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Fast, accurate, real-time measurement of gas concentration is an important task for preventing coal mining disasters. In order to develop an accurate monitoring method for methane gas concentration at different locations in a mine environment, a non-source optical fiber sensor for multi-point methane detection has been developed in this paper. A 16-channel fiber splitter and a multi-channel time-sharing acquisition module are employed within the sensor, enabling simultaneous detection of methane gas at 16 points by a host. Furthermore, the methane sensors are connected to the monitoring host via an all-optical method, achieving non-source and long-range detection of methane. To assess the performance of the methane gas sensor, experiments were conducted to evaluate its detection range, response time, and stability. The results indicated that the average detection error was approximately 1.84% across the full range, and the response time did not exceed 10 s. The minimum detection limit of the sensor, as determined by the 1σ criteria, was obtained as 58.42 ppm. Additionally, the concentrations of methane gas measured at varying distances (1 km, 2 km, 5 km) were found to be essentially consistent over an extended period. These results suggest that the development of this non-source optical fiber sensor holds significant potential for providing a method for mine environment, multi-point online methane gas detection.

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Accurately detecting atmospheric carbon dioxide is a vital part of responding to the global greenhouse effect. Conventional off-axis integral cavity detection systems are computationally intensive and susceptible to environmental factors. This study deploys an Extreme Learning Machine model incorporating a cascaded integrator comb (CIC) filter into the off-axis integrating cavity. It is shown that appropriate parameters can effectively improve the performance of the instrument in terms of lower detection limit, accuracy, and root mean square deviation. The proposed method is incorporated successfully into a monitoring station situated near an industrial area for detecting atmospheric carbon dioxide (CO2) concentration daily.

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The high risk of CO poisoning justifies the need for indoor air quality control and warning systems based on the detection of low concentrations (ppm-ppb) of CO. Cobalt corrole complexes selectively bind CO vs. O2, CO2, N2, opening new fields of applications. By combining the CO chemisorption properties of cobalt corroles with the known sorption capacity of MOFs, we hope to obtain high performance sensing materials for CO detection. In addition, the exposed metal sites of MOFs lead to CO2 physisorption, allowing the co-detection of CO and CO2. In this work, PCN-222, a stable Zr-based MOF made from Ni(TCPP) with natural vacancies, has been used as a porous matrix for the grafting of electron-poor metallocorroles. The materials were characterized by powder XRD, SEM and optical microscopy, BET analyses and gas adsorption measurements at 298 K. No degradation of the crystalline structure of PCN-222 was observed. At 1 atm, the adsorbed CO(g) volumes measured for the best materials were 12.15 cm3 g-1 and 14.01 cm3 g-1 for CoCorr2@PCN-222 and CoCorr3@PCN-222 respectively, and both materials exhibited high CO chemisorption and selectivity against O2, N2, and CO2 at low pressure due to the highest energy of the chemisorption process vs physisorption.

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Metal organic frameworks (MOFs) constructed with bismuth metal have not been widely reported, especially multifunctional Bi-MOFs. Therefore, developing multifunctional MOFs is of great significance due to the increasing requirements of materials. In this work, a 3D Bi-MOF (Bi-TCPE) with multifunctionality was successfully constructed, demonstrating high thermal stability, water stability, a porous structure, and strong blue fluorescence emission. We evaluated the properties of Bi-TCPE in detecting anions (S2-, Cr2O72-, and CrO42-) in aqueous solution, along with the rapid visual detection of H2S gas and proton conduction. In terms of anion detection, Bi-TCPE achieved the rapid detection of trace S2- in aqueous solutions, while the Ksv value was 1.224 × 104 M-1 with a limit of detection (LOD) value of 1.93 µM through titration experiments. Furthermore, Bi-TCPE could sensitively detect Cr2O72- and CrO42-, with Ksv values of 1.144 × 104 and 1.066 × 104 M-1, respectively, while LOD reached 2.07 and 2.18 µM. Subsequently, we conducted H2S gas detection experiments, and the results indicated that Bi-TCPE could selectively detect H2S gas at extremely low concentrations (2.08 ppm) and with a fast response time (<10 s). We also observed significant color changes under both UV light and sunlight. Therefore, we developed a H2S detection test paper for the rapid visual detection of H2S gas. Finally, we evaluated the proton conductivity of Bi-TCPE, and the experimental results showed that the proton conductivity of Bi-TCPE reached 4.77 × 10-2 S·cm-1 at 98% RH and 90 °C, achieving an excellent value for unmodified and encapsulated MOFs. In addition, Bi-TCPE showed high stability in proton conduction experiments (it remained stable after 21 consecutive days of testing and 12 cycles of testing), demonstrating relatively high application value. These results indicate that Bi-TCPE is a multifunctional MOF material with great application potential.

