State-of-the-art of methane sensing materials: A review and perspectives

Indoor Air Quality Monitoring System with High Accuracy of Gas Classification and Concentration Prediction via Selective Mechanism Research

The efficacy of sensors, particularly sensor arrays, lies in their selectivity. However, research on selectivity remains notably obscure and scarce. In this work, indoor pollutants (C7H8, HCHO, CH4, and NO2) were chosen as the target gas. Following the screening of six oxides from previous work, temperature-programmed desorption/reduction experiments were conducted to delve into the origins of selectivity. The results explicate the superiority of NiO in detecting toluene and unveil the distinctive NO2 sensing mechanism of WO3 sensors. Based on the sensor array comprising these oxides, it can clearly detect low concentrations of C7H8 (S = 1.6 to 50 ppb), HCHO (S = 1.4 to 50 ppb), and NO2 (S = 3.3 to 50 ppb), which satisfies the requisites of indoor air monitoring. Meanwhile, three machine learning models (Extreme Gradient Boosting, Support Vector Machine, and Back Propagation Neural Network) are employed for gas classification. The classification accuracies of these models are 95.45%, 100%, and 100%, while the R2 values of the concentration prediction are 99.65%, 94.9%, and 98.04%, respectively, indicating the rationality of material selection. Furthermore, it can still achieve relatively high accuracy in gas classification (94.12%) and concentration prediction (89.36%), even for gas mixtures of four gases. Finally, an indoor air quality monitoring system is developed, which enables real-time monitoring of indoor gas quality through the Internet of Things.

Advances in 2D Materials Based Gas Sensors for Industrial Machine Olfactory Applications

The escalating development and improvement of gas sensing ability in industrial equipment, or "machine olfactory", propels the evolution of gas sensors toward enhanced sensitivity, selectivity, stability, power efficiency, cost-effectiveness, and longevity. Two-dimensional (2D) materials, distinguished by their atomic-thin profile, expansive specific surface area, remarkable mechanical strength, and surface tunability, hold significant potential for addressing the intricate challenges in gas sensing. However, a comprehensive review of 2D materials-based gas sensors for specific industrial applications is absent. This review delves into the recent advances in this field and highlights the potential applications in industrial machine olfaction. The main content encompasses industrial scenario characteristics, fundamental classification, enhancement methods, underlying mechanisms, and diverse gas sensing applications. Additionally, the challenges associated with transitioning 2D material gas sensors from laboratory development to industrialization and commercialization are addressed, and future-looking viewpoints on the evolution of next-generation intelligent gas sensory systems in the industrial sector are prospected.

Non-Invasive Multi-Gas Detection Enabled by Cu-CuO/PEDOT Microneedle Sensor

Metal-oxide-based gas sensors are extensively utilized across various domains due to their cost-effectiveness, facile fabrication, and compatibility with microelectronic technologies. The copper (Cu)-based multifunctional polymer-enhanced sensor (CuMPES) represents a notably tailored design for non-invasive environmental monitoring, particularly for detecting diverse gases with a low concentration. In this investigation, the Cu-CuO/PEDOT nanocomposite was synthesized via a straightforward chemical oxidation and vapor-phase polymerization. Comprehensive characterizations employing X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), X-ray diffraction (XRD), and micro Raman elucidated the composition, morphology, and crystal structure of this nanocomposite. Gas-sensing assessments of this CuMPES based on Cu-CuO/PEDOT revealed that the response current of the microneedle-type CuMPES surpassed that of the pure Cu microsensor by nearly threefold. The electrical conductivity and surface reactivity are enhanced by poly (3,4-ethylenedioxythiophene) (PEDOT) polymerized on the CuO-coated surface, resulting in an enhanced sensor performance with an ultra-fast response/recovery of 0.3/0.5 s.

Self-assembled tetrazine cryptophane for ion pair recognition and guest release by cage disassembly

Hereby, we describe the synthesis of a self-assembled syn-cryptophane using dynamic nucleophilic aromatic substitution of tetrazines. 1H NMR cage titrations reveal that the tetramethylammonium cation binds under slow exchange conditions while counter-anions show a fast exchange regime. Finally, the cryptophane can be disassembled by the addition of thiols allowing guest release.

