includes a comparative analysis of photoacoustic gas sensors and other types of gas sensors, along with potential future research directions and opportunities. The main aim of this review is to advance the understanding and development of photoacoustic gas detection technology.

Adsorption and gas sensing properties of Cun, Agn and Rhn (n=1–3) clusters doped with WTe2 for transformer winding deformation fault gases

In order to solve the problem that the initial WTe2 has poor adsorption effect on transformer winding deformation fault gas, this paper uses density functional theory (DFT) to study the adsorption behavior of three target gases (CO, C2H2 and CO2) on the surface of WTe2 substrate doped with three metal clusters: Cun, Agn, and Rhn (n=1–3). By analyzing the adsorption distance, adsorption energy, DCD and DOS of the three systems, the effect of metal cluster doping on the adsorption of fault gas by WTe2 was revealed. The results show that metal cluster doping can effectively improve the conductivity of WTe2 substrate and make its band structure more compact. CO and C2H2 have good adsorption characteristics in the three doping systems, while CO2 can be effectively adsorbed by Rh cluster-doped WTe2. In addition, this article also uses work function and band gap to analyze the effect of gas adsorption on substrate conductivity, and discusses the practical application prospects of the three metal cluster doping systems from the perspectives of recovery time and sensitivity, and achieved good results. This paper provides theoretical guidance for exploring the application prospects of WTe2 substrate in transformer winding deformation fault diagnosis and gas detection.

Transition metal enhanced black phosphorus for early thermal runaway gas detection of lithium-ion batteries: A theoretical study

Lithium-ion batteries have seen widespread use, bringing the issue of thermal runaway into sharp focus. Thermal runaway can be diagnosed by the characteristic gases produced (CO2, H2, CO, CH4, C2H4, C2H6). Black phosphorus (BP) with corrugated plane was utilized as the base material, enhancing its chemical activity with transition metals (Au, Ag, Pt, Pd). The four transition metal-enhanced BPs can selectively adsorb CO and C2H4 with different response characteristics, which can be used to identify CO and C2H4. This study provides theoretical guidance for the engineering application of transition metal-enhanced BP in monitoring thermal runaway gases in lithium-ion batteries.

Helium Detection in Natural Gas Using Raman Spectroscopy.

Raman spectroscopy has great potential for quantitative analysis of natural gas. Helium is one of the components of natural gas and has a wide range of applications. It was believed that noble gases could not be detected using this technique due to the absence of their vibrational spectra. In this study, we demonstrated an approach to extracting the content of helium from the Raman spectrum of methane and carried out test measurements for the first time. The approach is based on the determination of changes in the ν1 band of methane caused by the influence of helium and other components. The necessary spectroscopic parameters characterizing the effect of methane (CH4), helium (He), nitrogen (N2), carbon dioxide (CO2), and ethane (C2H6) on the ν1 band of methane at a resolution of 0.35 cm-1 were obtained. The validation of the approach showed that the helium content in natural gas can be measured with an uncertainty of 1 mol% at a sample pressure of 50 bar. The measurement precision can be increased to 0.01 mol% by using a high-resolution spectrometer. The described method does not claim to replace helium detectors, but it can be considered a valuable addition to Raman gas analysis of natural gas in developing an all-in-one device. The possibilities for further improvement of the approach are also discussed.

Study on the Design Method of High-Resolution Volume-Phase Holographic Gratings.

