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Comparison of handheld and echelle spectrometer to assess copper in ores by means of laser-induced breakdown spectroscopy (LIBS)
- Its properties make copper one of the world’s most important functional metals. Numerous megatrends are increasing the demand for copper. This requires the prospection and exploration of new deposits, as well as the monitoring of copper quality in the various production steps. A promising technique to perform these tasks is Laser Induced Breakdown Spectroscopy (LIBS). Its unique feature, among others, is the ability to measure on site without sample collection and preparation. In this work, copper-bearing minerals from two different deposits are studied. The first set of field samples come from a volcanogenic massive sulfide (VMS) deposit, the second part from a stratiform sedimentary copper (SSC) deposit. Different approaches are used to analyze the data. First, univariate regression (UVR) is used. However, due to the strong influence of matrix effects, this is not suitable for the quantitative analysis of copper grades. Second, the multivariate method of partial least squares regression (PLSR) is used, which is more suitable forIts properties make copper one of the world’s most important functional metals. Numerous megatrends are increasing the demand for copper. This requires the prospection and exploration of new deposits, as well as the monitoring of copper quality in the various production steps. A promising technique to perform these tasks is Laser Induced Breakdown Spectroscopy (LIBS). Its unique feature, among others, is the ability to measure on site without sample collection and preparation. In this work, copper-bearing minerals from two different deposits are studied. The first set of field samples come from a volcanogenic massive sulfide (VMS) deposit, the second part from a stratiform sedimentary copper (SSC) deposit. Different approaches are used to analyze the data. First, univariate regression (UVR) is used. However, due to the strong influence of matrix effects, this is not suitable for the quantitative analysis of copper grades. Second, the multivariate method of partial least squares regression (PLSR) is used, which is more suitable for quantification. In addition, the effects of the surrounding matrices on the LIBS data are characterized by principal component analysis (PCA), alternative regression methods to PLSR are tested and the PLSR calibration is validated using field samples.…
Author details: | Pia BrinkmannGND, Nicole KöllnerORCiD, Sven MerkORCiDGND, Toralf BeitzORCiD, Uwe AltenbergerORCiDGND, Hans-Gerd LöhmannsröbenORCiDGND |
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URN: | urn:nbn:de:kobv:517-opus4-584742 |
DOI: | https://doi.org/10.25932/publishup-58474 |
ISSN: | 1866-8372 |
Title of parent work (German): | Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe |
Publication series (Volume number): | Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe (1311) |
Publication type: | Postprint |
Language: | English |
Date of first publication: | 2023/01/11 |
Publication year: | 2023 |
Publishing institution: | Universität Potsdam |
Release date: | 2023/03/24 |
Tag: | LIBS; PCA; PLSR; UVR; copper-bearing minerals |
Issue: | 1311 |
Number of pages: | 19 |
Source: | Minerals 13 (2023) 1, Art. 113 DOI:10.3390/min13010113 |
Organizational units: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Chemie |
DDC classification: | 5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften |
Peer review: | Referiert |
Publishing method: | Open Access / Green Open-Access |
License (German): | CC-BY - Namensnennung 4.0 International |
External remark: | Bibliographieeintrag der Originalveröffentlichung |