DEVELOPMENT OF METHODS FOR STUDYING SUBSTANCES ON SURFACES BY DIFFUSE REFLECTANCE SPECTROSCOPY AND INFRARED QUANTUM CASCADE LASERS
DMITRIY ANFIMOV1, IGOR FUFURIN1, PAVEL DEMKIN1 AND ANDREY MOROZOV1
1Department of physics, Bauman Moscow State Technical University, Russia
ABSTRACT
This paper presents the characteristics of a quantum cascade laser (QCL) prototype developed by the author's team in the range from 9.6 to 12.5 ^m, with a tuning step of 2 cm-1, a spectral line width of 2 cm-1, a maximum peak power of 199.8 mW and a maximum average power of 7.57 mW. The laser efficiency is 12.6 %. The prospects for using QCL in the field of identifying chemical substances in solid and liquid states on various substrates using diffuse reflectance infrared radiation are shown.
INTRODUCTION
At present, the task of studying various substances is extremely relevant and is being solved by many research teams, both in Russia [1, 2] and abroad [3]. One of the generally recognized optical methods is infrared spectroscopy. Infrared (IR) Fourier spectroscopy is used to study substances in the gaseous phase [4]. To study substances in solid and liquid phases, methods such as Raman spectroscopy [5] and diffuse light reflectance spectroscopy [6] are used, which is also actively used to study biological tissues and liquids. Diffuse reflectance spectroscopy requires broadband radiation sources, such as quantum cascade lasers, which are low-power and broadband radiation sources in a fairly wide IR range.
The studies [7-10] present the results of detection of small amounts of various chemical substances using a quantum cascade laser with an external resonator in the tuning range of 7.7-11.8 ^m. The laser beam moves along the plane, and using an IR camera with a spatial resolution of 70 ^m, a hypercube measuring 128 x 128 pixels and a depth of 130 signals at different wavelengths is recorded. A sample of 100 ^g of caffeine was detected at a distance of 5 m [7], 100 ^g of saccharin were detected at a distance of 25 m, and trace amounts of pentaerythritol tetranitrate at a distance of 0.1 m [10]. The detection limits [8] for pentaerythritol tetranitrate were 6 ng per pixel. The work [9] presents mathematical methods for modeling hypercubes that can be used to develop identification algorithms.
Diffuse reflectance spectroscopy is used to study biological tissues. It can help in developing noninvasive methods for analyzing cancer cells inside the human body [11, 12] and for studying skin lesions [13]. The author's team created an experimental setup based on the Block Engineering quantum cascade laser with a tuning range from 5.3 to 12.8 ^m. [14] The results of experiments on the identification of substances are presented and a mathematical apparatus is given, thanks to which it is possible to effectively carry out identification. [15]. The authors suggest expanding the arsenal of identification methods using machine and deep learning methods [16, 17, 18]. This is justified by the fact that depending on the angle of incidence of radiation, substrates and various external conditions, transmission spectra can differ from each other. Deep learning methods make it possible to take these differences into account without delving into the study of their nature.
Current paper presents a model of a quantum cascade laser with a tuning range from 9.6 to 12.5 ^m.[19] The characteristics of the developed laser and the prospects for its use in solving the problem of identifying solid and liquid substances on various substrates are presented.
RESULTS
Figure 1 shows a mockup of a quantum cascade laser. It consists of several main components: a quantum cascade laser chip (1); a thermoelectric controller for controlling the Peltier element, which maintains the laser temperature at a certain value (2); a diffraction grating (3); an inclined platform (4); a motor for rotating the diffraction grating (5); a voltage control board on the quantum cascade laser chip (6); aspherical lenses (7).
Figure 1: Mockup of a quantum cascade laser.
Figure 2 shows the spectrum of the average radiation power of a quantum cascade at a chip voltage of 14 volts and a chip temperature of 18 degrees Celsius.
Figure 2: Spectrum of the average radiation power of a quantum cascade laser model.
Figure 3 shows the pulse shape of the signal on the oscilloscope obtained using the cadmium-mercury-tellurium photodetector (PD) PVMI-4TE-10.6 (a) and the pulse shape at a certain wavelength obtained using the Thorlabs OSA207C spectrometer with a spectral resolution of 0.25 cm-1 (b).
(a)
(b)
Figure 3: The shape of the signal pulse on the PD (a) and on the spectrometer (b).
The above model of the quantum cascade laser can be used to identify substances on various substrates by diffusely reflected radiation.
The Block Engineering company (USA) [10] creates devices based on quantum cascade lasers, with the help of which it is possible to identify residual amounts of a substance on various surfaces. Figure 4 shows images obtained on an IR camera, capturing radiation diffuse reflected from a substance. Since the laser is capable of tuning to different wavelengths in the radiation range, the sum of the images allows you to build a hypercube. At the moment, a team of authors is working on creating an experimental setup for a laser hyperspectral spectrometer.
Figure 4: Concept of laser hyperspectral spectrometer for detection of trace chemicals. [10] CONCLUSIONS
This paper presents the results of developing a prototype of a quantum cascade laser in the tuning range from 9.6 to 12.5 ^m with a tuning step of 2 cm-1, a spectral line width of 2 cm-1, a maximum peak power of 199.8 mW and a maximum average power of 7.57 mW. The laser efficiency is 12.6 %. The laser can be used to identify trace amounts of solids and liquids on various surfaces using diffuse reflectance infrared radiation.
