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Mid-Infrared Laser Spectroscopy Detection and Quantification of Explosives in Soils Using Multivariate Analysis and Artificial Intelligence

dc.contributor.authorPacheco-Londoño, Leonardo C.
dc.contributor.otherWarren, Eric
dc.contributor.otherGalán-Freyle, Nataly J.
dc.contributor.otherVillarreal-González, Reynaldo
dc.contributor.otherAparicio-Bolaño, Joaquín A.
dc.contributor.otherOspina-Castro, María L.
dc.contributor.otherShih, Wei-Chuan
dc.contributor.otherHernández-Rivera, Samuel P.
dc.date.accessioned2022-11-15T21:27:05Z
dc.date.available2022-11-15T21:27:05Z
dc.date.issued2020-06-20
dc.date.submitted2020-04-02
dc.identifier.urihttps://hdl.handle.net/20.500.12834/1002
dc.description.abstractA tunable quantum cascade laser (QCL) spectrometer was used to develop methods for detecting and quantifying high explosives (HE) in soil based on multivariate analysis (MVA) and artificial intelligence (AI). For quantification, mixes of 2,4-dinitrotoluene (DNT) of concentrations from 0% to 20% w/w with soil samples were investigated. Three types of soils, bentonite, synthetic soil, and natural soil, were used. A partial least squares (PLS) regression model was generated for predicting DNT concentrations. To increase the selectivity, the model was trained and evaluated using additional analytes as interferences, including other HEs such as pentaerythritol tetranitrate (PETN), trinitrotoluene (TNT), cyclotrimethylenetrinitramine (RDX), and non-explosives such as benzoic acid and ibuprofen. For the detection experiments, mixes of di erent explosives with soils were used to implement two AI strategies. In the first strategy, the spectra of the samples were compared with spectra of soils stored in a database to identify the most similar soils based on QCL spectroscopy. Next, a preprocessing based on classical least squares (Pre-CLS) was applied to the spectra of soils selected from the database. The parameter obtained based on the sum of the weights of Pre-CLS was used to generate a simple binary discrimination model for distinguishing between contaminated and uncontaminated soils, achieving an accuracy of 0.877. In the second AI strategy, the same parameter was added to a principal component matrix obtained from spectral data of samples and used to generate multi-classification models based on di erent machine learning algorithms. A random forest model worked best with 0.996 accuracy and allowing to distinguish between soils contaminated with DNT, TNT, or RDX and uncontaminated soils.spa
dc.format.mimetypeapplication/pdfspa
dc.language.isoengspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.sourceMDPI AGspa
dc.titleMid-Infrared Laser Spectroscopy Detection and Quantification of Explosives in Soils Using Multivariate Analysis and Artificial Intelligencespa
dcterms.bibliographicCitation1. Frische, T.; Höper, H. Soil microbial parameters and luminescent bacteria assays as indicators for in situ bioremediation of TNT-contaminated soils. Chemosphere 2003, 50, 415–427spa
dcterms.bibliographicCitation2. Correa-Torres, S.N.; Pacheco-Londono, L.C.; Espinosa-Fuentes, E.A.; Rodriguez, L.; Souto-Bachiller, F.A.; Hernandez-Rivera, S.P. TNT removal from culture media by three commonly available wild plants growing in the Caribbean. J. Environ. Monit. 2012, 14, 30–33.spa
