Sensitive acetone detection with a mid-IR interband cascade laser and wavelength modulation spectroscopy

Xia, Jinbao; Zhu, Feng; Kolomenskii, A.A.; Bounds, James; Zhang, Sasa; Amani, Mahmood; Fernyhough, Liam; Schuessler, H. A.

doi:10.1364/osac.2.000640

Cited by 19 publications

(5 citation statements)

References 37 publications

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“…These bands strongly limit the tuneability of PAA-based PCs to the narrow region between 3400 and 5700 nm. Since the absorption bands of many important biosignatures and industrial substances like NO 2 [41], CH 4 [42], acetone [43], ozone [44], as well as chemical warfare agents [45], are located beyond 6000 nm, it is very important to extend the optical transparency of the PAA-based PCs further into MIR spectral region.…”

Section: Introductionmentioning

confidence: 99%

Structural stability and optical properties of 1D photonic crystals based on porous anodic alumina after annealing at different temperatures

et al. 2022

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Porous anodic alumina photonic crystals with a photonic stop-band placed in the mid-infrared spectral region represent a promising approach for increasing of gas sensors sensitivity. An onion-like layered distribution of anionic impurities is a hallmark of porous anodic alumina, and its presence is generally considered to demarcate the boundary between transparent and opaque ranges in the infrared spectral region. Here, we study the effect of annealing in the temperature range of 450–1 100 °C on the structural stability and optical properties in photonic crystals based on porous anodic alumina fabricated by pulse anodization in oxalic acid. Pulse sequences were selected in a way to obtain photonic crystals of different periodic structures with a photonic stop-band located in visible and mid-infrared spectral regions. The first photonic crystal was composed of layers with gradually changing porosity, whereas the second photonic crystal consisted of a sequentially repeated double-layer unit with an abrupt change in porosity. We investigated the response of alumina with rationally designed porosities and different arrangements of porous layers for high-temperature treatment. The microstructure (scanning electron microscopy), phase composition (x-ray diffraction), and optical properties (optical spectroscopy)were analysed to track possible changes after annealing. Both photonic crystals demonstrated an excellent structural stability after 24 hour annealing up to 950 °C. At the same time, the evaporation of the anionic impurities from porous anodic alumina walls caused a shift of the photonic stop-band towards the shorter wavelengths. Furthermore, the annealing at 1 100 °C induced a high transparency (up to 90%) of alumina in mid-infrared spectral region. It was shown thus that properly selected electrochemical and annealing conditions enable the fabrication of porous photonic crystals with the high transparency spanning the spectral range up to around 10 µm.

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Section: Introductionmentioning

confidence: 99%

Structural stability and optical properties of 1D photonic crystals based on porous anodic alumina after annealing at different temperatures

et al. 2022

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“…Разработка новых лазерных источников среднего инфракрасного диапазона, таких как квантовые каскадные лазеры (ККЛ) и межзонные каскадные лазеры, привела к заметному прогрессу в лазерной абсорбционной спектроскопии, что дает большие надежды на развитие метода в биомедицинских приложениях. Это обусловлено высокой селективностью метода лазерной инфракрасной спектроскопии относительно молекул-биомаркеров в среднем инфракрасном диапазоне, а также небольшим размером устройства, которое снижает стоимость «одного измерения» [8,9].…”

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Numerical methods of spectral analysis of multicomponent gas mixtures and human exhaled breath

et al. 2022

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In this paper, the application of machine learning and deep learning in the spectral analysis of multicomponent gas mixtures is considered. The experimental setup consists of a quantum cascade laser with a tuning range of 5.3–12.8 µm, a peak power of up to 150 mW, and an astigmatic Herriott gas cell with an optical path length of up to 76 m. Acetone, ethanol, methanol, and their mixtures are used as test substances. For the detection and clustering of substances, including molecular biomarkers, methods of machine learning, such as stochastic embedding of neighbors with a t-distribution, principal component analysis and classification methods, such as random forest, gradient boosting, and logistic regression, are proposed. A shallow convolutional neural network based on TensorFlow (Google) and Keras is used for the spectral analysis of gas mixtures. Model spectra of substances are used as a training sample, and model and experimental spectra are used as a test sample. It is shown that neural networks trained on model spectra (NIST database) can recognize substances in experimental gas mixtures. We propose using machine learning methods for clustering and classification of pure substances and gas mixtures and neural networks for the identification of gas mixture components. Using the experimental setup described, the experimentally obtained concentration limits are 80 ppb for acetone and 100–120 ppb for ethanol and methanol. The possibility of using the proposed methods for analyzing spectra of human exhaled air is shown, which is significant for biomedical applications.

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“…Simplified schematics of such experimental systems are presented in Figure 2b,c. Their experimental setup and operation are detailed in [47][48][49][50][51].…”

Section: Introductionmentioning

confidence: 99%

Advances in Mid-Infrared Spectroscopy-Based Sensing Techniques for Exhaled Breath Diagnostics

et al. 2020

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Human exhaled breath consists of more than 3000 volatile organic compounds, many of which are relevant biomarkers for various diseases. Although gas chromatography has been the gold standard for volatile organic compound (VOC) detection in exhaled breath, recent developments in mid-infrared (MIR) laser spectroscopy have led to the promise of compact point-of-care (POC) optical instruments enabling even single breath diagnostics. In this review, we discuss the evolution of MIR sensing technologies with a special focus on photoacoustic spectroscopy, and its application in exhaled breath biomarker detection. While mid-infrared point-of-care instrumentation promises high sensitivity and inherent molecular selectivity, the lack of standardization of the various techniques has to be overcome for translating these techniques into more widespread real-time clinical use.

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Sensitive acetone detection with a mid-IR interband cascade laser and wavelength modulation spectroscopy

Cited by 19 publications

References 37 publications

Structural stability and optical properties of 1D photonic crystals based on porous anodic alumina after annealing at different temperatures

Structural stability and optical properties of 1D photonic crystals based on porous anodic alumina after annealing at different temperatures

Numerical methods of spectral analysis of multicomponent gas mixtures and human exhaled breath

Advances in Mid-Infrared Spectroscopy-Based Sensing Techniques for Exhaled Breath Diagnostics

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