Mounted Single Particle Characterization for 3D Mineralogical Analysis—MSPaCMAn
This paper demonstrates a new method to classify mineral phases in 3D images of particulate materials obtained by X-ray computed micro-tomography (CT), here named mounted single particle characterization for 3D mineralogical analysis (MSPaCMAn). The method allows minimizing the impact of imaging art...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-08-01
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| Series: | Minerals |
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| Online Access: | https://www.mdpi.com/2075-163X/11/9/947 |
| _version_ | 1797518116621647872 |
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| author | Jose R. A. Godinho Barbara L. D. Grilo Friedrich Hellmuth Asim Siddique |
| author_facet | Jose R. A. Godinho Barbara L. D. Grilo Friedrich Hellmuth Asim Siddique |
| author_sort | Jose R. A. Godinho |
| collection | DOAJ |
| description | This paper demonstrates a new method to classify mineral phases in 3D images of particulate materials obtained by X-ray computed micro-tomography (CT), here named mounted single particle characterization for 3D mineralogical analysis (MSPaCMAn). The method allows minimizing the impact of imaging artefacts that make the classification of voxels inaccurate and thus hinder the use of CT to characterize natural particulate materials. MSPaCMAn consists of (1) sample preparation as particle dispersions; (2) image processing optimized towards the labelling of individual particles in the sample; (3) phase identification performed at the particle level using an interpretation of the grey-values of all voxels in a particle rather than of all voxels in the sample. Additionally, the particle’s geometry and microstructure can be used as classification criteria besides the grey-values. The result is an improved accuracy of phase classification, a higher number of detected phases, a smaller grain size that can be detected, and individual particle statistics can be measured instead of just bulk statistics. Consequently, the method broadens the applicability of 3D imaging techniques for particle analysis at low particle size to voxel size ratio, which is typically limited due to unreliable phase classification and quantification. MSPaCMAn could be the foundation of 3D semi-automated mineralogy similar to the commonly used 2D image-based semi-automated mineralogy methods. |
| first_indexed | 2024-03-10T07:25:39Z |
| format | Article |
| id | doaj.art-fa95eae7755f4bddb2b5389edfd5b1a9 |
| institution | Directory Open Access Journal |
| issn | 2075-163X |
| language | English |
| last_indexed | 2024-03-10T07:25:39Z |
| publishDate | 2021-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Minerals |
| spelling | doaj.art-fa95eae7755f4bddb2b5389edfd5b1a92023-11-22T14:20:57ZengMDPI AGMinerals2075-163X2021-08-0111994710.3390/min11090947Mounted Single Particle Characterization for 3D Mineralogical Analysis—MSPaCMAnJose R. A. Godinho0Barbara L. D. Grilo1Friedrich Hellmuth2Asim Siddique3Helmholtz-Zentrum Dresden-Rossendorf, Helmholtz Institute Freiberg for Resource Technology, Chemnitzer Straße 40, 09599 Freiberg, GermanyHelmholtz-Zentrum Dresden-Rossendorf, Helmholtz Institute Freiberg for Resource Technology, Chemnitzer Straße 40, 09599 Freiberg, GermanyHelmholtz-Zentrum Dresden-Rossendorf, Helmholtz Institute Freiberg for Resource Technology, Chemnitzer Straße 40, 09599 Freiberg, GermanyHelmholtz-Zentrum Dresden-Rossendorf, Helmholtz Institute Freiberg for Resource Technology, Chemnitzer Straße 40, 09599 Freiberg, GermanyThis paper demonstrates a new method to classify mineral phases in 3D images of particulate materials obtained by X-ray computed micro-tomography (CT), here named mounted single particle characterization for 3D mineralogical analysis (MSPaCMAn). The method allows minimizing the impact of imaging artefacts that make the classification of voxels inaccurate and thus hinder the use of CT to characterize natural particulate materials. MSPaCMAn consists of (1) sample preparation as particle dispersions; (2) image processing optimized towards the labelling of individual particles in the sample; (3) phase identification performed at the particle level using an interpretation of the grey-values of all voxels in a particle rather than of all voxels in the sample. Additionally, the particle’s geometry and microstructure can be used as classification criteria besides the grey-values. The result is an improved accuracy of phase classification, a higher number of detected phases, a smaller grain size that can be detected, and individual particle statistics can be measured instead of just bulk statistics. Consequently, the method broadens the applicability of 3D imaging techniques for particle analysis at low particle size to voxel size ratio, which is typically limited due to unreliable phase classification and quantification. MSPaCMAn could be the foundation of 3D semi-automated mineralogy similar to the commonly used 2D image-based semi-automated mineralogy methods.https://www.mdpi.com/2075-163X/11/9/947computed tomographyminerals engineeringraw materialsX-ray imagingprocessing3D particle |
| spellingShingle | Jose R. A. Godinho Barbara L. D. Grilo Friedrich Hellmuth Asim Siddique Mounted Single Particle Characterization for 3D Mineralogical Analysis—MSPaCMAn Minerals computed tomography minerals engineering raw materials X-ray imaging processing 3D particle |
| title | Mounted Single Particle Characterization for 3D Mineralogical Analysis—MSPaCMAn |
| title_full | Mounted Single Particle Characterization for 3D Mineralogical Analysis—MSPaCMAn |
| title_fullStr | Mounted Single Particle Characterization for 3D Mineralogical Analysis—MSPaCMAn |
| title_full_unstemmed | Mounted Single Particle Characterization for 3D Mineralogical Analysis—MSPaCMAn |
| title_short | Mounted Single Particle Characterization for 3D Mineralogical Analysis—MSPaCMAn |
| title_sort | mounted single particle characterization for 3d mineralogical analysis mspacman |
| topic | computed tomography minerals engineering raw materials X-ray imaging processing 3D particle |
| url | https://www.mdpi.com/2075-163X/11/9/947 |
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