Optical Gas Research Articles

Interband cascade laser absorption sensor for sensitive measurement of hydrogen chloride in smoke-laden gases using wavelength modulation spectroscopy

A tunable interband cascade laser sensor, based on wavelength modulation absorption spectroscopy near 3.73 µm, was developed to measure hydrogen chloride gas concentration in smoke-laden environments associated with the overhaul stages of firefighting. Wavelength selection near 2678cm−1 targets the P(0,9) transition within the fundamental vibrational band of HCl, chosen for its absorption strength and isolation from CO2, H2O, and CH4, as well as proximity to absorption features of other toxicant gases of interest in firefighting applications. Both scanned-wavelength direct absorption with a Voigt lineshape-fitting routine and a wavelength modulation spectroscopy absorption method are employed to recover species concentration. The laser sensor is paired with a compact commercial off-the-shelf 1 m multipass optical gas cell modified to use polished Alloy 20 steel mirrors for increased corrosion resistance against humid and acidic gases, and it is tested by sampling effluent gases from pyrolyzing and burning solid samples of polyvinyl chloride under a radiant heating apparatus in a laboratory fume hood. The wavelength modulation spectroscopy method is demonstrated to enable measurement at the near-ppm-level within a compact form-factor and to provide insights into the thermochemical pyrolysis processes that lead to the formation of hydrogen chloride when polyvinyl chloride is exposed to radiant heating.

Effects of Al doping on structural, optical, morphological, and low-concentration CO2 gas sensing properties of ZnO nanoparticles synthesized by sol-gel method

Abstract This work examines the morphological, structural, optical, and gas-sensing characteristics of ZnO thin films doped with Al that were created by the sol-gel spin coating technique. The thin films, doped with varying aluminum concentrations (0%, 2%, and 5%), were characterized using XRD, UV-visible spectroscopy, and FE-SEM to assess their crystallinity, band gap, and surface morphology. XRD analysis confirmed the incorporation of Al into the ZnO lattice without forming secondary phases, while UV-visible spectroscopy revealed an increase in transmittance and band gap with higher Al doping. FE-SEM images showed a transition from agglomerated grains to smoother surfaces with increased Al content. Gas sensing performance was evaluated using low-concentration CO2 as the target gas. The results demonstrated that Al doping significantly enhances the CO2 sensing response, with the 5% Al-doped ZnO exhibiting the optimal sensitivity due to increased carrier concentration and improved surface interaction. These findings suggest that Al-doped ZnO thin films are promising candidates for efficient CO2 gas sensors, combining enhanced structural and optical properties with superior gas sensing capabilities.

HMS optical fiber gas sensor based on double-layer WO3@CQDs porous film modified cladding for detecting 2-butanone gas at room temperature

In this study, a hollow malposition structure (HMS) optical fiber 2-butanone gas sensor based on double-layer WO3@CQDs porous film is proposed, and realizes the ppb detection of 2-butanone gas at room temperature. The HMS can excite the evanescent field and sense the gas adsorption on the fiber surface. The experimental results show sensitivity of 3.09 pm/ppm for this HMS optical fiber gas sensor based on double-layered WO3@CQDs porous film, which is 6.05 times higher than that of the sensor coated with single-layer WO3@CQDs porous film. In addition, a limit of detection (LOD) reaches 500 ppb. The response time is 11.7 s and the recovery time is 5.72 s. Density functional theory (DFT) results show that the modification of CQDs improves the adsorption capacity of WO3@CQDs for 2-butanone gas molecules and changes the refractive index of the material. The sensor has the advantages of small volume, high sensitivity and a low LOD, which is of great significance for the detection of trace 2-butanone gas.

YOLOGAS: An Intelligent Gas Leakage Source Detection Method Based on Optical Gas Imaging

YOLOGAS: An Intelligent Gas Leakage Source Detection Method Based on Optical Gas Imaging

Highly Sensitive Gas Pressure Sensing with Temperature Monitoring Using a Slightly Tapered Fiber with an Inner Micro-Cavity and a Micro-Channel.

A highly sensitive optical fiber gas pressure sensor with temperature monitoring is proposed and demonstrated. It is based on a slightly tapered fiber with an inner micro-cavity forming an in-fiber Mach-Zehnder interferometer (MZI), and a micro-channel is drilled into the lateral wall of the in-fiber micro-cavity using a femtosecond laser to allow gas to flow in. Due to the dependence of the refractive index (RI) of air inside the micro-cavity on its gas pressure and the high RI sensitivity of the MZI, the device is extremely sensitive to gas pressure. To prevent fiber breakage, the MZI is housed in a silicate capillary tube with an air inlet. Multiple modes are excited by slightly tapering the inner micro-cavity, and the resonance dips in the sensor's transmission spectrum feature different linear gas pressure and temperature responses, so a sensitivity matrix algorithm can be used to achieve simultaneous demodulation of two parameters, thus resolving the temperature crosstalk. As expected, the experimental results demonstrated the reliability of the matrix algorithm, with pressure sensitivity reaching up to ~-12.967 nm/MPa and temperature sensitivity of ~89 pm/°C. The features of robust mechanical strength and high air pressure sensitivity with temperature monitoring imply that the proposed sensor has good practical and application prospects.

Ultra-compact dual-channel integrated CO2 infrared gas sensor

Expiratory CO2 concentrations can directly reflect human physiological conditions, and their detection is highly important in the treatment and rehabilitation of critically ill patients. Existing respiratory gas analyzers suffer from large sizes and high power consumption due to the limitations of the internal CO2 sensors, which prevent them from being wearable to track active people. The internal and external interference and sensitivity limitations must be overcome to realize wearable respiratory monitoring applications for CO2 sensors. In this work, an ultra-compact CO2 sensor was developed by integrating a microelectromechanical system emitter and thermopile detectors with an optical gas chamber; the power consumption of the light source and ambient temperature of the thermally sensitive devices were reduced by heat transfer control; the time to reach stabilization of the sensor was shortened; the humidity resistance of the sensor was improved by a dual-channel design; the light loss of the sensor was compensated by improving the optical coupling efficiency, which was combined with the amplitude trimming network to equivalently improve the sensitivity of the sensor. The minimum size of the developed sensor was 12 mm × 6 mm × 4 mm, and the reading error was <4% of the reading from −20 °C to 50 °C. The minimum power consumption of the sensor was ~33 mW, and the response time and recovery time were 10 s (@1 Hz), and the sensor had good humidity resistance, stability, and repeatability. These results indicate that the CO2 sensor developed using this strategy has great potential for wearable respiratory monitoring applications.

Dynamic Wavelength-Selective Diffraction and Absorption with Direct-Patterned Hydrogel Metagrating.

Hydrogel nanophotonic devices exhibit attractive tunable capabilities in structural coloration and optical display. However, current hydrogel-based tunable strategies are mostly based on a single physical mechanism, and it remains a challenge to merge multiple mechanisms for active devices with integrated functionalities. Here, a hydrogel metagrating combining Fabry-Pérot (FP) resonance and diffraction effects is proposed for achieving tunable absorption and dynamic wavelength-selective beam steering. Through exploiting hydrogel shrinkage under electron-beam exposure, a hydrogel nanocavity composed of Ag/Hydrogel/Ag three-layer films can be directly printed with arbitrary patterns, enabling the direct-pattering technique of metagrating. The hydrogel nanocavity performs as an FP-type absorber, and its absorption peak rapidly shifts with humidity variation due to the hydrogel layer scaling. The response speed is <320ms, and the absorption peak shift range is >150nm. It is further demonstrated that the hydrogel metagrating exclusively deflects light at the resonance wavelength, and its operating wavelength can be actively switched by regulating ambient humidity. The proposed tunable hydrogel metagrating can promote new technologies of tunable metasurfaces for optical filtering, gas sensing, and optical imaging.

Sol-Gel Pt-VO2 Films as Selective Chemoresistive and Optical H2 Gas Sensors.

In this work, VO2 (M1/R) thin films were exploited as H2 gas sensors. A flat film morphology, obtained by furnace annealing, was compared with a laser-induced nanostructured one. The combination of the environmentally friendly sol-gel approach with the ultrafast laser crystallization allows for significant reductions in energy consumption and related emissions during the fabrication of VO2 sensors. By decorating the sensors' surface with Pt nanoparticles (NPs), the sensor response was enhanced exploiting the hydrogen spillover effect. The Pt/VO2 sensors, tested at operating temperatures between 20 and 200 °C and for concentration of H2 from few ppm to 50000 ppm, offered a dual chemoresistive and optical sensing mode. Low operating temperatures of 150 °C were achieved, along with a detection limit as low as 2 ppm and a perfect baseline recovery. Both sensors guaranteed specific selectivity toward H2, without response to NO2 or humidity, and long-term stability over 500 h. The H2 sensing mechanism, for both the monoclinic and rutile VO2 phases, was investigated through in operando X-ray Diffraction and in situ X-ray Photoelectron Spectroscopy tests. The interaction was found to be based on the reversible formation of HxVO2 bronze, along with the reversible variations in the oxidation state of V.

Study of Neural Network Architectures for Determining Gas Concentrations by Spectra

A study of a number of neural networks of different architectures for determining gas concentrations from spectra obtained using an optical emission gas analyzer, which measures the spectrum of electromagnetic radiation emitted by gases when excited by an electric discharge, is presented. The neural network is trained on data from the optical spectroscopy laboratory and is able to predict gas concentrations from spectra at high speed. The research concerned the deep neural network architectures with convolutional and recurrent layers. Convolutional layers highlight the features of the spectra, while recurrent layers take into account the consistent structure of the data. The quality of the neural network is evaluated by the R2 coefficient of determination, and the comparison between networks by the RMSE indicator between the predicted and real gas concentrations.

Developing Specific Emission Factors for Natural Gas Driven Pneumatic Devices.

A measurement study was conducted in 2023 to derive operator-specific emission factors for natural gas driven pneumatic devices at onshore production facilities in the United States. A total of 369 intermittent bleed and 26 continuous low-bleed pneumatic devices were measured using a high-volume sampler. Considering all intermittent bleed devices, the emission factor from this study was statistically lower than the factor in the revised Greenhouse Gas Reporting Rule (GHGRP) issued May 6, 2024. Intermittent devices were classified by inspection with an optical gas imaging camera as functioning or malfunctioning. Measurements of functioning intermittent bleed devices were statistically higher while measurements of malfunctioning intermittent bleed devices were statistically lower than the corresponding emission factor in the final revisions to the GHGRP. Measurements of continuous low-bleed pneumatic devices were statistically lower than the updated factor in the final revisions to GHGRP. Additionally, a Monte Carlo analysis was conducted to investigate the potential impact of measurement duration and sample size on emission factors derived for intermittent bleed devices. We conclude that while a short measurement duration may miss actuations of properly operating devices with low vent frequencies, potentially resulting in an emission factor with low bias, the sample size of greater than 300 measurements each greater than 3 min in duration, as included in this study, is unlikely to be biased low in a statistically significant manner, particularly when one considers the material contribution of malfunctioning devices.

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.

Ultrasensitive Mid-Infrared Optical Gas Sensor Based on Germanium-on-Insulator Photonic Circuits with Limit-of-Detection at Sub-ppm Level

Ultrasensitive Mid-Infrared Optical Gas Sensor Based on Germanium-on-Insulator Photonic Circuits with Limit-of-Detection at Sub-ppm Level

Miniature optical fiber photoacoustic spectroscopy gas sensor based on a 3D micro-printed planar-spiral spring optomechanical resonator

Photoacoustic spectroscopy (PAS) gas sensors based on optomechanical resonators (OMRs) have garnered significant attention for ultrasensitive trace-gas detection. However, a major challenge lies in balancing small size with high performance when developing ultrasensitive miniaturized optomechanical resonant PAS (OMR-PAS) gas sensors for space-constrained applications. Here, we present a miniature optical fiber PAS gas sensor based on a planar-spiral spring OMR (PSS-OMR) that is in situ 3D micro-printed on the end-face of a fiber-optic ferrule. Experimental results demonstrate that mechanical vibrational resonance can enhance the sensor's acoustic sensitivity by over two orders of magnitude. Together with a 1.4 μL non-resonant photoacoustic cell, it can detect C2H2 gas concentration at the 45-ppb level, and its response is very fast approximating 0.2seconds. This optical fiber OMR-PAS gas sensor holds great promise for the detection or monitoring of rapidly varying trace gas in many applications ranging from production process control to industrial environmental surveillance.

Methane Detection using Optical Gas Imaging: Passive Infrared Technology

Methane Detection using Optical Gas Imaging: Passive Infrared Technology

Single ZnO Nanowire for Electrical and Optical NO2 Gas Sensing: Origin of Reversible and Irreversible Gas Effects Investigated by Photoluminescence Spectroscopy.

In this work, the gas sensing properties of a single ZnO nanowire (NW) are investigated, simultaneously in terms of photoluminescence (PL) and photocurrent (PC) response to NO2 gas, with the purpose of giving new insights on the gas sensing mechanism of a single 1D ZnO nanostructure. A single ZnO NW sensing device was fabricated, characterized, and compared with a sample made of bundles of ZnO NWs. UV near-band-edge PL emission spectroscopy was carried out at room temperature and by lowering the temperature down to 77 K, which allows detection of resolved PL peaks related to different excitonic transition regions. Surface effects were observed in PL maps, considering different nano and microstructures. Electrical and optical measurements were acquired at the same time during the NO2 gas exposure, allowing for the comparison of PL and PC response times and signal recovery. During NO2 gas desorption, irreversible behavior in the surface-related and donor-acceptor pair (DAP) regions is interpreted as the effect of an initial transient when electronic transfer from the gas molecules to the bulk occurs through the ZnO NW surface which acts as a channel. To the best of our knowledge, this is the first work which investigates the simultaneous PL optical and PC electrical response signals of a single ZnO NW to gas exposure.

Optical chemical gas sensor based on spectral autocorrelation: A method for online detection of nitric oxide and ammonia in exhaled breath

The detection of nitric oxide (NO) and ammonia (NH3) in exhaled breath (EB) plays a crucial role in non-invasive diagnosis of airway inflammatory and kidney diseases. Here we report an optical chemical gas sensor for NO and NH3 based on spectral autocorrelation. In our sensor system, the target gas is removed through a chemical reaction with a sensing material and the spectrum of the target gas is extracted from the spectra obtained before and after the reaction by autocorrelation. Our method focuses on the ability of the material to eliminate the target gas without the need for detecting signals of the reaction, greatly relaxing the requirements on material properties. Fundamentally different from optical sensors that obtain spectra by spectral decoupling, our sensor relies on autocorrelation operation to acquire the spectrum of the target gas, thereby overcoming spectra overlap. Lab-based results show that the sensor enables detection of NO (2.28–451.82 ppb) and NH3 (11.52–12,725.42 ppb) with mean absolute errors (MAEs) of 0.79 ppb and 6.13 ppb and measurement accuracies of 0.8 % and 1.4 %, respectively. The EB experiment proves that the sensor can detect exhaled NO and NH3 and distinguish EB between healthy subjects and simulated patients.

Enhanced sensing properties of optical ammonia sensor based on electrospun fibers containing Eosin-Y and silver nanoparticles

This study presents a highly sensitive fluorescence intensity-based gas sensor specifically designed to detect ammonia. Eosin-Y fluorescent dye and silver nanoparticles are incorporated into` cellulose acetate to fabricate fibers membrane using the electrospinning technique, which serves as the foundation for the optical ammonia sensors. Afterward, this sensor is illuminated by a 405 nm LED for monitoring purposes, resulting in changes to both intensity and wavelength. The sensitivity of the optical ammonia sensor is evaluated by comparing the fluorescence intensity recorded for pure nitrogen with that for 1000 ppm ammonia, expressed as the ratio I0/I1000 ppm. The sensor's ability to detect ammonia is evaluated based on the differences in fluorescence intensities between nitrogen and ammonia environments. The proposed optical ammonia gas sensor utilizes Eosin-Y molecules as indicator compounds. Notably, the sensor, constructed from an electrospun fiber membrane, demonstrates an exceptional response of 50.9 at 1000 ppm in an ammonia gas environment at room temperature, representing the highest response achieved to date in an ammonia gas sensor utilizing Eosin-Y molecules. Experimental findings highlight the enhanced sensitivity of the proposed Eosin-Y-containing electrospun fibers compared to traditional Eosin-Y-based dyes for optical ammonia sensing. The development of an optical ammonia sensor utilizing electrospun fibers embedded with fluorescent dye presents a promising opportunity, offering practical applicability due to its cost-effectiveness and straightforward manufacturing process. Finally, the innovative optical ammonia sensor approach can be applied across various fields, including environmental, industrial, and medical applications.

Hydrogen isotopic ratio by residual gas analysis during the JET DT campaigns

Abstract The analysis of hydrogen isotope content is crucial for understanding the operation of fusion devices. Hydrogen isotopic analysis in the core and plasma edge is conducted through neutron and spectroscopic diagnostics. In the case of exhaust gas, mass spectrometry is employed using residual gas analyzers (RGAs), along with optical gas analysis (OGA) utilizing an optical Penning gauge. The use of traditional quadrupole mass spectrometers for RGA encounters challenges during discharges with tritium gas due to signal overlap of different hydrogen molecules at the same mass number. This paper introduces a novel technique to address this issue through a cross-related analysis of RGA data with OGA results. Another consideration in mass spectrometry analysis is the instrument’s varying sensitivity concerning the gas mass number. The paper includes gas calibration data results for all the quadrupoles used in the JET gas analysis. Hydrogen isotopic ratios are calculated from RGA detected currents using simple formulas. The results of this procedure are presented for selected DT JET discharges in relation to the JET pulse time, and they are compared with corresponding optical data. Time-averaged hydrogen isotopic ratio values are computed for numerous discharges during the DT and T campaigns.

Design of an optical gas sensor based on chalcogenide (ChG) glass platform in the mid-infrared for detection of CO2 and CO

Design of an optical gas sensor based on chalcogenide (ChG) glass platform in the mid-infrared for detection of CO2 and CO

Laser-Induced Periodic Surface Structures and Their Application for Gas Sensing.

Semiconducting metal oxides are widely used for solar cells, photo-catalysis, bio-active materials and gas sensors. Besides the material properties of the semiconductor being used, the specific surface topology of the sensors determines device performance. This study presents different approaches for increasing the sensing area of semiconducting metal oxide gas sensors. Micro- and nanopatterned laser-induced periodic surface structures (LIPSSs) are generated on silicon, Si/SiO2 and glass substrates. The surface morphologies of the fabricated samples are examined by FE SEM. We selected the nanostructuring and characterization of nanostructured source Ni/Au and Ti/Au films prepared on glass using laser ablation as the most suitable of the investigated approaches. Surface structures produced on glass by backside ablation provide 100 nm features with a high surface area; they are also transparent and have high resistivity. The value of the hydrogen sensitivity in the range concentrations from 100 to 500 ppm was recorded using transmittance measurements to be twice as great for the nanostructured target TiO2/Au as compared to the NiO/Au. It was found that such transparent materials present additional possibilities for producing optical gas sensors.