Shuvam Gupta , Vivian Moutinho , Jose R.A. Godinho , Bradley M. Guy , Jens Gutzmer
{"title":"含稀土矿物包裹体颗粒材料的三维矿物定量:通过考虑局部体积和模糊效应实现亚体素分辨率","authors":"Shuvam Gupta , Vivian Moutinho , Jose R.A. Godinho , Bradley M. Guy , Jens Gutzmer","doi":"10.1016/j.tmater.2025.100050","DOIUrl":null,"url":null,"abstract":"<div><div>This study documents a significant enhancement to the recently introduced Mounted Single Particle Characterization and Mineralogical Analyses (MSPaCMAn) workflow for particulate samples by X-ray computed tomography analyses. This enhancement is used to quantify the abundance of small grains of rare earth minerals within particulate samples of iron ore. In the studied samples, rare earth minerals are typically present as minute grains. The small size creates challenges for X-ray computed tomography due to the well-known partial volume and blurring effects. This effect is particularly pronounced when the sizes of grains start to approach the sizes of voxels. The enhanced MSPaCMAn workflow incorporates new steps to improve the reliability of mineral characterization by simultaneously analyzing the grey values and geometrical properties of rare earth mineral grains and their host minerals. The refined workflow also enables the comprehensive characterization of particle surfaces. The results of the MSPaCMAn were validated by scanning electron microscopy-based automated mineralogy and X-ray powder diffraction data. The study is a step towards accurate and reproducible mineralogical quantification of particulate processing samples using X-ray 3D imaging.</div></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"7 ","pages":"Article 100050"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"3D mineral quantification of particulate materials with rare earth mineral inclusions: Achieving sub-voxel resolution by considering the partial volume and blurring effect\",\"authors\":\"Shuvam Gupta , Vivian Moutinho , Jose R.A. Godinho , Bradley M. Guy , