Multipass Gas Cell Research Articles

Calibration-free infrared absorption spectroscopy using cantilever-enhanced photoacoustic detection of the optical power

We report on sensitive tunable laser absorption spectroscopy using a multipass gas cell and a solid-state photoacoustic optical power detector. Unlike photoacoustic spectroscopy (PAS), this method readily allows a low gas pressure for high spectral selectivity and a free gas flow for continuous measurements. Our photoacoustic optical power detector has a large linear dynamic range and can be used at almost any optical wavelength, including the middle infrared and THz regions that are challenging to cover with traditional optical detectors. Furthermore, our approach allows for compensation of laser power drifts with a single detector. As a proof of concept, we have measured very weak CO2 absorption lines at 9.2 µm wavelength and achieved a normalized noise equivalent absorption (NNEA) of 2.35·10−9 Wcm−1Hz−1/2 with a low-power quantum cascade laser. The absolute value of the gas absorption coefficient is obtained directly from the Beer-Lambert law, making the technique calibration-free.

A hybrid learning approach to better classify exhaled breath's infrared spectra: A noninvasive optical diagnosis for socially significant diseases.

Early diagnosis is crucial for effective treatment of socially significant diseases, such as type 1 diabetes mellitus (T1DM), pneumonia, and asthma. This study employs a diagnostic method based on infrared laser spectroscopy of human exhaled breath. The experimental setup comprises a quantum cascade laser, which emits in a pulsed mode with a peak power of up to 150 mW in the spectral range of 5.3-12.8 μm (780-1890 cm-1), and a Herriott multipass gas cell with a specific optical path length of 76 m. Using this setup, spectra of exhaled breath in the mid-infrared range were obtained from 165 volunteers, including healthy individuals, patients with T1DM, asthma, and pneumonia. The study proposes a hybrid approach for classifying these spectra, utilizing a variational autoencoder for dimensionality reduction and a support vector machine method for classification. The results demonstrate that the proposed hybrid approach outperforms other machine learning method combinations.

Triple-range adjustable plane-concave multipass gas cell for high-precision trace gas detection based on TDLAS

A triple-range adjustable plane-concave multipass gas cell (PC-MPGC) was developed for high-precision trace gas detection based on tunable diode laser absorption spectroscopy. Effective optical path lengths (EOPLs) of 64.5, 42.5, and 20.5 m could be easily achieved by adjusting the incident beam angle. The trace gas sensor system employed a 1.653 µm distributed feedback diode laser to target a strong methane (CH4) absorption line, and direct absorption spectroscopy (DAS) was used to evaluate the performance of the system with a 64.5 m EOPL. A Savitzky–Golay filtering algorithm was employed to denoise the measured signal, and a third harmonic signal was used for laser frequency locking. A signal-to-noise ratio (SNR) of 191 was achieved, which corresponds to a detection sensitivity of 0.78 ppmv. The system response time was obtained through measurement of CH4 at concentration of 0 ppmv and 20 ppmv at 298 K and 1 atm, and it was found to be 11 s. Kalman filtering was applied to improve the detection sensitivity of the gas sensor. The stability of the system was analyzed using Allan deviation, and a minimum detectable limit of 21 ppbv was obtained for an integration time of 580 s. In situ continuous monitoring of atmospheric CH4 characteristics was performed for 72-h. The development of a new type of PC-MPGC paves the way for the detection of multicomponent gases at different absorption path lengths.

A neural network filter based high-sensitive MIR CO2 sensor

A low-power consumption, small-size and high measurement sensitivity mid-infrared (MIR) carbon dioxide (CO2) sensor was developed based on wavelength modulation spectroscopy (WMS) technology, utilizing a mid-infrared distributed feedback interband cascade laser (DFB-ICL) operating around 2682 nm. The sensor incorporated two key components, a home-made multi-pass gas cell with base length of 10 cm achieving 1.5 m optical path and a highly integrated FPGA board, which were used to reduce the size of the sensor. A novel second harmonic-neural network filter (SH-NNF) was also proposed and implemented in this sensor. The sensor’s performance was evaluated through a 20 mins continuous experiment using calibrated gas with 500 ppm concentration. The results, before and after SH-NNF, demonstrated an improvement in sensitivity and detection precision from 1.68 ppm (1 σ) to 1.17 ppm and from 2.14 ppm to 1.45 ppm, respectively. The optimum limit of detection of 0.392 ppm with integration time of 218 s was obtained. The ppm detection and compact characteristics of the developed MIR sensor show its potential for detecting CO2 in the ambient air.

Enhanced performance for simultaneous atmospheric N2O and CO measurements based on ICEEMDAN and GWO-LSSVM

A TDLAS-based sensor for simultaneous detection of N2O and CO has been developed by us, which is capable of monitoring the concentrations of both gases in real time with high stability and detection accuracy. Two distributed feedback (DFB) were deployed as laser sources, a 20 m multi-pass gas cell (MPGC) was installed for absorption, an InGaAs detector was used to receive the optical signals and graphical user interface (GUI) were designed based on the microcontroller. The modulation depth curves were obtained experimentally to obtain the lowest measured concentration. Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN) was employed to increase signal-to-noise ratio (SNR) of the signals and GWO-LSSVM was performed to invert concentrations. The linearity of the sensor was analyzed by linearity experiments, which obtained the linearity of the sensor for N2O and CO, with linear correlation coefficients (R2) of 0.9990 and 0.998, respectively. The detection accuracy of the sensor was verified and the relative errors of the sensor were all less than 3.59 %. The stability and anti-interference ability of the sensor were verified, it was found that the standard deviation (SD) of N2O and CO measured by the sensor was 47.27 ppb and 48.31 ppb respectively. The limit of detection (LoD) for N2O and CO are 8.37 ppb and 5.91 ppb, respectively according to Allan-Werle deviation. The sensor has good performance in simultaneous detection of N2O and CO.

Near-infrared wide-range dual-gas sensor system for simultaneous detection of methane and carbon monoxide in coal mine environment

To effectively monitor gas explosion and coal spontaneous combustion in coal mine, an intrinsically safe and explosion-proof dual-gas sensor system was developed for methane (CH4) and carbon monoxide (CO) measurement. A distributed feedback (DFB) laser was used to scan two adjacent absorption lines (CH4: 4284.51 cm−1, CO: 4285.01 cm−1). Two measurement ranges of 0–500 parts per million by volume (ppmv) and 0–300,000 ppmv for CH4 and 0–100 ppmv and 0–4000 ppmv for CO were realized using a ∼25 cm single-pass gas cell (SPGC) and a ∼25 m multi-pass gas cell (MPGC), respectively. A gas pre-treatment module was used to remove moisture and aerosols from gas samples. A temperature compensation algorithm was adopted to deal with ambient temperature change. Based on the Allan deviation analysis, the limit of detection (LoD) of CH4 is 0.19 ppmv and the LoD of CO is 0.12 ppmv, respectively, at an averaging time of 0.5 s. A continuous two-day CH4 measurement was performed to demonstrate the long-term stability and environmental monitoring capability. The sensor system was successfully deployed in coal mine gas analysis at Longjiapu, Changchun City, China.

Water vapor detection based on three-line TDLAS with a continuous wave quantum cascade laser

Water vapor is an important gas species in atmosphere. In this work, we present a three-line tunable diode laser absorption spectroscopy (TDLAS) gas sensor for water vapor detection based on direct absorption spectroscopy. A continuous wave quantum cascade laser (QCL) is employed as the light source with a wavelength near 7.15 µm. The output wavelength of the QCL is tuned to scan across three absorption lines of water vapor simultaneously in the detection. A detection limit of 10.7 ppm v (parts per million by volume) is obtained in 30-s integration time with a 40 cm gas cell. This detection limit could be further improved if wavelength modulation spectroscopy (WMS) or a multi-pass gas cell is introduced to the system.

Mid-infrared carbon isotope spectrum logging system combined with a thermostat of optical subsystem for high-precision detection of isotope ratio

In the process of oil and gas exploration and development, carbon isotope ratio can reflect the maturity of oil and gas and predict the recovery factor, and the isotope ratio in the composition of shale gas is particularly important. Thus, a carbon isotope spectrum logging system was designed and exploited based on tunable diode laser absorption spectroscopy (TDLAS) technology under the fundamental frequency absorption band of 12CO2 and 13CO2 molecules, and a quantum cascade laser (QCL) with center wavelength of 4.35 μm was applied. For further detection sensitivity, wavelength modulation spectroscopy (WMS) technology was combined to suppress background noise through the modulation of QCL. A multi-pass gas cell (MPGC) with an optical path length of 41 m was utilized for lower limit of detection (LoD). In order to suppress the temperature dependence of the absorption spectrum, the optical subsystem was placed in a high-precision thermostat to maintain a stable temperature, so as to achieve high-precision and high-stability detection. Meanwhile, sparrow search algorithm-back propagation (SSA-BP) was applied for concentration prediction of 12CO2 and 13CO2. Taking advantage of the excellent optimization ability, fast convergence speed and high stability of SSA, the problem that BP neural network algorithm is highly dependent on initial value can be solved to some extent. Sensor performance was validated through calibration and stability experiments. The LoD of 12CO2 reached a minimum of 0.618 parts-per-billion (ppb) with an 88 s averaging time, and the LoD of 13CO2 reached 0.181 ppb when the averaging time was 96 s. Besides, the standard deviation of carbon isotope ratio obtained by this system was ∼ 0.61 ‰. The results illustrate that this self-developed sensor has a bright prospect in the field of shale gas isotope detection.

Development of a Stable Oxygen Sensor Using a 761 nm DFB Laser and Multi-Pass Absorption Spectroscopy for Field Measurements.

An optical sensor system based on wavelength modulation spectroscopy (WMS) was developed for atmospheric oxygen (O2) detection. A distributed feedback (DFB) laser with butterfly packaging was used to target the O2 absorption line at 760.89 nm. A compact multi-pass gas cell was employed to increase the effective absorption length to 3.3 m. To ensure the stability and anti-interference capability of the sensor in field measurements, the optical module was fabricated with isolation of ambient light and vibration design. A 1f normalized 2f WMS (WMS-2f/1f) technique was adopted to reduce the effect of laser power drift. In addition, a LabVIEW-based dual-channel lock-in amplifier was developed for harmonic detection, which significantly reduced the sensor volume and cost. The detailed detection principle was described, and a theoretical model was established to verify the effectiveness of the technique. Experiments were carried out to obtain the device's sensing performances. An Allan deviation analysis yielded a minimum detection limit of 0.054% for 1 s integration time that can be further improved to 0.009% at ~60 s. Finally, the reliability and anti-interference capability of the sensor system were verified by the atmospheric O2 monitoring.

A near-infrared multi-gas sensor based on IWTD-CEEMDAN and WOA-BiLSTM for detection of CH4 and NH3 leaked in industrial production

A multi-gas trace sensor based on tunable diode laser absorption spectroscopy (TDLAS) with two distributed feedback (DFB) lasers is designed, which was applied to measure methane (CH4) and ammonia (NH3) leaked in industrial production. The multi-frequency synchronous modulation strategy was used to drive two lasers simultaneously, where the lasers have a central wavelength of 1653.7 nm and 1512.2 nm, corresponding to the target absorption lines of CH4 and NH3 respectively. A miniaturized multi-pass gas cell (MPGC) is used as the gas absorption cell. Improved wavelet threshold denoising algorithm based on complete ensemble empirical mode decomposition with the adaptive noise (IWTD-CEEMDAN) is applied to improve the SNR of the spectral signals, and the signal-to-noise ratio (SNR) could be enhanced by approximately 26.34 dB. The concentration of CH4 and NH3 is inverted by whale optimization algorithm–bidirectional long short-term memory (WOA-BiLSTM) with a root-mean-square error (RMSE) of 0.691 ppb and 0.111 ppb respectively. The linearity, stability and response time were verified and the determination coefficients (R2) were 0.9994 and 0.9992 for CH4 and NH3. The response time of the sensor is 4.8 s, which satisfies the real-time detection demands and has the RMSE of 43.24 ppb and 11.83 ppb respectively. The limit of detection (LoD) for CH4 is 6.69 ppb with 212 s integration time, and the LoD for NH3 is 3.78 ppb with 36 s integration time, which is obtained by Allan-Werle deviation. The measurement results of CH4 and NH3 concentrations in atmosphere indicate that the sensors provide a reliable method for simultaneous real-time detection of multiple leaking gases.

Mid-infrared acetone sensor for exhaled gas using FWA-LSSVM and empirical mode decomposition algorithm

The acetone can be regarded as one of the respiratory biomarkers for lung cancer, the detection of acetone in human exhaled gas has great important for early lung cancer screening. Based on Tunable Diode Laser Absorption Spectroscopy (TDLAS), a system for detecting acetone in exhaled gas has been developed, a multi-pass gas cell (MPGC), which has a 76 m effective absorption optical path, as well as a 7.32 μm quantum cascade laser (QCL) were adopted in the detection system. In order to confirm the function of the system, a gas distribution station equipped with standard concentrations of acetone was used. Empirical mode decomposition (EMD) algorithm as a spectral pre-processing algorithm was implemented to reduce the noise from the second harmonic signal (2f signal), using an orthogonal lock-in amplifier based on LabVIEW to demodulate the detector signal. Fireworks algorithm with the least squares support vector machine (FWA-LSSVM) was designed to improve the accuracy and sensitivity of acetone gas concentration inversion. The limits of detection (LoD) of the sensor system can be found the middle value of up to ∼ 21.4 parts per billion (ppb) with a 78 s integration time by Allan-Werle deviation analysis. The exhaled breath experiment showed that the sensor provides a promising way for the detection of acetone in human exhaled breath.

Fast gas sensing scheme with multi-component gas measurement capacity based on non-dispersive frequency comb spectroscopy (ND-FCS).

A fast gas sensing scheme based on a non-dispersive frequency comb spectroscopy (ND-FCS) is proposed and experimentally demonstrated. Its capacity for multi-component gas measurement is experimentally investigated as well, by using the time-division-multiplexing (TDM) method to realize specific wavelength selection of the fiber laser optical frequency comb (OFC). A dual-channel optical fiber sensing scheme is established with a sensing path consisting of a multi-pass gas cell (MPGC), and a reference path with a calibrated signal to track the repetition frequency drift of the OFC for a real-time lock-in compensation and system stabilization. The long-term stability evaluation and the simultaneous dynamic monitoring are carried out, with the target gases of ammonia (NH3), carbon monoxide (CO) and carbon dioxide (CO2). The fast CO2 detection in human breath is also conducted. The experimental results show that at an integration time of 10 ms, the detection limits of the three species are evaluated to be 0.0048%, 0.1869% and 0.0467%, respectively. A low minimum detectable absorbance (MDA) down to 2.8 × 10-4 can be achieved and a dynamic response with millisecond time can be realized. Our proposed ND-FCS exhibits excellent gas sensing performance with merits of high sensitivity, fast response and long-term stability. It also shows great potential for multi-component gas monitoring in atmospheric monitoring applications.

An Ultrahigh-Sensitivity and Wide-Range Measurement System of Dissolved CO2 for Deep-Sea Nature Gas Hydrates Exploration

A compact and high-sensitivity sensing system is required for the exploration of natural gas hydrates (NGHs) to measure dissolved CO2 in seawater. In this study, a mid-infrared (MIR) CO2-sensing system was investigated by wavelength modulation spectroscopy (WMS). The system contained an interband cascade laser (ICL) operating in MIR wavelength, an optical multipass gas cell (MPGC), and an MIR mercury cadmium telluride detector. A combination of three absorption lines was utilized to achieve measurement with a wide CO2-concentration range. Additionally, we proposed and introduced in detail a method of optimizing the operating temperature, pressure, and modulation depth. The optimum minimum detection limit (MDL) of 11 ppbv was achieved when the integration time was 145 s. In the northern South China Sea, a deep-sea test was performed, and the test results validated the satisfactory performance of the sensing system for deep-sea NGH exploration.

Smoldering peat fire detection by time-resolved measurements of transient CO2 and CH4 emissions using a novel dual-gas optical sensor