Utilization of a Low-Cost Sensor Array for Mobile Methane Monitoring

The use of low-cost sensors (LCSs) for the mobile monitoring of oil and gas emissions is an understudied application of low-cost air quality monitoring devices. To assess the efficacy of low-cost sensors as a screening tool for the mobile monitoring of fugitive methane emissions stemming from well sites in eastern Colorado, we colocated an array of low-cost sensors (XPOD) with a reference grade methane monitor (Aeris Ultra) on a mobile monitoring vehicle from 15 August through 27 September 2023. Fitting our low-cost sensor data with a bootstrap and aggregated random forest model, we found a high correlation between the reference and XPOD CH4 concentrations (r = 0.719) and a low experimental error (RMSD = 0.3673 ppm). Other calibration models, including multilinear regression and artificial neural networks (ANN), were either unable to distinguish individual methane spikes above baseline or had a significantly elevated error (RMSDANN = 0.4669 ppm) when compared to the random forest model. Using out-of-bag predictor permutations, we found that sensors that showed the highest correlation with methane displayed the greatest significance in our random forest model. As we reduced the percentage of colocation data employed in the random forest model, errors did not significantly increase until a specific threshold (50 percent of total calibration data). Using a peakfinding algorithm, we found that our model was able to predict 80 percent of methane spikes above 2.5 ppm throughout the duration of our field campaign, with a false response rate of 35 percent.

Single-Molecule Methane Sensing Using Palladium-Functionalized nIR Fluorescent Single-Walled Carbon Nanotubes

There has been considerable interest in detecting atmospheric and process-associated methane (CH4) at low concentrations due to its potency as a greenhouse gas. Nanosensor technology, particularly fluorescent single-walled carbon nanotube (SWCNT) arrays, is promising for such applications because of their chemical sensitivities at single-molecule detection limits. However, the methodologies for connecting the stochastic molecular fluctuations from gas impingement on such sensors require further development. In this work, we synthesize Pd-conjugated ss(GT)15-DNA-wrapped SWCNTas near-infrared (nIR) fluorescent, single-molecule sensors of CH4. The complexes are characterized using X-ray photoelectron spectroscopy (XPS) and spectrophotometry, demonstrating spectral changes between the Pd2+ and Pd0 oxidation states. The nIR fluctuations generated upon exposure from 8 to 26 ppb of CH4 were separated into high- and low-frequency components. Aggregating the low-frequency components for an array of sensors showed the most consistent levels of detection with a limit of 0.7 ppb. These results advance the hardware and computational methods necessary to apply this approach to the challenge of environmental methane sensing.

Room-Temperature Monitoring of CH4 and CO2 Using a Metal-Organic Framework-Based QCM Sensor Showing Inherent Analyte Discrimination

The detection of methane and carbon dioxide is of growing importance due to their negative impact on global warming. This is true for both environmental monitoring and leak detection in industrial processes. Although solid-state sensors are technologically mature, they have limitations that prohibit their use in certain situations, e.g., explosive atmospheres. Thus, there is a need to develop new types of sensor materials. Herein, we demonstrate a simple, low-cost, metal-organic framework (MOF)-based gas leak detection sensor. The system is based on gravimetric sensing by using a quartz crystal microbalance. The quartz crystal is functionalized by layer-by-layer growth of a thin metal-organic framework film. This film shows selective uptake of methane or carbon dioxide under atmospheric conditions. The hardware has low cost, simple operation, and theoretically high sensitivity. Overall, the sensor is characterized by simplicity and high robustness. Furthermore, by exploiting the different adsorption kinetics as measured by multiple harmonic analyses, it is possible to discriminate whether the response is due to methane or carbon dioxide. In summary, we demonstrate data relevant toward new applications of metal-organic frameworks and microporous hybrid materials in sensing.