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Differential photoacoustic spectroscopy (PAS) for flow gas detection based on single microphone is innovatively proposed and experimentally demonstrated. Unlike the traditional systems, only one microphone is used to suppress flowing gas noise. Wavelength modulation spectroscopy and second harmonic detection technique are applied in this PAS system with Q-point demodulation for acetylene (C2H2) gas detection. The experiment is conducted at 1 atm and 300 K. Different concentrations and flow rates of C2H2 from 0 sccm to 225 sccm are detected by using nitrogen (N2) as the carrier gas, which indicates that the system can respond well to flowing gases while maintaining the noise at the same level. The system response time decreases to 3.58 s while the gas velocity is 225 sccm. The detection limit of 43.97 ppb with 1 s integration time and normalized noise equivalent absorption (NNEA) coefficient of 4.0 × 10-9 cm-1 W Hz-1/2 is achieved at the flow rate of 225 sccm. The firstly proposed differential PAS based on single microphone greatly simplifies the system structure for flow gas detection, which provides a novel route for development of PAS with significant practical implementation prospects.

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Differential photoacoustic spectroscopy (DPAS) cells are usually excited on the first longitudinal ring mode, with a microphone situated in the middle of each of the two resonator tubes. However, it is known from other photoacoustic spectroscopy cell designs that connecting the microphones via a capillary can lead to signal enhancement. By means of finite element method (FEM) simulations, we compared such a photoacoustic spectroscopy (PAS) cell with a capillary to a DPAS cell with a capillary attached to each of the two resonators and showed that the behavior of both systems is qualitatively the same: In both the PAS and the DPAS cell, in-phase and anti-phase oscillations of the coupled system (resonator-capillary) can be excited. In the DPAS cell, capillaries of suitable length also increase the pressure signal at the microphones according to the FEM simulations. For different capillary diameters (1.2 mm/1.7 mm/2.2 mm), the respective optimal capillary length (36-37.5 mm) and signal amplification was determined (94%, 70%, 53%). According to the results of these FEM simulations, a significant increase in sensitivity can, therefore, also be achieved in DPAS cells by expanding them with thin tubes leading to the microphones.

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In this article, we aim to develop and study a highly sensitive and selective cm2scale graphene-based gas sensor. We present the technology used to fabricate sensors which integrate monolayer chemical vapour deposition graphene: photolithography and transfer of layers. Characterization techniques (optical microscopy, AFM, micro-Raman spectroscopy, transport electrical measurements) ensure a diagnosis of graphene ribbons and allow good reproducibility of technological processes. We present the results of gas characterizations after a 200 ppm NO2exposure. We propose a novel approach for the modelling of the sensor response with a three-site adsorption/desorption Langmuir model. This innovative way of modelling the sensor response should provide a better understanding of the sensor's kinetic and help to overcome the long response time observed with graphene gas sensors.

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Optical cross-correlation is a technique that can achieve both high specificity and high sensitivity when deployed as the basis for a sensing technology. Offering significant gains in cost, size and complexity, it can also deliver significantly higher signal-to-noise ratios than traditional approaches such as absorption methodologies. In this paper, we present an optical cross-correlation technology constructed around a bespoke customised Fiber Bragg Grating (FBG). Exploiting the remarkable flexibility in design enabled by multiple aperiodic Bragg gratings, optical filters are devised that exactly mimic the absorption features of a target gas species (for this paper, acetylene C 2 H 2 ) over some waveband of interest. This grating forms the heart of the sensor architecture described here that employs modulated optical cross-correlation for gas detection. An experimental demonstration of this approach is presented, and shown to be capable of differentiating between different concentrations of the C 2 H 2 target gas. Furthermore these measurements are shown to be robust against interloper species, with minimal impact on the detection signal-to-noise arising from the introduction of contaminant gases. This represents is a significant step toward the use of customised FBGs as low-cost, compact, and highly customisable photonic devices for deployment in gas detection.