Volume-phase holographic gratings are suitable for use in greenhouse gas detection imaging spectrometers, enabling the detection instruments to achieve high spectral resolution, high signal-to-noise ratios, and high operational efficiency. However, when utilized in the infrared wavelength band with high dispersion requirements, gratings struggle to meet the demands for low polarization sensitivity due to changes in diffraction performance caused by phase delays in the incidence of light waves with distinct polarization states, and current methods for designing bulk-phase holographic gratings require a large number of calculations that complicate the balance of diffraction properties. To overcome this problem, a design method for transmissive bulk-phase holographic gratings is proposed in this study. The proposed method combines two diffraction theories (namely, Kogelnik coupled-wave theory and rigorous coupled-wave theory) and establishes a parameter optimization sequence based on the influence of design parameters on diffraction characteristics. Kogelnik coupled-wave theory is employed to establish the initial Bragg angle range, ensuring that the diffraction efficiency and phase delay of the grating thickness curve meet the requirements for incident light waves in various polarization states. Utilizing rigorous coupled-wave theory, we optimize grating settings based on criteria such as a center wavelength diffraction efficiency greater than 95%, polarization sensitivity less than 10%, maximum bandwidth, and spectral diffraction efficiency exceeding 80%. The ideal grating parameters are ultimately determined, and the manufacturing tolerances for various grating parameters are analyzed. The design results show that the grating stripe frequency is 1067 lines per millimeter, and the diffraction efficiencies of TE and TM waves are 96% and 99.89%, respectively. The diffraction efficiency of unpolarized light is more than 88% over the whole spectral range with an average efficiency of 94.49%, an effective bandwidth of 32 nm, and a polarization sensitivity of less than 7%. These characteristics meet the performance requirements for dispersive elements based on greenhouse gas detection, the spectral resolution of the detection instrument is up to 0.1 nm, and the signal-to-noise ratio and working efficiency are improved by increasing the transmittance of the instrument.

Natural gas leakage detection from offshore platform by OGI camera and unsupervised deep learning

Natural gas leak from offshore platform poses a potential to cause explosion disaster and bring significant causalities and economic losses. Existing deep learning-based leak detection approaches are limited by the requirement of a large number of labeled leak datasets, and also has worse performance in the complex and changeable marine environment. This study proposes a detection approach of natural gas leakage from offshore platform by integrating optical gas imaging (OGI) camera and unsupervised deep probability learning. In this approach, unsupervised deep learning is applied to learn the changeable infrared features of offshore platform, and variational Bayesian inference is integrated to provide the larger epistemic uncertainty contour corresponding to the infrared natural gas plume. An epistemic uncertainty-based detection score is proposed as the detection criterion to improve the accuracy of natural gas plume detection and localization. An OGI imaging experiment of natural gas leak from offshore platform is conducted to construct the benchmark dataset. With such datasets, two pre-defined parameters, namely Monte Carlo sampling number m = 100 and dropout probability p=0.1 are determined to guarantee the detection accuracy and efficiency. Comparison between the proposed approach and prevalent unsupervised deep learning approach is also conducted. The results demonstrate that our proposed approach has the higher detection accuracy with AUC = 0.9753, as well as the real-time capability with inference time of 4s/frame. Overall, our proposed approach provides a more accurate and generalized approach of natural gas detection for safety monitoring and detection management of offshore platforms.

Recent Progress on Perovskite Materials for VOC Gas Sensing.

Volatile organic compound (VOC) gases are highly hazardous to human health, and their presence in the human breath plays an indispensable role for the early diagnosis of various diseases (cancer, renal failure, etc.). In recent times, perovskite materials have shown notable performance in the detection of VOC gases with high accuracy, fast response, recovery time, selectivity, and sensitivity, owing to their unique crystallographic structures and excellent optoelectronic properties. In this Review, we look at recent reports on perovskite-based sensors and their sensing performance toward VOC gases. Here, we focus on the sensing mechanisms of two types of perovskite materials, metal halide and metal oxide perovskites, and explain the differences in their crystal structures. We also discuss the common preparation methods used by researchers for the synthesis of these perovskite materials. Further, we elucidate various important factors influencing the sensing performance of perovskite-based sensors, such as doping, defects, morphology, temperature, humidity, and light. We conclude with the future prospects and challenges related to these perovskite-based sensors toward the detection of VOC gases.

Silver Telluride Colloidal Quantum Dot Solid for Fast Extended Shortwave Infrared Photodetector.

Extended shortwave infrared (eSWIR) photodetectors that employ solution-processable semiconductors have attracted attention for use in applications such as ranging, night vision, and gas detection. Colloidal quantum dots (CQDs) are promising materials with facile bandgap tunability across the visible-to-mid-infrared wavelengths. However, toxic elements, such as Hg and Pb, and the slow response time of CQD-based IR photodetectors, limit their commercial viability. This article presents a novel eSWIR photodetector that is fabricated using silver telluride (Ag2Te) CQDs. Effective thiolate ligand exchange enables a lower trap density and improved carrier mobility in CQD solids. Furthermore, a vertical p-n photodiode architecture with a favorable energy-level landscape is utilized to facilitate charge extraction, resulting in a fast, room-temperature-operable, and toxic-element-free CQD photodetector. The best eSWIR Ag2Te CQD photodetector exhibits a fall time of 72ns, representing the fastest response time among all prior CQD-based eSWIR photodetectors, including those containing toxic elements, such as Pb and Hg.

