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Lazic V, Andreoli F, Almaviva S, Pistilli M, Menicucci I, Ulrich C, Schnürer F, Chirico R. A Novel LIBS Sensor for Sample Examinations on a Crime Scene. SENSORS (BASEL, SWITZERLAND) 2024; 24:1469. [PMID: 38475005 DOI: 10.3390/s24051469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2023] [Revised: 02/20/2024] [Accepted: 02/22/2024] [Indexed: 03/14/2024]
Abstract
In this work, we present a compact LIBS sensor developed for characterization of samples on a crime scene following requirements of law enforcement agencies involved in the project. The sensor operates both in a tabletop mode, for aside measurements of swabbed materials or taken fragments, and in handheld mode where the sensor head is pointed directly on targets at the scene. The sensor head is connected via an umbilical to an instrument box that could be battery-powered and contains also a color camera for sample visualization, illumination LEDs, and pointing system for placing the target in focus. Here we describe the sensor's architecture and functionalities, the optimization of the acquisition parameters, and the results of some LIBS measurements. On nano-plotted traces at silica wafer and in optimized conditions, for most of the elements the detection limits, in term of the absolute element masses, were found to be below 10 picograms. We also show results obtained on some representative materials, like fingerprints, swabbed soil and gunshot residue, varnishes on metal, and coated plastics. The last, solid samples were used to evaluate the depth profiling capabilities of the instrument, where the recognition of all four car paint layers was achieved.
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Affiliation(s)
- Violeta Lazic
- Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Laboratory FSN-TECFIS-DIM, Via Enrico Fermi 45, 00044 Frascati, Italy
| | - Fabrizio Andreoli
- Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Laboratory FSN-FUSEN-TEN, Via Enrico Fermi 45, 00044 Frascati, Italy
| | - Salvatore Almaviva
- Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Laboratory FSN-TECFIS-DIM, Via Enrico Fermi 45, 00044 Frascati, Italy
| | - Marco Pistilli
- Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Laboratory FSN-TECFIS-DIM, Via Enrico Fermi 45, 00044 Frascati, Italy
| | - Ivano Menicucci
- Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Laboratory FSN-TECFIS-DIM, Via Enrico Fermi 45, 00044 Frascati, Italy
| | - Christian Ulrich
- Fraunhofer Institute for Chemical Technology ICT, Energetic Materials Department, Joseph-von-Fraunhofer-Str. 7, 76327 Pfinztal, Germany
| | - Frank Schnürer
- Fraunhofer Institute for Chemical Technology ICT, Energetic Materials Department, Joseph-von-Fraunhofer-Str. 7, 76327 Pfinztal, Germany
| | - Roberto Chirico
- Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Laboratory FSN-TECFIS-DIM, Via Enrico Fermi 45, 00044 Frascati, Italy
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Janovszky P, Kéri A, Palásti DJ, Brunnbauer L, Domoki F, Limbeck A, Galbács G. Quantitative elemental mapping of biological tissues by laser-induced breakdown spectroscopy using matrix recognition. Sci Rep 2023; 13:10089. [PMID: 37344545 DOI: 10.1038/s41598-023-37258-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 06/19/2023] [Indexed: 06/23/2023] Open
Abstract
The present study demonstrates the importance of converting signal intensity maps of organic tissues collected by laser-induced breakdown spectroscopy (LIBS) to elemental concentration maps and also proposes a methodology based on machine learning for its execution. The proposed methodology employs matrix-matched external calibration supported by a pixel-by-pixel automatic matrix (tissue type) recognition performed by linear discriminant analysis of the spatially resolved LIBS hyperspectral data set. On a swine (porcine) brain sample, we successfully performed this matrix recognition with an accuracy of 98% for the grey and white matter and we converted a LIBS intensity map of a tissue sample to a correct concentration map for the elements Na, K and Mg. Found concentrations in the grey and white matter agreed the element concentrations published in the literature and our reference measurements. Our results revealed that the actual concentration distribution in tissues can be quite different from what is suggested by the LIBS signal intensity map, therefore this conversion is always suggested to be performed if an accurate concentration distribution is to be assessed.
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Affiliation(s)
- Patrick Janovszky
- Department of Inorganic and Analytical Chemistry, University of Szeged, Dóm square 7, Szeged, 6720, Hungary
| | - Albert Kéri
- Department of Inorganic and Analytical Chemistry, University of Szeged, Dóm square 7, Szeged, 6720, Hungary
| | - Dávid J Palásti
- Department of Inorganic and Analytical Chemistry, University of Szeged, Dóm square 7, Szeged, 6720, Hungary
| | - Lukas Brunnbauer
- Institute of Chemical Technologies and Analytics, TU Wien, Getreidemarkt 9/164, 1060, Vienna, Austria
| | - Ferenc Domoki
- Department of Physiology, University of Szeged, Dóm square 10, Szeged, 6720, Hungary
| | - Andreas Limbeck
- Institute of Chemical Technologies and Analytics, TU Wien, Getreidemarkt 9/164, 1060, Vienna, Austria
| | - Gábor Galbács
- Department of Inorganic and Analytical Chemistry, University of Szeged, Dóm square 7, Szeged, 6720, Hungary.
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