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The concentration of end-tidal carbon dioxide is one of the important indicators for evaluating whether the human respiratory system is normal. Accurately detecting of end-tidal carbon dioxide is of great significance in clinical practice. With the continuous promotion of the localization of end-tidal carbon dioxide monitoring technology, its application in clinical practice in China has become increasingly widespread in recent years. The study is based on the non-dispersive infrared method and comprehensively elaborates on the detection principle, gas sampling methods, key technologies, and technological progress of end-tidal carbon dioxide detection technology. It comprehensively introduces the current development status of this technology and provides reference for application promotion and further improvement.

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Deep learning methods, a powerful form of artificial intelligence, have been applied in a number of spectroscopy and gas sensing applications. However, the speciation of multi-component gas mixtures from infrared (IR) absorption spectra using deep learning remains to be explored. Here, we propose a one-dimensional deep convolutional neural network gas classification model for the identification of small molecules of interest based on IR absorption spectra in flexible user-defined frequency ranges. The molecules considered include ten that are of interest in the atmosphere or in industrial and environmental processes: water vapor, carbon dioxide, ozone, nitrous oxide, carbon monoxide, methane, nitric oxide, sulfur dioxide, nitrogen dioxide, and ammonia. A simulated dataset of IR absorption spectra for mixtures of these molecules diluted in air was generated and used to train a deep learning model. The model was tested against simulated spectra containing noise and was found to provide speciation predictions with accuracy from 82 to 97%. The internal operation of the model was investigated using class activation maps that illustrate how the model prioritizes spectral information for classification. Finally, the model was demonstrated for the prediction of speciation for two synthetic experimental mixture spectra. The proposed model and the dataset generation strategies are generalized and can be implemented for other gases, different frequency ranges, and spectroscopy types. The multi-component speciation method developed herein is the first application of a convolutional neural network model, trained on HITRAN-based simulations, for spectral identification.

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We have investigated a polarization property of the (specularly) reflected light from an aluminum grating, coated with a palladium (Pd) thin-film on its surface. The polarization property, which is associated with surface plasmon resonance (SPR), and occurs in the Pd thin-film on the aluminum grating in a conical mounting, is observed as a rapid change in the normalized Stokes parameter s3, around the resonance angle, θsp, at which point, SPR occurs. The sensing technique used the rapid change in s3 to allow us to successfully detect a small change in the complex refractive index of the Pd thin-film layer upon exposure to hydrogen gas, with a concentration near the lower explosion level. Experimental results showed that the sensing technique provided a sensitive and stable response when the Pd thin-film layer was exposed to gas mixtures containing hydrogen at concentrations of 1 to 4% (by volume) in nitrogen.

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BACKGROUND: Highly toxic organophosphorus nerve agents often exist in the form of gas in the environment and can damage human neuroregulatory system by inhibiting the activity of acetylcholinesterase (AChE). However, fluorescent probes based on small organic molecules bring a secondary burden to environment, and their sensitivity and specificity for sarin simulant diethyl chlorophosphate (DCP) detection are unsatisfactory. Nanozyme cascade systems with signal amplification can be used for highly sensitive identification of analytes, but are rarely used in ratiometric analysis of DCP. Combination of enzyme cascades and ratiometric fluorescence ensures the accuracy and sensitivity of the output signal. RESULTS: We prepared a self-assembled nanohybrid (Ag-AuNCs@UiO-66-NH2) by metal-organic framework material and gold nanoclusters. On the one hand, UiO-66-NH2 with enzyme-like activity was used to hydrolyze DCP into diethyl phosphate (DEP) and chloridion (Cl-). Cl- hindered aggregation-induced enhanced emission (AIEE) of AuNCs by binding with Ag+ and decreased the fluorescence of AuNCs. On the other hand, ligand metal charge transfer effect (LMCT) of UiO-66-NH2 was blocked by DCP to enhance the fluorescence of UiO-66-NH2. Combining ratiometric analysis and nanozyme cascade reaction, an ultra-sensitive fluorescence sensor for detecting DCP was constructed, and ensured the accuracy of experimental results. In addition, Ag-AuNCs@UiO-66-NH2 was embedded into the agarose hydrogel substrate, the resulting agarose hydrogel film allowed quantitative assessment of DCP vapor and high sensitivity was demonstrated (detection limit as low as 1.02 ppb). SIGNIFICANCE: A strategy combining enzyme cascade with ratiometric fluorescence was proposed, which improved the accuracy and sensitivity of the analysis results. The soft-solid platform based on agarose hydrogel film was constructed to realize the quantitative monitoring of sarin simulant gas. The LOD value obtained in this work is much lower than the immediately life-threatening or health threatening concentration of sarin.