dcterms.bibliographicCitation3. Hildenbrand, J.; Herbst, J.; Wöllenstein, J.; Lambrecht, A. Explosive detection using infrared laser spectroscopy. Proc. SPIE 2009, 7222, 72220B.spa
dcterms.bibliographicCitation4. Narang, U.; Gauger, P.R.; Ligler, F.S. A Displacement Flow Immunosensor for Explosive Detection Using Microcapillaries. Anal. Chem. 1997, 69, 2779–2785.spa
dcterms.bibliographicCitation5. Hilmi, A.; Luong, J.H.T. Micromachined Electrophoresis Chips with Electrochemical Detectors for Analysis of Explosive Compounds in Soil and Groundwater. Environ. Sci. Technol. 2000, 34, 3046–3050.spa
dcterms.bibliographicCitation6. Kumar, S.; Venkatramaiah, N.; Patil, S. Fluoranthene Based Derivatives for Detection of Trace Explosive Nitroaromatics. J. Phys. Chem. C 2013, 117, 7236–7245.spa
dcterms.bibliographicCitation7. Sheremata, T.W.; Halasz, A.; Paquet, L.; Thiboutot, S.; Ampleman, G.; Hawari, J. The Fate of the Cyclic Nitramine Explosive RDX in Natural Soil. Environ. Sci. Technol. 2001, 35, 1037–1040.spa
dcterms.bibliographicCitation8. Larson, S.L.; Martin, W.A.; Escalon, B.L.; Thompson, M. Dissolution, Sorption, and Kinetics Involved in Systems Containing Explosives, Water, and Soil. Environ. Sci. Technol. 2008, 42, 786–792.spa
dcterms.bibliographicCitation9. Marple, R.L.; LaCourse,W.R. Application of Photoassisted Electrochemical Detection to Explosive-Containing Environmental Samples. Anal. Chem. 2005, 77, 6709–6714.spa
dcterms.bibliographicCitation10. Gallagher, N.B.; Blake, T.A.; Gassman, P.L. Application of extended inverse scatter correction to mid-infrared reflectance spectra of soil. J. Chemom. 2005, 19, 271–281.spa
dcterms.bibliographicCitation11. Forouzangohar, M.; Kookana, R.S.; Forrester, S.T.; Smernik, R.J.; Chittleborough, D.J. Mid-infrared Spectroscopy and Chemometrics to Predict Diuron Sorption Coe cients in Soils. Environ. Sci. Technol. 2008, 42, 3283–3288.spa
dcterms.bibliographicCitation12. Gallagher, N.B.; Gassman, P.L.; Blake, T.A. Strategies for Detecting Organic Liquids on Soils Using Mid-Infrared Reflection Spectroscopy. Environ. Sci. Technol. 2008, 42, 5700–5705.spa
dcterms.bibliographicCitation13. Mukherjee, A.; Von der Porten, S.; Patel, C.K.N. Stando detection of explosive substances at distances of up to 150 m. Appl. Opt. 2010, 49, 2072–2078.spa
dcterms.bibliographicCitation14. Hernández, M.D.; Santiago, I.; Padilla, I.Y. Macro-sorption of 2,4-dinitrotoluene onto sandy and clay soils. Proc. SPIE 2006, 6217, 621736.spa
dcterms.bibliographicCitation15. Baez, B.; Correa, S.N.; Hernandez-Rivera, S.P.; de Jesus, M.; Castro, M.E.; Mina, N.; Briano, J.G. Transport of explosives I: TNT in soil and its equilibrium vapor. Proc. SPIE 2004, 5415, 1389–1399.spa
dcterms.bibliographicCitation16. Torres, A.; Padilla, I.; Hwang, S. Physical modeling of 2,4-DNT gaseous di usion through unsaturated soil. Proc. SPIE 2007, 6553, 65531Q.spa
dcterms.bibliographicCitation17. Herrera-Sandoval, G.M.; Ballesteros, L.M.; Mina, N.; Briano, J.; Castro, M.E.; Hernandez-Rivera, S.P. Raman signatures of TNT in contact with sand particles. Proc. SPIE 2005, 5794, 1245–1253.spa