Pt-Pd Nanoalloys Functionalized Mesoporous SnO2 Spheres: Tailored Synthesis, Sensing Mechanism, and Device Integration

Methane (CH4 ), as the vital energy resource and industrial chemicals, is highly flammable and explosive for concentrations above the explosive limit, triggering potential risks to personal and production safety. Therefore, exploiting smart gas sensors for real-time monitoring of CH4 becomes extremely important. Herein, the Pt-Pd nanoalloy functionalized mesoporous SnO2 microspheres (Pt-Pd/SnO2 ) were synthesized, which show uniform diameter (≈500 nm), high surface area (40.9-56.5 m2 g-1 ), and large mesopore size (8.8-15.8 nm). The highly dispersed Pt-Pd nanoalloys are confined in the mesopores of SnO2 , causing the generation ofoxygen defects and increasing the carrier concentration of sensitive materials. The representative Pt1 -Pd4 /SnO2 exhibits superior CH4 sensing performance with ultrahigh response (Ra /Rg = 21.33 to 3000 ppm), fast response/recovery speed (4/9 s), as well as outstanding stability. Spectroscopic analyses imply that such an excellent CH4 sensing process involves the fast conversion of CH4 into formic acid and CO intermediates, and finally into CO2 . Density functional theory (DFT) calculations reveal that the attractive covalent bonding interaction and rapid electron transfer between the Pt-Pd nanoalloys and SnO2 support, dramatically promote the orbital hybridization of Pd4 sites and adsorbed CH4 molecules, enhancing the catalytic activation of CH4 over the sensing layer.

Benzothiazole-based novel fluorescence probe sensing 1, 3-diaminopropane

Amines are extensively present in biological systems and are abundantly used in research, industries and agriculture. Systematic detection and quantification of certain amines can help us in food quality control and diagnosis of many diseases. A Schiff base probe HL was designed and successfully synthesized. It was proposed as a sensor for the exclusive detection of 1, 3- diaminopropane through turn-on fluorescence response in a variety of solvents including water. Micromolar limits of detection was achieved in all these solvents. Mechanism of detection was proposed by investigating mass spectrometric and NMR results. These were corroborated with DFT/TD-DFT calculations. Spiking experiments performed in various real water samples revealed the potential of the sensor to be used in day-to-day applications. Paper strip experiments demonstrated the suitability of the probe for real-life applications.

MOF/MWCNT-Nanocomposite Manipulates High Selectivity to Gas via Different Adsorption Sites with Varying Electron Affinity: A Study in Methane Detection in Parts-per-Billion

Metal-organic frameworks (MOFs) present specific adsorption sites with varying electron affinity which are uniquely conducive to selective gas sensing but are typically large-band-gap insulators. On the contrary, multiwall carbon nanotubes (MWCNTs) exhibit superior mesoscopic transport exploiting strong electron correlations among sub-bands below and above the Fermi level at room temperature. We synergize them in a new class of nanocomposites based on zeolitic imidazolate framework-8 (ZIF-8) and report selective sensing of CH₄ in ∼10 parts-per-billion (ppb) with a determined limit of detection of ∼0.22 ppb, hitherto unprecedented. The observed selectivity to CH₄ over non-polar CO₂, polar volatile organic compounds, and moisture has roots in competing electron-sharing mechanisms at its different adsorption sites. This important result provides a significant reference to guide future MOF-related composite research to achieve the best sensing performance. On molecular adsorption, MWCNTs facilitate electrical transport via manipulating the ZIF-8 band gap to show a p-type semiconductor behavior with lower activation energy to induce a measurable resistance change. Excellent repeatability and reversibility are shown. A carbon-engineered MOF composite has the potential to actuate similar selective response to low reactive gases via carrier manipulation in the energy band gap.

Effect of Pd-Sensitization on Poisonous Chlorine Gas Detection Ability of TiO2: Green Synthesis and Low-Temperature Operation

