Quantitative X-ray fluorescence micro-analysis of wood samples and visualization of tree rings
The following paper describes the quantitative analysis of wood samples of black pine (Pinus nigra) using a benchtop Micro X-ray Fluorescence (μXRF) device for elemental analysis and surface scanning. Calibration of the device for quantitative elemental analysis and local density measurements of woo...
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| Published in | Radiation physics and chemistry (Oxford, England : 1993) Vol. 218; p. 111603 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
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Elsevier Ltd
01.05.2024
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| Online Access | Get full text |
| ISSN | 0969-806X |
| DOI | 10.1016/j.radphyschem.2024.111603 |
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| Abstract | The following paper describes the quantitative analysis of wood samples of black pine (Pinus nigra) using a benchtop Micro X-ray Fluorescence (μXRF) device for elemental analysis and surface scanning. Calibration of the device for quantitative elemental analysis and local density measurements of wood was performed by utilizing characteristic X-ray line intensities and backscattered radiation intensities. The influence of a variable wood density and matrix composition on X-ray spectra were studied with Monte Carlo calculations. The Monte Carlo model was validated with a set of reference materials possessing known compositions and densities. It has been demonstrated that Monte Carlo simulations with the MCNP code, along with, only one reference material are required for the quantitative XRF analysis. The backscattered radiation in the XRF spectra can be used for simple recognition of individual tree rings and their corresponding shapes.
•Quantitative XRF micro-analysis of wood was introduced.•Effect of wood density in XRF was corrected with Monte Carlo method.•Local wood density was determined with X-ray densitometry.•Hidden tree rings in wood were recognized and their shapes visualised. |
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| AbstractList | The following paper describes the quantitative analysis of wood samples of black pine (Pinus nigra) using a benchtop Micro X-ray Fluorescence (μXRF) device for elemental analysis and surface scanning. Calibration of the device for quantitative elemental analysis and local density measurements of wood was performed by utilizing characteristic X-ray line intensities and backscattered radiation intensities. The influence of a variable wood density and matrix composition on X-ray spectra were studied with Monte Carlo calculations. The Monte Carlo model was validated with a set of reference materials possessing known compositions and densities. It has been demonstrated that Monte Carlo simulations with the MCNP code, along with, only one reference material are required for the quantitative XRF analysis. The backscattered radiation in the XRF spectra can be used for simple recognition of individual tree rings and their corresponding shapes.
•Quantitative XRF micro-analysis of wood was introduced.•Effect of wood density in XRF was corrected with Monte Carlo method.•Local wood density was determined with X-ray densitometry.•Hidden tree rings in wood were recognized and their shapes visualised. |
| ArticleNumber | 111603 |
| Author | Trojek, Tomáš Dušková, Aneta |
| Author_xml | – sequence: 1 givenname: Tomáš orcidid: 0000-0002-2136-4503 surname: Trojek fullname: Trojek, Tomáš email: tomas.trojek@fjfi.cvut.cz – sequence: 2 givenname: Aneta surname: Dušková fullname: Dušková, Aneta |
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| Cites_doi | 10.1002/xrs.3102 10.1016/j.dendro.2019.04.004 10.1016/j.dendro.2023.126091 10.1515/HF.2002.060 10.1016/j.nimb.2007.04.063 10.1002/jqs.1303 10.1016/j.scitotenv.2019.06.515 10.1016/j.radphyschem.2018.08.004 10.1016/j.radphyschem.2019.04.044 10.3390/ma15155425 10.1007/s00107-012-0636-5 10.12841/wood.1644-3985.S13.05 10.1016/j.ecolmodel.2015.12.015 10.3959/1536-1098-73.2.75 10.1016/j.dendro.2023.126092 10.1021/ef502380x 10.1016/j.quaint.2018.09.007 10.1063/1.2720459 10.1016/j.scitotenv.2017.12.229 |
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| References | Trojek, Bártová (bib18) 2019; 155 Beckhoff (bib1) 2006 Cook (bib2) 2010; 25 McKenzie, Parker, Pisaric, Arain (bib9) 2023; 79 Skonieczna, Małek, Polowy, Węgiel (bib15) 2014; 57 Devi, Kukarskih, Bubnov (bib3) 2023; 79 Piernik (bib11) 2022; 15 Hevia (bib6) 2018; 625 Rodriguez, Almeida, Tomazello-Filho, Carvalho (bib12) 2020; 708 Saarela (bib13) 2002; 56 Trojek (bib17) 2020; 167 Morgan (bib10) 2015; 29 Gaitan-Alvarez, Moya, Berrocal (bib4) 2019; 55 Šmit, Prokeš (bib16) 2019; 48 Sánchez-Salguero (bib14) 2019; 514 Website (bib21) Hevia (bib7) 2019; 690 Kletetschka, Procházka, Fantucci, Trojek (bib8) 2017; 73 Gielen (bib5) 2016; 324 Waters (bib20) 2007; 896 Zielenkiewicz, Radomski, Zawadzki (bib22) 2012; 70 Trojek, Čechák (bib19) 2007; 263 Website (10.1016/j.radphyschem.2024.111603_bib21) Beckhoff (10.1016/j.radphyschem.2024.111603_bib1) 2006 Hevia (10.1016/j.radphyschem.2024.111603_bib7) 2019; 690 Cook (10.1016/j.radphyschem.2024.111603_bib2) 2010; 25 Piernik (10.1016/j.radphyschem.2024.111603_bib11) 2022; 15 Saarela (10.1016/j.radphyschem.2024.111603_bib13) 2002; 56 Trojek (10.1016/j.radphyschem.2024.111603_bib18) 2019; 155 Trojek (10.1016/j.radphyschem.2024.111603_bib19) 2007; 263 Trojek (10.1016/j.radphyschem.2024.111603_bib17) 2020; 167 Hevia (10.1016/j.radphyschem.2024.111603_bib6) 2018; 625 Skonieczna (10.1016/j.radphyschem.2024.111603_bib15) 2014; 57 Waters (10.1016/j.radphyschem.2024.111603_bib20) 2007; 896 Morgan (10.1016/j.radphyschem.2024.111603_bib10) 2015; 29 McKenzie (10.1016/j.radphyschem.2024.111603_bib9) 2023; 79 Rodriguez (10.1016/j.radphyschem.2024.111603_bib12) 2020; 708 Gaitan-Alvarez (10.1016/j.radphyschem.2024.111603_bib4) 2019; 55 Šmit (10.1016/j.radphyschem.2024.111603_bib16) 2019; 48 Kletetschka (10.1016/j.radphyschem.2024.111603_bib8) 2017; 73 Sánchez-Salguero (10.1016/j.radphyschem.2024.111603_bib14) 2019; 514 Devi (10.1016/j.radphyschem.2024.111603_bib3) 2023; 79 Zielenkiewicz (10.1016/j.radphyschem.2024.111603_bib22) 2012; 70 Gielen (10.1016/j.radphyschem.2024.111603_bib5) 2016; 324 |
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