dcterms.bibliographicCitation18. Blanco, A.; Mina, N.; Castro, M.E.; Castillo-Chara, J.; Hernandez-Rivera, S.P. E ect of environmental conditions on the spectroscopic signature of DNT in sand. Proc. SPIE 2005, 5794, 1281–1289.spa
dcterms.bibliographicCitation19. Ballesteros, L.M.; Herrera, G.M.; Castro, M.E.; Briano, J.; Mina, N.; Hernandez-Rivera, S.P. Spectroscopic signatures of PETN in contact with sand particles. Proc. SPIE 2005, 5794, 1254–1262.spa
dcterms.bibliographicCitation20. Hernandez-Rivera, S.P.; Manrique-Bastidas, C.A.; Blanco, A.; Primera, O.M.; Pacheco, L.C.; Castillo-Chara, J.; Castro, M.E.; Mina, N. Spectroscopic characterization of nitroaromatic landmine signature explosives. Proc. SPIE 2004, 5415, 474–485.spa
dcterms.bibliographicCitation21. Osorio, C.; Gomez, L.M.; Hernandez, S.P.; Castro, M.E. Time-of-flight mass spectroscopy measurements of TNT and RDX on soil surfaces. Proc. SPIE 2005, 5794, 803–811.spa
dcterms.bibliographicCitation22. Manrique-Bastidas, C.A.; Mina, N.; Castro, M.E.; Hernandez-Rivera, S.P. Raman microspectroscopy and FTIR crystallization studies of 2,4,6-TNT in soil. Proc. SPIE 2005, 5794, 1358–1365.spa
dcterms.bibliographicCitation23. Blanco, A.; Pacheco-Londoño, L.C.; Peña-Quevedo, A.J.; Hernández-Rivera, S.P. UV Raman detection of 2,4-DNT in contact with sand particles. Proc. SPIE 2006, 6217, 621737.spa
dcterms.bibliographicCitation24. Galán-Freyle, N.J.; Pacheco-Londoño, L.C.; Figueroa-Navedo, A.M.; Hernandez-Rivera, S.P. Stando Detection of Highly Energetic Materials Using Laser-Induced Thermal Excitation of Infrared Emission. Appl. Spectrosc. 2015, 69, 535–544.spa
dcterms.bibliographicCitation25. Galán-Freyle, N.J.; Ospina-Castro,M.L.;Medina-González, A.R.; Villarreal-González, R.; Hernández-Rivera, S.P.; Pacheco-Londoño, L.C. Artificial Intelligence AssistedMid-Infrared Laser Spectroscopy In Situ Detection of Petroleum in Soils. Appl. Sci. 2020, 10, 1319.spa
dcterms.bibliographicCitation26. Rüther, A.; Pfeifer, M.; Lórenz-Fonfría, V.A.; Lüdeke, S. pH Titration Monitored by Quantum Cascade Laser-Based Vibrational Circular Dichroism. J. Phys. Chem. B 2014, 118, 3941–3949.spa
dcterms.bibliographicCitation27. Lüdeke, S.; Pfeifer, M.; Fischer, P. Quantum-Cascade Laser-Based Vibrational Circular Dichroism. J. Am. Chem. Soc. 2011, 133, 5704–5707.spa
dcterms.bibliographicCitation28. Shi, Q.; Nelson, D.D.; McManus, J.B.; Zahniser, M.S.; Parrish, M.E.; Baren, R.E.; Shafer, K.H.; Harward, C.N. Quantum Cascade Infrared Laser Spectroscopy for Real-Time Cigarette Smoke Analysis. Anal. Chem. 2003, 75, 5180–5190.spa
dcterms.bibliographicCitation29. Wörle, K.; Seichter, F.; Wilk, A.; Armacost, C.; Day, T.; Godejohann, M.; Wachter, U.; Vogt, J.; Radermacher, P.; Mizaiko , B. Breath Analysis with Broadly Tunable Quantum Cascade Lasers. Anal. Chem. 2013, 85, 2697–2702.spa
dcterms.bibliographicCitation30. Galán-Freyle, N.J.; Pacheco-Londoño, L.C.; Román-Ospino, A.D.; Hernandez-Rivera, S.P. Applications of Quantum Cascade Laser Spectroscopy in the Analysis of Pharmaceutical Formulations. Appl. Spectrosc. 2016, 70, 1511–1519.spa
dcterms.bibliographicCitation31. Padilla-Jiménez, A.C.; Ortiz-Rivera, W.; Rios-Velazquez, C.; Vazquez-Ayala, I.; Hernández-Rivera, S.P. Detection and discrimination of microorganisms on various substrates with quantum cascade laser spectroscopy. OPTICE 2014, 53, 061611.spa