Ganoderma lucidum mushroom-mediated green synthesis of nanocrystalline titanium dioxide (TiO₂) is explored via a low-temperature (≤70 °C) wet chemical method. The role of Ganoderma lucidum mushroom extract in the reaction is to release the ganoderic acid molecules that tend to bind to the Ti⁴⁺ metal ions to form a titanium-ganoderic acid intermediate complex for obtaining TiO₂ nanocrystallites (NCs), which is quite novel, considering the recent advances in fabricated gas sensing materials. The X-ray powder diffraction, field emission scanning electron microscopy, Raman spectroscopy, and Brunauer–Emmett–Teller measurements etc., are used to characterize the crystal structure, surface morphology, and surface area of as-synthesized TiO₂ and Pd-TiO₂ sensors, respectively. The chlorine (Cl₂) gas sensing properties are investigated from a lower range of 5 ppm to a higher range of 400 ppm. In addition to excellent response–recovery time, good selectivity, constant repeatability, as well as chemical stability, the gas sensor efficiency of the as-synthesized Pd-TiO₂ NC sensor is better (136% response at 150 °C operating temperature) than the TiO₂ NC sensor (57% at 250 °C operating temperature) measured at 100 ppm (Cl₂) gas concentration, suggesting that the green synthesized Pd-TiO₂ sensor demonstrates efficient Cl₂ gas sensing properties at low operating temperatures over pristine ones.

Design and development of highly sensitive PEDOT-PSS/AuNP hybrid nanocomposite-based sensor towards room temperature detection of greenhouse methane gas at ppb level

Herein, we present fabrication of a novel methane sensor based on poly (3,4-ethylenedioxythiophene:poly (styrene sulfonic acid)) (p-PEDOT-PSS) and gold nanoparticles (AuNPs) treated with dimethyl sulfoxide (DMSO) and Zonyl using a spin coating technique. The nanocomposite films were further post treated with H2SO4 to improve the charge transport mechanism. The structural and morphological features of the composites were analyzed through scanning electronic microscopy, transmission electron microscopy, Fourier transform infra-red spectroscopy, UV-Vis spectroscopy and thermogravimetric analysis. Treatment with organic solvents and post treatment of H2SO4 significantly enhances the conductivity of the composite to 1800 S cm-1. The fabricated sensor shows an excellent sensing response, fast response and recovery time along with acceptable selectivity towards methane gas at ppb concentrations. Due to a simple fabrication technique, excellent conductivity, superior sensing performance and improved mechanical properties, the sensor fabricated in this study could potentially be used to detect greenhouse methane gas at low concentrations.

A chemiresistive methane sensor

A chemiresistive sensor is described for the detection of methane (CH₄), a potent greenhouse gas that also poses an explosion hazard in air. The chemiresistor allows for the low-power, low-cost, and distributed sensing of CH₄ at room temperature in air with environmental implications for gas leak detection in homes, production facilities, and pipelines. Specifically, the chemiresistors are based on single-walled carbon nanotubes (SWCNTs) noncovalently functionalized with poly(4-vinylpyridine) (P4VP) that enables the incorporation of a platinum-polyoxometalate (Pt-POM) CH₄ oxidation precatalyst into the sensor by P4VP coordination. The resulting SWCNT-P4VP-Pt-POM composite showed ppm-level sensitivity to CH₄ and good stability to air as well as time, wherein the generation of a high-valent platinum intermediate during CH₄ oxidation is proposed as the origin of the observed chemiresistive response. The chemiresistor was found to exhibit selectivity for CH₄ over heavier hydrocarbons such as n-hexane, benzene, toluene, and o-xylene, as well as gases, including carbon dioxide and hydrogen. The utility of the sensor in detecting CH₄ using a simple handheld multimeter was also demonstrated.

Capacitive and Infrared Gas Sensors for the Assessment of the Methane Number of LNG Fuels

Liquid Natural Gas (LNG) is an energy source that is becoming more important in energy transition, as the world is facing lower the CO₂ emissions and backup sources for wind and solar energy are needed. LNG is becoming a major player not only as fuel for power plants, but also in transport and mobility. However, the composition of LNG varies significantly between the various production locations around the world, and the layering of hydrocarbons with different molecular weights takes place even in LNG containers. This is especially critical for LNG engines, in which the ignition properties of the gas depend heavily on the fuel quality or Methane Number (MN) of the gas. For optimized engine operation and motor management, this fuel quality should be measured regularly, preferably online and by a small and low-cost sensor. This paper presents two sensor solutions for the assessment of the full gas composition. For both sensors, the standard deviation in the composition of the relevant hydrocarbons was low enough to calculate the Methane Number with an accuracy of approximately 1 MN unit. It was demonstrated that the electronic capacitive sensor was better suited to assess the higher hydrocarbons, whereas the infrared sensor showed higher selectivity for the lower hydrocarbons.