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Quantitative Line Assignment in Optical Emission Spectroscopy

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Date Issued:
2018
Abstract/Description:
Quantitative elemental analysis using Optical Emission Spectroscopy (OES) starts with a high level of confidence in spectral line assignment from reference databases. Spectral interferences caused by instrumental and line broadening decrease the resolution of OES spectra creating uncertainty in the elemental profile of a sample for the first time. An approach has been developed to quantify spectral interferences for individual line assignment in OES. The algorithm calculates a statistical interference factor (SIF) that combines a physical understanding of plasma emission with a Bayesian analysis of the OES spectrum. It can be used on a single optical spectrum and still address individual lines. Contrary to current methods, quantification of the uncertainty in elemental profiles of OES, leads to more accurate results, higher reliability and validation of the method. The SIF algorithm was evaluated for Laser-Induced Breakdown Spectroscopy (LIBS) on samples with increasing complexity: from silicon to nickel spiked alumina to NIST standards (600 glass series and nickel-chromium alloy). The influence of the user's knowledge of the sample composition was studied and showed that for the majority of spectral lines this information is not changing the line assignment for simple compositions. Nonetheless, the amount of interference could change with this information, as expected. Variance of the SIF results for NIST glass standard was evaluated by the chi-square hypothesis test of variance showing that the results of the SIF algorithm are very reproducible.
Title: Quantitative Line Assignment in Optical Emission Spectroscopy.
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Name(s): Chappell, Jessica, Author
Baudelet, Matthieu, Committee Chair
Hernandez, Florencio, Committee Member
Campiglia, Andres, Committee Member
Ni, Liqiang, Committee Member
Sigman, Michael, Committee Member
University of Central Florida, Degree Grantor
Type of Resource: text
Date Issued: 2018
Publisher: University of Central Florida
Language(s): English
Abstract/Description: Quantitative elemental analysis using Optical Emission Spectroscopy (OES) starts with a high level of confidence in spectral line assignment from reference databases. Spectral interferences caused by instrumental and line broadening decrease the resolution of OES spectra creating uncertainty in the elemental profile of a sample for the first time. An approach has been developed to quantify spectral interferences for individual line assignment in OES. The algorithm calculates a statistical interference factor (SIF) that combines a physical understanding of plasma emission with a Bayesian analysis of the OES spectrum. It can be used on a single optical spectrum and still address individual lines. Contrary to current methods, quantification of the uncertainty in elemental profiles of OES, leads to more accurate results, higher reliability and validation of the method. The SIF algorithm was evaluated for Laser-Induced Breakdown Spectroscopy (LIBS) on samples with increasing complexity: from silicon to nickel spiked alumina to NIST standards (600 glass series and nickel-chromium alloy). The influence of the user's knowledge of the sample composition was studied and showed that for the majority of spectral lines this information is not changing the line assignment for simple compositions. Nonetheless, the amount of interference could change with this information, as expected. Variance of the SIF results for NIST glass standard was evaluated by the chi-square hypothesis test of variance showing that the results of the SIF algorithm are very reproducible.
Identifier: CFE0007564 (IID), ucf:52575 (fedora)
Note(s): 2018-08-01
Ph.D.
Sciences, Chemistry
Doctoral
This record was generated from author submitted information.
Subject(s): optical emission spectroscopy -- elemental analysis -- spectral line assignment -- spectral interferences -- laser-induced breakdown spectroscopy
Persistent Link to This Record: http://purl.flvc.org/ucf/fd/CFE0007564
Restrictions on Access: campus 2020-02-15
Host Institution: UCF

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