dcterms.bibliographicCitation32. Faist, J.; Capasso, F.; Sivco, D.L.; Sirtori, C.; Hutchinson, A.L.; Cho, A.Y. Quantum Cascade Laser. Science 1994, 264, 553–556.spa
dcterms.bibliographicCitation33. Hvozdara, L.; Pennington, N.; Kraft, M.; Karlowatz, M.; Mizaiko , B. Quantum cascade lasers for mid-infrared spectroscopy. Vib. Spectrosc. 2002, 30, 53–58.spa
dcterms.bibliographicCitation34. Ruiz-Caballero, J.L.; Blanco-Riveiro, L.A.; Ramirez-Marrero, I.A.; Perez-Almodovar, L.A.; Colon-Mercado, A.M.; Castro-Suarez, J.R.; Pacheco-Londoño, L.C.; Hernandez-Rivera, S.P. Enhanced RDX Detection Studies on Various Types of Substrates via Tunable Quantum Cascade Laser Spectrometer Coupled with Grazing Angle Probe. IOP Conf. Ser. Mater. Sci. Eng. 2019, 519, 012007.spa
dcterms.bibliographicCitation35. Pacheco-Londoño, L.C.; Galán-Freyle, N.J.; Figueroa-Navedo, A.M.; Infante-Castillo, R.; Ruiz-Caballero, J.L.; Hernández-Rivera, S.P. Quantum cascade laser back-reflection spectroscopy at grazing-angle incidence using the fast Fourier transform as a data preprocessing algorithm. J. Chemom. 2019, 33, e3167.spa
dcterms.bibliographicCitation36. Pacheco-Londoño, L.C.; Aparicio-Bolaño, J.A.; Galán-Freyle, N.J.; Román-Ospino, A.D.; Ruiz-Caballero, J.L.; Hernández-Rivera, S.P. Classical Least Squares-Assisted Mid-Infrared (MIR) Laser Spectroscopy Detection of High Explosives on Fabrics. Appl. Spectrosc. 2019, 73, 17–29.spa
dcterms.bibliographicCitation37. Pacheco-Londoño, L.C.; Ruiz-Caballero, J.L.; Ramírez-Cedeño, M.L.; Infante-Castillo, R.; Gálan-Freyle, N.J.; Hernández-Rivera, S.P. Surface Persistence of Trace Level Deposits of Highly Energetic Materials. Molecules 2019, 24, 3494.spa
dcterms.bibliographicCitation38. Pacheco-Londoño, L.C.; Castro-Suarez, J.R.; Galán-Freyle, N.J.; Figueroa-Navedo, A.M.; Ruiz-Caballero, J.L.; Infante-Castillo, R.; Hernández-Rivera, S.P. Mid-Infrared Laser Spectroscopy Applications I: Detection of Traces of High Explosives on Reflective and Matte Substrates. In Infrared Spectroscopy—Principles, Advances, and Applications; IntechOpen: London, UK, 2019.spa
dcterms.bibliographicCitation39. Phillips, M.C.; Bernacki, B.E. Hyperspectral microscopy of explosives particles using an external cavity quantum cascade laser. OPTICE 2012, 52, 061302.spa
dcterms.bibliographicCitation40. Pacheco-Londoño, L.C.; Castro-Suarez, J.R.; Hernández-Rivera, S.P. Detection of Nitroaromatic and Peroxide Explosives in Air Using Infrared Spectroscopy: QCL and FTIR. Adv. Opt. Technol. 2013, 2013, 532670.spa
dcterms.bibliographicCitation41. Sirkeli, V.P.; Yilmazoglu, O.; Preu, S.; Küppers, F.; Hartnagel, H.L. Proposal for a Monolithic Broadband Terahertz Quantum Cascade Laser Array Tailored to Detection of Explosive Materials. Sens. Lett. 2018, 16, 1–7.spa
dcterms.bibliographicCitation42. Pettersson, A.; Wallin, S.; Östmark, H.; Ehlerding, A.; Johansson, I.; Nordberg, M.; Ellis, H.; Al-Khalili, A. Explosives stando detection using Raman spectroscopy: From bulk towards trace detection. Proc. SPIE 2010, 7664, 76641K.spa
