Frequency-Division-Multiplexed Multicomponent Gas Sensing with Photothermal Spectroscopy and a Single NIR/MIR Fiber-Optic Gas Cell

Current Advances of CO Sensing Based on Low Dimensional Materials

Carbon monoxide (CO) is a harmful gas with significant impacts on human health and the environment. Its timely detection, especially in the event of thermal runaway in automotive lithium batteries, is crucial to prevent casualties. This paper reviews the progress in the development of efficient, sensitive, and reliable CO sensors, focusing on electrochemical, optical, and resistive sensing materials. Low-dimensional materials have a large specific surface area, providing an abundant number of active sites, which has drawn extensive attention from researchers. According to the different sensor signals, we categorized these sensors into electrical and optical signal sensors. We hope that by systematically introducing the sensing mechanism and sensing performance of these two kinds of sensors, appropriate CO sensors can be developed in different application scenarios so as to realize early warning and monitoring to the maximum extent, reduce industrial losses, and ensure the life and health of personnel.

Pressure-Compensated Fiber-Optic Photoacoustic Sensors for Trace SO2 Analysis in Gas Insulation Equipment

A high-sensitivity fiber-optic photoacoustic sensor with pressure compensation is proposed to analyze the decomposition component SO2 in high-pressure gas insulation equipment. The multiple influence mechanism of pressure on photoacoustic excitation and cantilever detection has been theoretically analyzed and verified. In the high-pressure environment, the excited photoacoustic signal is enhanced, which compensates for the loss of sensitivity of the cantilever. A fiber-optic F-P cantilever is utilized to simultaneously measure static pressure and dynamic photoacoustic wave, and a spectral demodulation method based on white light interference is applied to calculate the optical path difference of the F-P interferometer (FPI). The real-time pressure is judged through the linear relationship between the average optical path difference of FPI and the pressure, which gives the proposed fiber-optic photoacoustic sensor the inherent advantages of being uncharged and resistant to electromagnetic interference. The average optical path difference of FPI is positively related to pressure, with a responsivity of 0.6 μm/atm, which is based on changes in the refractive index of gas. In the range of 1-4 atm, the SO2 sensor has a higher detection sensitivity at high-pressure, which benefits from the pressure compensation effect. With the pressure environment of gas insulation equipment at 4 atm as the application background, the SO2 gas is tested. The detection limit is 20 ppb with an averaging time of 400 s.

In Vitro Glucose Measurement from NIR and MIR Spectroscopy: Comprehensive Benchmark of Machine Learning and Filtering Chemometrics

The quantitative analysis of glucose using spectroscopy is a topic of great significance and interest in science and industry. One conundrum in this area is deploying appropriate preprocessing and regression tools. To contribute to addressing this challenge, in this study, we conducted a comprehensive and novel comparative analysis of various machine learning and preprocessing filtering techniques applied to near-infrared, mid-infrared, and a combination of near-infrared and mid-infrared spectroscopy for glucose assay. Our objective was to evaluate the effectiveness of these techniques in accurately predicting glucose levels and to determine which approach was most optimal. Our investigation involved the acquisition of spectral data from samples of glucose solutions using the three aforementioned spectroscopy techniques. The data was subjected to several preprocessing filtering methods, including convolutional moving average, Savitzky-Golay, multiplicative scatter correction, and normalisation. We then applied representative machine learning algorithms from three categories: linear modelling, traditional nonlinear modelling, and artificial neural networks. The evaluation results revealed that linear models exhibited higher predictive accuracy than nonlinear models, whereas artificial neural network models demonstrated comparable performance. Additionally, the comparative analysis of various filtering methods demonstrated that the convolutional moving average and Savitzky-Golay filters yielded the most precise outcomes overall. In conclusion, our study provides valuable insights into the efficacy of different machine learning techniques for glucose measurement and highlights the importance of applying appropriate filtering methods in enhancing predictive accuracy. These findings have important implications for the development of new and improved glucose quantification technologies.