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Semiconductor metal oxides (SMOs) nanomaterials are a category of sensing materials that are widely applied to chemiresistive NOx gas sensors. However, there is much space to improve the sensing performance of SMOs nanomaterials. Therefore, how to improve the sensing performance of SMOs nanomaterials for NOx gases has always attracted the interest of researchers. Up to now, there are few reviews focus on the modification strategies of SMOs which applied to NOx gas sensors. In order to compensate for the limitation, this review summarizes the existing modification strategies of SMOs, hoping to provide researchers a view of the research progress in this filed as comprehensive as possible. This review focuses on the progress of the modification of SMOs nanomaterials for chemiresistive NOx (NO, NO2) gas sensors, including the morphology modulation of SMOs, compositing SMOs, loading noble metals, doping metal ions, compositing with carbon nanomaterials, compositing with biomass template, and compositing with MXene, MOFs, conducting polymers. The mechanism of each strategy to enhance the NOx sensing performance of SMOs-based nanomaterials is also discussed and summarized. In addition, the limitations of some of the modification strategies and ways to address them are discussed. Finally, future perspectives for SMOs-based NOx gas sensors are also discussed.

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Sulfur hexafluoride (SF6) gas is extensively utilized as an insulating and arc-quenching medium in the circuit breakers and isolating switches of electrical equipment. It effectively isolates the circuits from the atmosphere and promptly extinguishes arcs. Therefore, the issue of SF6 gas leakage poses a significant threat to the related application fields, and the detection of SF6 gas leakage becomes extremely important. Infrared imaging detection offers advantages including non-contact, high precision, and visualization. However, most existing infrared detection systems are equipped with only one filter to detect SF6 gas. The images captured contain background noise and system noise, making these systems vulnerable to interference from such noises. To address these issues, we propose a method for monitoring SF6 gas leakage based on a customized binocular imaging (CBI) system. The CBI system has two filters, greatly reducing the interference of system noise and background noise. The first filter features the absorption resonant peak of SF6 gas. The second filter is used to record background noise and system noise. One aspect to note is that, in order to avoid the interference of other gases, the central wavelength of this second filter should keep away from the absorption resonant peaks of those gases. Accordingly, the central wavelengths of our customized filters were determined as 10,630 nm and 8370 nm, respectively. Then, two cameras of the same type were separately assembled with a customized filter, and the CBI prototype was accomplished. Finally, we utilized the difference method using two infrared images captured by the CBI system, to monitor the SF6 gas leakage. The results demonstrate that our developed system achieves a high accuracy of over 99.8% in detecting SF6 gas. Furthermore, the CBI system supports a plug-and-play customization to detect various gases for different scenarios.

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Gas imaging has become one of the research hotspots in the field of gas detection due to its significant advantages, such as high efficiency, large range, and dynamic visualization. It is widely used in industries such as natural gas transportation, chemical, and electric power industries. With the development of infrared detector technology, uncooled thermal imagers are undergoing a developmental stage of technological advancement and widespread application. This article introduces a gas imaging principle and radiation transfer model, focusing on passive imaging technology and active imaging technology. Combined with the actual analysis, the application scenarios using uncooled thermal imaging cameras for gas imaging measurement are analyzed. Finally, the limitations and challenges of the development of gas imaging technology are analyzed.

