Broadband-tunable external-cavity quantum cascade lasers for the spectroscopic detection of hazardous substances

Hugger, S.; Fuchs, F.; Jarvis, J.; Kinzer, M.; Yang, Quankui; Driad, R.; Aidam, R.; Wagner, J.

doi:10.1117/12.2008880

Cited by 17 publications

(10 citation statements)

References 16 publications

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“…In a search for alternatives, more efficient, rapid analysis techniques that can overcome this challenge, such as mid-infrared (MIR) laser spectroscopy using quantum cascade lasers (QCLs) have been found as a possible solution [26]. These devices are characterized by room-temperature operation, continuous-wave operation, high output power, high wall-plug efficiency [27], small footprints, long lifetimes, low energy consumption, and high long-term power stability [28]. Another characteristic of QCLs is the possibility of widely tuning their output frequencies [29].…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence Assisted Mid-Infrared Laser Spectroscopy In Situ Detection of Petroleum in Soils

et al. 2020

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A simple, remote-sensed method of detection of traces of petroleum in soil combining artificial intelligence (AI) with mid-infrared (MIR) laser spectroscopy is presented. A portable MIR quantum cascade laser (QCL) was used as an excitation source, making the technique amenable to field applications. The MIR spectral region is more informative and useful than the near IR region for the detection of pollutants in soil. Remote sensing, coupled with a support vector machine (SVM) algorithm, was used to accurately identify the presence/absence of traces of petroleum in soil mixtures. Chemometrics tools such as principal component analysis (PCA), partial least square-discriminant analysis (PLS-DA), and SVM demonstrated the effectiveness of rapidly differentiating between different soil types and detecting the presence of petroleum traces in different soil matrices such as sea sand, red soil, and brown soil. Comparisons between results of PLS-DA and SVM were based on sensitivity, selectivity, and areas under receiver-operator curves (ROC). An innovative statistical analysis method of calculating limits of detection (LOD) and limits of decision (LD) from fits of the probability of detection was developed. Results for QCL/PLS-DA models achieved LOD and LD of 0.2% and 0.01% for petroleum/soil, respectively. The superior performance of QCL/SVM models improved these values to 0.04% and 0.003%, respectively, providing better identification probability of soils contaminated with petroleum.

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Section: Introductionmentioning

confidence: 99%

Artificial Intelligence Assisted Mid-Infrared Laser Spectroscopy In Situ Detection of Petroleum in Soils

et al. 2020

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“…Methods for the in situ detection and identification of organic compounds on surfaces at trace‐level quantities are needed for rapid and effective applications in various areas, such as homeland security, environmental problems, and the development of methods for process analytical technology (PAT) in pharmaceutical industries . Cleaning validation procedures in pharmaceutical industries are a requirement of current good manufacturing practices (cGMPs) .…”

Section: Introductionmentioning

confidence: 99%

Quantum cascade laser back‐reflection spectroscopy at grazing‐angle incidence using the fast Fourier transform as a data preprocessing algorithm

Pacheco‐Londoño

Galán-Freyle

et al. 2019

Journal of Chemometrics

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A simple optical layout for a grazing-angle probe (GAP) mount for coupling to a midinfrared (MIR) quantum cascade laser (QCL) spectrometer is described.This assembly enables reflectance measurements at high incident angles. In the case of optically thin films and deposits on MIR reflective substrates, a double-pass effect occurs, which is accompanied by the absorption of deposited samples in a reflection-absorption infrared spectroscopy modality. The optical system allows MIR light to pass through the sample twice.Applications to cleaning validation and detection of traces of explosives using the QCL-GAP is reported. Principal component analysis and partial least squares multivariate chemometrics methods were employed to analyze MIR spectra to evaluate an analytical methodology for confirming the presence of residues of pharmaceutically active ingredients (irbesartan) and of traces of explosives (cyclotrimethylenetrinitramine [RDX]) that have been deposited on metallic substrates. The performance of spectral preprocessing via fast Fourier transform (FFT) analysis was evaluated for the ability to extract more powerful and accurate information from the obtained reflectance spectra.According to the figures of merit of this new technique, FFT with chemometric routines can obtain sensitivity and specificity values of 1.000. The limits of detection that were obtained for irbesartan and RDX were 26 and 8 ng/cm 2 , respectively. The experimental results demonstrate that the proposed system, when used together with proper chemometrics routines, constitutes a powerful tool for the development of methodologies that have lower detection limits for a range of applications that involve detecting traces of analytes that reside on substrates as contaminants. KEYWORDS fast Fourier transform (FFT), grazing angle MIR laser spectroscopy, irbesartan/RDX, partial least squares (PLS), principal component analysis (PCA)

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“…Chemical and explosive materials can be detected by a few methods, such as LIBS, Raman spectroscopy, photoacoustic spectroscopy, hyperspectral imaging, photo-thermal effect imaging [1][2][3][4][5][6][7][8][9][10][11][12][13], etc. LIBS is arguably one with simple configuration and short acquisition time [14][15][16][17][18][19][20][21][22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

Chemical and explosive detection with long-wave infrared laser induced breakdown spectroscopy

et al. 2016

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Conventional laser induced breakdown spectroscopy (LIBS) mostly uses silicon-based detectors and measures the atomic emission in the UV-Vis-NIR (UVN) region of the spectrum. It can be used to detect the elements in the sample under test, such as the presence of lead in the solder for electronics during RoHS compliance verification. This wavelength region, however, does not provide sufficient information on the bonding between the elements, because the molecular vibration modes emit at longer wavelength region. Measuring long-wave infrared spectrum (LWIR) in a LIBS setup can instead reveal molecular composition of the sample, which is the information sought in applications including chemical and explosive detection and identification. This paper will present the work and results from the collaboration of several institutions to develop the methods of LWIR LIBS for chemical/explosive/pharmaceutical material detection/identification, such as DMMP and RDX, as fast as using a single excitation laser pulse. In our latest LIBS setup, both UVN and LWIR spectra can be collected at the same time, allowing more accurate detection and identification of materials.

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Broadband-tunable external-cavity quantum cascade lasers for the spectroscopic detection of hazardous substances

Cited by 17 publications

References 16 publications

Artificial Intelligence Assisted Mid-Infrared Laser Spectroscopy In Situ Detection of Petroleum in Soils

Artificial Intelligence Assisted Mid-Infrared Laser Spectroscopy In Situ Detection of Petroleum in Soils

Quantum cascade laser back‐reflection spectroscopy at grazing‐angle incidence using the fast Fourier transform as a data preprocessing algorithm

Chemical and explosive detection with long-wave infrared laser induced breakdown spectroscopy

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