Modeling the UV-visible spectroscopic data of an aromatic hydrocarbon mixture to solve the problem of gas mixtures

Document Type : Research Paper


1 Department of Clinical laboratory science, University of Kerbala, Iraq

2 Department of Physics, College of Science, Mustansiriyah University, Baghdad, Iraq


The information data obtained from the spectra of the sensors were combined, which allowed us to build a matrix including thousands of spectrum-simulating gas mixtures, taking into account the presence of different components in several concentrations. Signal process technique and experimental design were utilized all the way for simulating spectral datasets. Particularly, the purpose of the simulation is for database creation for the evaluation of the final detection system for mixtures of gases (aromatic hydrocarbons). The dependable components of a fluorescent read platform are a light source for fluorescence excitation and for isolating the filtered fluorescent light from the excitement light and image detector. However, this technique has several limitations because of the need to utilize many chemo-sensor elements at the same time, which make titration complicated. This is needed to search for another way to overcome complications. In our study, certain filters were used to solve the problem of fluorescence spectroscopy.


[1] D.W. Ball, Field guide to spectroscopy, SPIE Publication, Bellingham, 2006.
[2] N. Brown and P. Bladon, Spectroscopy and structure of (1, 3-diketonato) boron difluorides and related compounds, J. Chem. Soc. A: Inorganic, Physical, Theor. (1969), 526–532.
[3] P. Cadusch, M. Hlaing, S. Wade, S. McArthur and P. Stoddart, Improved methods for fluorescence background subtraction from Raman spectra, J. Raman Spectroscopy 44 (2013), 1587–1595.
[4] T.T. Cai, D. Zhang and D. Ben-Amotz, Enhanced chemical classification of Raman images using multiresolution wavelet transformation, Appl. Spectroscopy 55 (2001), no. 9, 1124–1130.
[5] M.A. Choma, M.V. Sarunic, C. Yang and J.A. Izatt, Sensitivity advantage of swept source and Fourier domain optical coherence tomography, Optics Express 11 (2003), no. 18.
[6] J.D.A. Espinoza, V. Sazhnikov, S. Sabik, D. Ionov, E. Smits, S. Kalathimekkad, G. Van Steenberge, M. Alfimov, M. Po´sniak, E. Dobrzy´nska and M. Szewczy´nska, Flexible optical chemical sensor platform for BTX, Proc. Eng. 47 (2012), 607–610.
[7] C.V. Gazarov, V.E. Pozhar and V.N. Zhogun, Acousto-optical spectrometer for air pollution monitoring, CIS Selected Papers: Optic. Monitor. Envir. SPIE 2107 (1993), 143–146.
[8] R. Heinrich, A. Popescu, A. Hangauer, R. Strzoda and S. H¨ofling, High performance direct absorption spectroscopy of pure and binary mixture hydrocarbon gases in the 6–11 µm range, Appl. Phys. B 123 (2017), no. 223, 1–9.
[9] M. Jalali-Heravi and H. Parastar, Assessment of the co-elution problem in gas chromatography-mass spectrometry using non-linear optimization techniques, Chemom. Intell. Lab. Syst. 101 (2010), no. 1, 1–13.
[10] Y.M. Jung, Principal component analysis based two-dimensional correlation spectroscopy for noise filtering effect, Vibrat. Spectroscopy 36 (2004), no. 2, 267.
[11] R. Kengne-Momo, P. Daniel, F. Lagarde, Y. Jeyachandran, J. Pilard, M.J. Durand-Thouand, G. Thouand, Protein interactions investigated by the Raman spectroscopy for biosensor applications, Int. J. Spectroscopy 2012 (2012).
[12] A.-I.Z. Khalaf, M. Alboedam, H.J. Abidalhussein and A.-Z.S. Hassan, The role of blood proteins and nucleic acids in the detection of multiple Myeloma based on Raman spectroscopy, EurAsian J. BioSci. 14 (2020), no. 1, 1955–1963.
[13] A.-I.Z. Khalaf, M. Alboedam, H.J. Abidalhussein and A.-Z.S. Hassan, Detecting levels amino acids for proteins of dierent for patients with myeloma and comparing them using a portable Raman spectrometer, EurAsian J. BioSci. 14 (2020), no. 1, 2029–2036.
[14] J. Luo, K. Ying, P. He and J. Bai, Properties of Savitzky–Golay digital differentiators, Digital Signal Process. 15 (2005), no. 2, 122–136.
[15] V. Mazet, C. Carteret, D. Brie, J. Idier and B. Humbert, Background removal from spectra by designing and minimising a non-quadratic cost function, Chemom. Intel. Lab. Syst. 76 (2005), no. 2, 121–133.
[16] A. Mirzaei, J.H. Kim, H.W. Kim and S.S. Kim, Resistive-based gas sensors for detection of benzene, toluene and xylene (BTX) gases: a review, J. Mater. Chem. C 6 (2018), no. 16, 4342–4370.
[17] U. Platt, D. Perner and H.W. P¨atz, Simultaneous measurement of atmospheric CH2O, O3, and NO2 by differential optical absorption, J. Geophys. Res.: Oceans 84 (1979), no. C10, 6329–6335.
[18] V.I. Pustovoit and V.E. Pozhar, Long-path optical spectral AOTF-based gas analyzer, Instrument. Air Poll. Glob. Atmosph. Monitor. SPIE 4574 (2002), 174–178.
[19] M.A. Rahman, M.A. Rashid and M. Ahmad, Selecting the optimal conditions of Savitzky–Golay filter for fNIRS signal, Biocyb. Biomed. Eng. 39 (2019), no. 3, 624–637.
Volume 14, Issue 1
January 2023
Pages 2753-2758
  • Receive Date: 18 October 2022
  • Revise Date: 22 December 2022
  • Accept Date: 02 January 2023