Dense Multibutterfly Spots-Enhanced Miniaturized Optical Fiber Photoacoustic Gas Sensor

A miniaturized optical fiber photoacoustic gas sensor enhanced by dense multibutterfly spots is reported for the first time. The principle of space light transmission of neglecting paraxial approximation is theoretically analyzed for designing a dense multibutterfly spots-based miniature multipass cell. In a multipass photoacoustic tube with a diameter of 16 mm, the light beam is reflected about a hundred times. The light spots on the mirror surfaces at both ends of the photoacoustic tube form a dense multibutterfly distribution. The volume of the micro multipass gas chamber is only 5.3 mL. An optical fiber cantilever based on F-P interference is utilized as a photoacoustic pressure detector. Compared with that of the single-pass structure, the gas detection ability of the photoacoustic system with dense multibutterfly spots is improved by about 50 times. The proposed miniaturized sensor realizes a detection limit of 3.4 ppb for C2H2 gas with an averaging time of 100 s. The recognized coefficients of minimum detectable absorption (αmin) and normalized noise equivalent absorption are 1.9 × 10-8 cm-1 and 8.4 × 10-10 W cm-1 Hz-1/2, respectively.

Fiber-Optic Photoacoustic CO Sensor for Gas Insulation Equipment Monitoring Based on Cantilever Differential Lock-In Amplification and Optical Excitation Enhancement

A fiber-optic photoacoustic CO sensor for gas insulation equipment is proposed, which relies on F-P interferometric cantilever-based differential lock-in amplification and optical multipass excitation enhancement. The sensor has excellent characteristics of high sensitivity, antielectromagnetic interference, fast response, and long-distance detection. The photoacoustic pressure waves in the two resonators of the differential photoacoustic cell (DPAC) are simultaneously detected by two fiber-optic interferometric cantilevers and processed differentially; thereby, the gas flow noise is effectively suppressed. Based on the comprehensive analysis of the superposition of photoacoustic excitation and multipass absorption, the diameter of the resonator is determined to be 6 mm. The optical power emitted by the 1566.6 nm distributed feedback laser is increased to 500 mW by an erbium-doped fiber amplifier. The near-infrared light is reflected 30 times in the multipass cell, which improves the order of magnitude of optical effective excitation. Due to the low sound velocity of SF6 gas, the resonant frequency of the DPAC with a resonator length of 80 mm is 760 Hz. The response time to CO/SF6 gas is 93 s with a flow rate of 500 sccm. The detection limit of the CO sensor is 53 ppb, which realizes the accurate and timely perception of the SF6 decomposition derivative CO and provides technical support for trouble-free operation of gas insulation equipment.

Mid-infrared auto-correction on-chip waveguide gas sensor based on 2f/1f wavelength modulation spectroscopy

Compared to the most commonly used on-chip direct absorption spectroscopy (DAS) gas detection technique, the second harmonic (2f) based on-chip wavelength modulation spectroscopy (WMS) proposed by our group has the faculty to suppress noise and improve performance, but the accuracy of 2f WMS is easily affected by optical power variation. A mid-infrared auto-correction on-chip gas sensor based on 2f/1f WMS was proposed for decreasing the influence of the variation of optical power. The limit of detection of methane (CH4) obtained by a chalcogenide waveguide with a length of 10 mm is 0.031%. Compared with the 2f WMS, the maximum relative concentration error of the auto-correction on-chip gas sensor was decreased by ∼5.6 times. The measurement error is ≤2% in a temperature variation range of 30°C. This auto-correction sensor without a complicated manual calibration is helpful to the high accuracy measurement for on-chip integrated gas sensing.

Mid-infrared optical modulator enabled by photothermal effect

Photothermal effect in a gas-filled hollow-core fiber may result in agile mid-infrared optical modulators for broadband phase modulation and high extinction ratio intensity modulation.