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A high sensitivity and ultra-low concentration range photoacoustic spectroscopy (PAS) gas detection system, which was based on a novel trapezoid compound ellipsoid resonant photoacoustic cell (TCER-PAC) and partial least square (PLS), was proposed to detect acetylene (C2H2) gas. In the concentration range of 0.5 ppm ∼ 10.0 ppm, the limit of detection (LOD) values of TCER-PAC-based PAS system without data processing was 66.4 ppb, which was lower than that of the traditional trapezoid compound cylindrical resonant photoacoustic cell (TCCR-PAC). The experimental results indicated that the TCER-PAC had higher sensitivity than of TCCR-PAC. Within the concentration range of 12.5 ppb ∼ 125.0 ppb, the LOD and limit of quantification (LOQ) of TCER-PAC-based PAS system combined with PLS regression algorithm were 1.1 ppb and 3.7 ppb, respectively. The results showed that higher detection sensitivity and lower LOD were obtained by PAS system with TCER-PAC and PLS than that of TCCR-PAC-based PAS system.

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Invasive methods such as blood collection and biopsy are commonly used for testing liver and kidney function, which are painful, time-consuming, require trained personnel, and may not be easily accessible to people for their routine checkup. Early diagnosis of liver and kidney diseases can prevent severe symptoms and ensure better management of these patients. Emerging approaches such as breath and sweat analysis have shown potential as non-invasive methods for disease diagnosis. Among the many markers, ammonia is often used as a biomarker for the monitoring of liver and kidney functions. In this review we provide an insight into the production and expulsion of ammonia gas in the human body, the different diseases that could potentially use ammonia as biomarker and analytical devices such as chemiresistive gas sensors for non-invasive monitoring of this gas. The review also provides an understanding into the different materials, doping agents and substrates used to develop such multifunctional sensors. Finally, the current challenges and the possible future trends have been discussed.

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Photoacoustic spectroscopy (PAS) can be utilized as an ultrasensitive gas detection method. The basic principles of gas detection using PAS are discussed in this paper. First, the basic instrumentation for a PAS gas detection system is introduced focusing on the photoacoustic cell. The discussion includes non-resonant photoacoustic cells and the different types of resonant photoacoustic cells, including the longitudinal photoacoustic cell, the Helmholtz photoacoustic cell, the T-type photoacoustic cell, and the high-frequency resonant photoacoustic cell. The basic working principles of each of these, cells as well as the advantages and disadvantages of photoacoustic cells are discussed, and the development of newer types of photoacoustic cells in recent years is outlined in detail. This review provides detailed reference information and guidance for interested researchers who would like to design and build advanced photoacoustic cells for gas detection.

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As highly promising devices for odor recognition, current electronic noses are still not comparable to human olfaction due to the significant disparity in the number of gas sensors versus human olfactory receptors. Inspired by the sniffing skills of wine tasters to achieve better odor perception, a multiple overlapping sniffs (MOSS) strategy is proposed in this study. The MOSS strategy involves rapid and continuous inhalation of odorants to stimulate the sensor array to generate feature-rich temporal signals. Computational fluid dynamics simulations are performed to reveal the mechanism of complex dynamic flows affecting transient responses. The proposed strategy shows over 95% accuracy in the recognition experiments of three gaseous alkanes and six liquors. Results demonstrate that the MOSS strategy can accurately and easily recognize odors with a limited sensor number. The proposed strategy has potential applications in various odor recognition scenarios, such as medical diagnosis, food quality assessment, and environmental surveillance.

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An all-optical non-resonant photoacoustic spectroscopy system for multicomponent gas detection based on a silicon cantilever optical microphone (SCOM) and an aseismic photoacoustic cell is proposed and demonstrated. The SCOM has a high sensitivity of over 96.25 rad/Pa with sensitivity fluctuation less than ± 1.56 dB between 5 Hz and 250 Hz. Besides, the minimal detectable pressure (MDP) of the sensor is 0.55 µPa·Hz-1/2 at 200 Hz, which indicates that the fabricated sensor has high sensitivity and low noise level. Six different gases of CO2, CO, CH4, C2H6, C2H4, C2H2 are detected at the frequency of 10 Hz, whose detection limits (3σ) are 62.66 ppb, 929.11 ppb, 1494.97 ppb, 212.94 ppb, 1153.36 ppb and 417.61 ppb, respectively. The system achieves high sensitivity and low detection limits for trace gas detection. In addition, the system exhibits seismic performance with suppressing vibration noise by 4.5 times, and achieves long-term stable operation. The proposed non-resonant all-optical PAS multi-component gas detection system exhibits the advantages of anti-vibration performance, low gas consumption and long term stability, which provides a solution for working in complex environments with inherently safe.