A compact and sensitive dual-gas laser absorption sensor was developed for smoldering peat fire detection by real-time monitoring of transient CO2 and CH4 emissions from peat combustion exhaust. The sensor combines two infrared lasers to exploit CH4 and CO2 absorption lines centered at 6057.09 cm−1 and 6359.96 cm−1, respectively. Scanned-wavelength modulation spectroscopy with the second-harmonic detection (WMS-2f) and a custom-designed Herriot multipass gas cell (10.3 m path length in a 40.5 mL volume) were employed to improve detection sensitivity. The simultaneous real-time transient emissions (CH4 and CO2) were measured at an interval of 0.1 s under various smoldering peat combustion conditions in a top open cylindrical reactor. An increasing trend of CH4/CO2 ratio from 0.053 to 0.075 and the greenhouse gas (GHG) flux from 1.5 g/m2 s to 3.4 g/m2 s was observed with increasing oxygen supplies from 10 mm/s to 24 mm/s. However, a decreasing trend of CH4/CO2 ratio from 0.06 to 0.043 and GHG flux from 2.6 g/m2 s to 0.4 g/m2 s was noticed with increasing peat moisture content from 8% (dry peat) to 100%. The measurement results agree well with commercial non-dispersive infrared CO2 and CH4 analyzers which are not fast enough to capture transient emissions due to their low time response. The developed dual-gas sensor has the potential to be applied for detecting underground peatland fires and evaluating the overall GHGs emissions from smoldering wildfires due to its excellent temporal resolution, hardware simplicity, and compactness.

Highly Sensitive Hydrogen Sensing Based on Tunable Diode Laser Absorption Spectroscopy with a 2.1 μm Diode Laser

As a new form of energy, hydrogen (H2) has clean and green features, and the detection of H2 has been a hot topic in recent years. However, the lack of suitable laser sources and the weak optical absorption of H2 limit the research concerning its detection. In this study, a continuous-wave distributed feedback (CW-DFB) diode laser was employed for sensing H2. Tunable diode laser absorption spectroscopy (TDLAS) was adopted as the detection technique. The strongest H2 absorption line, located at 4712.90 cm−1 (2121.83 nm, line strength: 3.19 × 10−26 cm−1/cm−2 × molec), was selected. We propose a H2-TDLAS sensor based on the wavelength modulation spectroscopy (WMS) technique and a Herriott multipass gas cell (HMPC) with an optical length of 10.13 m to achieve a sensitive detection. The WMS technique and second harmonic (2f) demodulation technique were utilized to suppress system noise and simplify the data processing. The 2f signal of the H2-TDLAS sensor, with respect to different H2 concentrations, was measured when the laser wavelength modulation depth was at the optimal value of 0.016 cm−1. The system’s signal-to-noise ratio (SNR) and minimum detection limit (MDL) were improved from 248.02 and 0.40% to 509.55 and 0.20%, respectively, by applying Daubechies (DB) wavelet denoising, resulting in 10 vanishing moments. The Allan variance was calculated, and the optimum MDL of 522.02 ppm was obtained when the integration time of the system was 36 s.

High Sensitivity Monitoring of VOCs in Air through FTIR Spectroscopy Using a Multipass Gas Cell Setup.

Human exposure to Volatile Organic Compounds (VOCs) and their presence in indoor and working environments is recognized as a serious health risk, causing impairments of varying severities. Different detecting systems able to monitor VOCs are available in the market; however, they have significant limitations for both sensitivity and chemical discrimination capability. During the last years we studied systematically the use of Fourier Transform Infrared (FTIR) spectroscopy as an alternative, powerful tool for quantifying VOCs in air. We calibrated the method for a set of compounds (styrene, acetone, ethanol and isopropanol) by using both laboratory and portable infrared spectrometers. The aim was to develop a new, and highly sensitive sensor system for VOCs monitoring. In this paper, we improved the setup performance, testing the feasibility of using a multipass cell with the aim of extending the sensitivity of our system down to the part per million (ppm) level. Considering that multipass cells are now also available for portable instruments, this study opens the road for the design of new high-resolution devices for environmental monitoring.

Performance of a Mid-Infrared Sensor for Simultaneous Trace Detection of Atmospheric CO and N2O Based on PSO-KELM.