REFERENCES
[1] Vintaykin, I. B., Golyak, I. S., Korolev, P. A., Morozov, A. N., Tabalin, S. E. and Timashova, L. N., "Application of a Static IR Fourier Spectrometer for Recording Chemical Compounds in an Open Atmosphere," Russian Journal of Physical Chemistry B 15(3), 413-419 (2021).
[2] Maiorov, V. D., Voloshenko, G. I. and Kislina, I. S., "Composition and Structure of Complexes Formed in Aqueous Solutions of Trifluoroacetic Acid According to IR Spectroscopy Data," Russian journal of physical chemistry. B 12(2), 185-191 (2018).
[3] Yasuura, M. and Fujimaki, M., "Detection of Extremely Low Concentrations of Biological Substances Using Near-Field Illumination," Scientific Reports 6(1) (2016).
[4] Morozov A.N., Svetlichny S.I. Fundamentals of Fourier spectroradiometry. M.: Nauka, 2014. 2nd ed., revised. and additional
[5] Portnov, A., Rosenwaks, S. and Bar, I., "Detection of particles of explosives via backward coherent anti -Stokes Raman spectroscopy," Applied Physics Letters 93(4) (2008).
[6] Kelley, D. B., Goyal, A. K., Zhu, N., Wood, D. A., Myers, T. R., Kotidis, P., Murphy, C., Georgan, C., Raz, G., Maulini, R. and Müller, A., "High-speed mid-infrared hyperspectral imaging using quantum cascade lasers," SPIE Proceedings 10183, A. W. Fountain and J. A. Guicheteau, Eds., 1018304 (2017).
[7] Goyal, A. K., Kelley, D. B., Wood, D. A. and Petros Kotidis., "High-speed and large-area scanning of surfaces for trace chemicals using wavelength-tunable quantum cascade lasers," SPIE Proceedings 10629, 8-8 (2018).
[8] Wood, D. A., Kelley, D., Goyal, A. and Petros Kotidis., "Mid-infrared reflection signatures for trace chemicals on surfaces," SPIE Proceedings 10629 (2018).
[9] Myers, T., Wood, D., Goyal, A. K., Kelley, D., Kotidis, P., Raz, G., Murphy, C. and Georgan, C., "Mid -infrared hyperspectral simulator for laser-based detection of trace chemicals on surfaces," SPIE Proceedings 10198, M. Velez-Reyes and D. W. Messinger, Eds., 101980C (2017).
[10] Goyal, A. K., Wood, D., Lee, V., Rollag, J., Schwarz, P., Zhu, L. and Santora, G., "Laser -based long-wave-infrared hyperspectral imaging system for the standoff detection of trace surface chemicals," Optical Engineering 59(09), 1 (2020).
[11] Yeh, K. and Bhargava, R., "Discrete frequency infrared imaging using quantum cascade lasers for biological tissue analysis," Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE (2016).
[12] de, L., Torre Michelle Bydlon, Frederieke van Duijnhoven, Jeanne, M., Loo, C. E., Gonneke A. O. WinterWarnars, Sanders, J., Henricus J. C. M. Sterenborg, Benno and Theo J.M. Ruers., "Towards the use of diffuse reflectance spectroscopy for real-time in vivo detection of breast cancer during surgery," Journal of Translational Medicine 16(1) (2018).
[13] Marbach, R. and Heise, H. M., "Optical diffuse reflectance accessory for measurements of skin tissue by near-infrared spectroscopy," Applied Optics 34(4), 610 (1995).
[14] Fufurin, I. L., Tabalina, A. S., Morozov, A. N., Golyak, I. S., Svetlichnyi, S. I., Anfimov, D. R. and Kochikov, I. V., "Identification of substances from diffuse reflectance spectra of a broadband quantum cascade laser using Kramers-Kronig relations," Optical Engineering 59(06), 1-1 (2020).
[15] Anfimov, D. R., Golyak, I. S., Nebritova, O. A. and Fufurin, I. L., "Dispersion Analysis of Diffuse Scattering Spectra Obtained by a Quantum-Cascade Laser as a Means of Substance Identification," Russian Journal of Physical Chemistry B 16(5), 834-838 (2022).
[16] Igor Semenovich Golyak, Dmitriy Romanovich Anfimov, Pavel Pavlovich Demkin, Pavel Vyacheslavovich Berezhanskiy, Nebritova, O. A., Morozov, A. N. and Igor Leonidovich Fufurin., "A hybrid learning approach to better classify exhaled breath's infrared spectra: A noninvasive optical diagnosis for socially significant diseases," Journal of Biophotonics (2024).
[17] Igor Fufurin, Pavel Berezhanskiy, Igor Golyak, Dmitriy Anfimov, Elizaveta Kareva, Anastasiya Scherbakova, Pavel Demkin, Nebritova, O. and Morozov, A., "Deep Learning for Type 1 Diabetes Mellitus Diagnosis Using Infrared Quantum Cascade Laser Spectroscopy," Materials 15(9), 2984-2984 (2022).
[18] Fufurin, I. L., Anfimov, D. R., Kareva, E. R., Scherbakova, A. V., Demkin, P. P., Morozov, A. N. and Golyak, I. S., "Numerical techniques for infrared spectra analysis of organic and inorganic volatile compounds for biomedical applications," Optical Engineering 60(08) (2021).
[19] Anfimov, D. R., Golyak, Ig. S., Demkin, P. P., Zadorozhny, E. N., Vintaykin, I. B., Morozov, A. N. and Fufurin, I. L., "Pulsed tunable quantum cascade laser in the spectral range of 9.6-12.5 ^m," Technical Physics 69(3) (2024).