dcterms.bibliographicCitation43. Yang, C.S.C.; Brown, E.E.; Hommerich, U.; Jin, F.; Trivedi, S.B.; Samuels, A.C.; Snyder, A.P. Long-Wave, Infrared Laser-Induced Breakdown (LIBS) Spectroscopy Emissions from Energetic Materials. Appl. Spectrosc. 2012, 66, 1397–1402.spa
dcterms.bibliographicCitation44. Misra, A.K.; Sharma, S.K.; Acosta, T.E.; Porter, J.N.; Bates, D.E. Single-Pulse Stando Raman Detection of Chemicals from 120 m Distance During Daytime. Appl. Spectrosc. 2012, 66, 1279–1285.spa
dcterms.bibliographicCitation45. Gottfried, J.L.; De Lucia, F.C.;Munson, C.A.;Miziolek, A.W. Standoff Detection of Chemical and Biological Threats Using Laser-Induced Breakdown Spectroscopy. Appl. Spectrosc. 2008, 62, 353–363.spa
dcterms.bibliographicCitation46. Castro-Suarez, J.R.; Pacheco-Londoño, L.C.; Vélez-Reyes, M.; Diem, M.; Tague, T.J.; Hernandez-Rivera, S.P. FT-IR Stando Detection of Thermally Excited Emissions of Trinitrotoluene (TNT) Deposited on Aluminum Substrates. Appl. Spectrosc. 2013, 67, 181–186.spa
dcterms.bibliographicCitation47. Carter, J.C.; Angel, S.M.; Lawrence-Snyder, M.; Sca di, J.; Whipple, R.E.; Reynolds, J.G. Stando Detection of High Explosive Materials at 50 Meters in Ambient Light Conditions Using a Small Raman Instrument. Appl. Spectrosc. 2005, 59, 769–775.spa
dcterms.bibliographicCitation48. Averett, L.A.; Gri ths, P.R. Mid-Infrared Di use Reflection of a Strongly Absorbing Analyte on Non-Absorbing and Absorbing Matrices. Part II: Thin Liquid Layers on Powdered Substrates. Appl. Spectrosc. 2008, 62, 383–388.spa
dcterms.bibliographicCitation49. Pacheco-Londoño, L.; Ortiz-Rivera, W.; Primera-Pedrozo, O.; Hernández-Rivera, S. Vibrational spectroscopy stando detection of explosives. Anal. Bioanal. Chem. 2009, 395, 323–335.spa
dcterms.bibliographicCitation50. Van Neste, C.W.; Senesac, L.R.; Thundat, T. Stando Spectroscopy of Surface Adsorbed Chemicals. Anal. Chem. 2009, 81, 1952–1956.spa
dcterms.bibliographicCitation51. Moros, J.; Lorenzo, J.A.; Lucena, P.; Miguel Tobaria, L.; Laserna, J.J. Simultaneous Raman Spectroscopy– Laser-Induced Breakdown Spectroscopy for Instant Stando Analysis of Explosives Using a Mobile Integrated Sensor Platform. Anal. Chem. 2010, 82, 1389–1400.spa
dcterms.bibliographicCitation52. Moros, J.; Laserna, J.J. New Raman–Laser-Induced Breakdown Spectroscopy Identity of Explosives Using Parametric Data Fusion on an Integrated Sensing Platform. Anal. Chem. 2011, 83, 6275–6285.spa
dcterms.bibliographicCitation53. Ortiz-Rivera, W.; Pacheco-Londoño, L.; Castro-Suarez, J.; Felix-Rivera, H.; Hernandez-Rivera, S. Vibrational Spectroscopy Stando Detection of Threat Chemicals; SPIE: Bellingham, WA, USA, 2011; Volume 8031.spa
dcterms.bibliographicCitation54. Miyazawa, M.; Pavan, M.A.; de Oliveira, E.L.; Ionashiro, M.; Silva, A.K. Gravimetric determination of soil organic matter. Braz. Arch. Biol. Technol. 2000, 43, 475–478.spa
dcterms.bibliographicCitation55. Weiner, E.R. Applications of Environmental Chemistry: A Practical Guide for Environmental Professionals; Lewis Pub.: Boca Raton, FL, USA, 2000.spa
dcterms.bibliographicCitation56. Yanjun, C.; Achari, G.; Langford, C.H. Protocols for the analysis of transformer oil and its degradation in soil by hydrogen peroxide. Can. J. Civ. Eng. 2009, 36, 1547–1557.spa
dcterms.bibliographicCitation57. Lorber, A. Error propagation and figures of merit for quantification by solving matrix equations. Anal. Chem. 1986, 58, 1167–1172.spa