In this article, a field deployable sensor was developed using a self-developed 4.58-µm continuous wave quantum cascade laser (CW-QCL) for the simultaneous detection of carbon monoxide (CO) and nitrous oxide (N2O), both of which have strong fundamental absorption bands in this waveband. The sensor is based on tunable diode laser absorption spectroscopy (TDLAS) technology, which combined a multi-pass gas cell (MPGC) with a 41 m optical path length to achieve high-precision detection. Meanwhile, the particle swarm optimization-kernel extreme learning machine (PSO-KELM) algorithm was applied for CO and N2O concentration prediction. In addition, the self-designed board-level QCL driver circuit and harmonic signal demodulation circuit reduce the sensor cost and size. A series of validation experiments were conducted to verify the sensor performance, and experiments showed that the concentration prediction results of the PSO-KELM algorithm are better than those of the commonly used back propagation (BP) neural networks and partial least regression (PLS), with the smallest root mean square error (RMSE) and linear correlation coefficient closest to 1, which improves the detection precision of the sensor. The limit of detection (LoD) was assessed to be 0.25 parts per billion (ppb) for CO and 0.27 ppb for N2O at the averaging time of 24 and 38 s. Field deployment of the sensor was reported for simultaneous detection of CO and N2O in the air.

Performance enhancement of a near-infrared NH3 sensor based on PSO-LSSVM for denitrification industrial process

A near-infrared NH3 sensor based on a 1512 nm distributed feedback (DFB) laser was designed to perform real-time and online detection of NH3 in the industrial denitrification. A miniaturized multi-pass gas cell (MPGC) is utilized as a site for infrared laser-gas interaction, in which the infrared light is reflected back and forth 76 times within the MPGC, with an effective optical path length of 20 m. High-precision concentration inversion of the detected second harmonic (2f) signals at both high and low concentrations was performed by the particle swarm optimization-least squares support vector machine (PSO-LSSVM) algorithm, and the linear correlation coefficient R2 between the standard and measured concentrations could be as high as 0.9999 or later in both cases. The sensor was tested for stability for 1 h and its Allan -Werle deviation was analyzed. The minimum limit of detection (LoD) of the sensor is 3.95 ppb at an averaging time of 38 s. An outdoors deployment of the sensor was reported for detection of the leaking NH3 in Laboratory Building.

Simultaneous methane and acetylene detection using frequency-division multiplexed laser absorption spectroscopy

A dual-gas optical sensor was developed using frequency-division multiplexed (FDM) scanned-wavelength modulation spectroscopy for simultaneous detection of methane (CH4) and acetylene (C2H2). Two infrared lasers were combined to exploit C2H2 and CH4 absorption lines centered at 6539.45 cm−1 and 6057.09 cm−1, respectively. Scanned-WMS with the second-harmonic detection (WMS-2f) and a compact astigmatic multipass gas cell (36-m path length in a 0.3 L volume) were employed to improve detection sensitivity. Simultaneous dual-gas detection was realized by modulating each laser at a different frequency (5 kHz for 1529 nm and 13 kHz for 1650 nm) and software lock-in amplifiers were used to obtain the corresponding WMS-2f signals from a single photodetector. The Allan deviation analysis was performed to assess the long-term stability and minimum detection limit (MDL) of the sensor system. The MDL of 0.92 ppm for CH4 and 0.64 ppm for C2H2 was achieved at 0.02-s integration time, which can be further improved to 55 ppb for CH4 and 10 ppb for C2H2 at an optimum integration time of 10-s and 15-s, respectively. Such a dual-gas sensor has a promising potential for detecting dissolved gases (CH4 and C2H2) in transformer oil for fault diagnosis due to its high sensitivity, hardware simplicity, and fast temporal resolution.

Deep Learning for Type 1 Diabetes Mellitus Diagnosis Using Infrared Quantum Cascade Laser Spectroscopy.

An estimated 10.5% of the world’s population aged 20–79 years are currently living with diabetes in 2021. An urgent task is to develop a non-invasive express-diagnostics of diabetes with high accuracy. Type 1 diabetes mellitus (T1DM) diagnostic method based on infrared laser spectroscopy of human exhaled breath is described. A quantum cascade laser emitting in a pulsed mode with a peak power of up to 150 mW in the spectral range of 5.3–12.8 μm and Herriot multipass gas cell with an optical path length of 76 m were used. We propose a method for collecting and drying an exhaled human air sample and have measured 1200 infrared exhaled breath spectra from 60 healthy volunteers (the control group) and 60 volunteers with confirmed T1DM (the target group). A 1-D convolutional neural network for the classification of healthy and T1DM volunteers with an accuracy of 99.7%, recall 99.6% and AUC score 99.9% was used. The demonstrated results require clarification on a larger dataset and series of clinical studies and, further, the method can be implemented in routine medical practice.