Ultrabroadband mid-infrared emission and gas sensing of cobalt-doped chalcogenide glass ceramics.

Mid-infrared (MIR) gain materials are of great significance for the development of MIR tunable fiber lasers. Herein, for the first time, to the best of our knowledge, it is found that Ga2Se3 nanocrystals distributed in chalcogenide glass ceramics can provide new tetrahedral-coordinated sites that can be used to activate ultrabroadband MIR emissions of divalent transition metal ions, such as Co2+. Under the excitation of a 1550 nm diode laser, the transparent Ge-Ga-Se glass ceramic embedded with Co2+: Ga2Se3 nanocrystals shows an intense 2.5-5.5 µm ultrabroadband emission. The peak wavelength is located at ∼4.2 µm and the full width at half maximum exceeds 2 µm. Such emission properties, originating from the dual lattice sites of Ga3+ ions, are superior to those of transparent chalcogenide glass ceramics embedded with Co2+: ZnSe nanocrystals. Moreover, the gas detection system built based on the glass ceramic shows a sensitivity of 45.9 ppm for butane gas. Therefore, the chalcogenide glass ceramics embedded with active Co2+: Ga2Se3 nanocrystals have great potential in MIR tunable fiber lasers and gas sensing.

Ag modified ZnO nanoflower gas sensitive sensor for selective detection of n-butanol

Ag modified ZnO nanoflowers were successfully prepared by sunlight induced solvent reduction method. The samples were characterized by x-ray diffractometer, field emission scanning electron microscope, transmission electron microscope and energy dispersive x-ray spectrum, and the results confirmed the presence of Ag nanoparticles on the ZnO nanoflower. The gas sensing performance of the materials was studied at different operating temperatures and different n-butanol concentrations. The results showed that the Ag modified ZnO nanoflower sensor responded to 50 ppm n-butanol up to 147.17 at 280 °C, and the Ag modified ZnO nanoflower sensor exhibited excellent repeatability, stability and response recovery time. In addition, different target gases were employed for the selectivity study of the Ag modified ZnO nanoflower. It can be found that the Ag modified ZnO nanoflower had good selectivity for n-butanol. The improved response of the Ag modified ZnO nanoflower sensor was attributed to the catalytic effect of Ag nanoparticles. The results indicate that the Ag modified ZnO nanoflower will become a very promising sensing material for n-butanol gas detection.

Detection of CO2, H2S, NH3, and gas mixtures using a quartz crystal microbalance sensor array with five sensitive materials

The large-scale development of chicken farms has inevitably led to an increase in the emission of harmful gases, which has prompted rapid research development on the detection of harmful gases, such as quartz crystal microbalance (QCM) sensors. In this research, a QCM sensor array modified with ethyl cellulose (EC), polyethyleneimine (PEI), polypyrrole (PPy), tetramethylammonium fluoride tetrahydrate (TMAF), and Nitrogen-doped tungsten carbide supported on carbon nanosheets (WC@NC) was established to detect gas mixtures. By analyzing the relationship between the fundamental frequency shift and the number of sensitive material layers for the QCM sensor, the optimal number of layers was determined. The QCM sensor array consisted of a blank QCM sensor, an 8-layer EC sensor, a 4-layer PEI sensor, a 3-layer PPy sensor, an 8-layer TMAF sensor, and an 8-layer WC@NC sensor. The results showed that the PEI sensor exhibited maximum frequency shifts when detecting gases, while TMAF and WC@NC films had the highest contribution to NH3 detection. TMAF, PEI, and WC@NC played significant roles in the binary classification of exceeding the standard detection of NH3. Additionally, WC@NC and EC sensors played an important role in detecting H2S and CO2, respectively. The QCM sensor array could accurately classify the excessive state of CO2. Overall, the QCM sensor array demonstrated a correct recognition rate of 87.5 %, indicating its potential for classifying the exceedance of NH3, CO2, and H2S gases in gas mixtures. This work provides basic information for research on QCM sensor arrays in gas detection.