dcterms.bibliographicCitation58. Ferreira, M.H.; Braga, J.W.B.; Sena, M.M. Development and validation of a chemometric method for direct determination of hydrochlorothiazide in pharmaceutical samples by di use reflectance near-infrared spectroscopy. Microelectron. J. 2013, 109, 158–164.spa
dcterms.bibliographicCitation59. Olivieri, A.C.; Faber, N.M.; Ferré, J.; Boqué, R.; Kalivas, J.H.; Mark, H. Uncertainty estimation and figures of merit for multivariate calibration (IUPAC Technical Report). Pure Appl. Chem. 2006, 78, 633.spa
dcterms.bibliographicCitation60. Felipe-Sotelo, M.; Cal-Prieto, M.J.; Ferre, J.; Boque, R.; Andrade, J.M.; Carlosena, A. Linear PLS regression to cope with interferences of major concomitants in the determination of antimony by ETAAS. J. Anal. Spectrom. 2006, 21, 61–68.spa
dcterms.bibliographicCitation61. Galan-Freyle, N.J.; Figueroa-Navedo, A.M.; Pacheco-Londoño, Y.C.; Ortiz-Rivera,W.; Pacheco-Londoño, L.C.; Hernández-Rivera, S.P. Chemometrics-enhanced fiber-optic Raman detection, discrimination and quantification of chemical agents simulants concealed in commercial bottles. Anal. Chem. Res. 2014, 2, 15–22.spa
dcterms.bibliographicCitation62. Buitinck, L.; Louppe, G.; Blondel, M.; Pedregosa, F.; Mueller, A.; Grisel, O.; Niculae, V.; Prettenhofer, P.; Gramfort, A.; Grobler, J.; et al. API design for machine learning software: Experiences from the scikit-learn project. In Proceedings of the European Conference on Machine Learning and Principles and Practices of Knowledge Discovery in Databases, Prague, Czech Republic, 23 September 2013.spa
dcterms.bibliographicCitation63. Kubelka, P. New Contributions to the Optics of Intensely Light-Scattering Materials. Part I. J. Opt. Soc. Am 1948, 38, 448.spa
dcterms.bibliographicCitation64. Bull, C.R. Compensation for particle size e ects in near-infrared reflectance. Analyst 1991, 116, 781–786.spa
dcterms.bibliographicCitation65. Sirita, J.; Phanichphant, S.; Meunier, F.C. Quantitative Analysis of Adsorbate Concentrations by Di use Reflectance FT-IR. Anal. Chem. 2007, 79, 3912–3918.spa
dcterms.bibliographicCitation66. Igne, B.; Hurburgh, C.R. Local chemometrics for samples and variables: Optimizing calibration and standardization processes. J. Chemom. 2010, 24, 75–86.spa
datacite.rightshttp://purl.org/coar/access_right/c_abf2spa
oaire.resourcetypehttp://purl.org/coar/resource_type/c_6501spa
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85spa
dc.audiencePúblico generalspa
dc.identifier.doi10.3390/app10124178
dc.identifier.instnameUniversidad del Atlánticospa
dc.identifier.reponameRepositorio Universidad del Atlánticospa
dc.rights.ccAttribution-NonCommercial 4.0 International*
dc.subject.keywordsquantum cascade laser; remote detection; partial least squares; high explosives; artificial intelligence; machine learningspa
dc.type.driverinfo:eu-repo/semantics/articlespa
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersionspa
dc.type.spaArtículospa
dc.publisher.placeBarranquillaspa
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessspa
dc.publisher.disciplineQuímicaspa
dc.publisher.sedeSede Nortespa


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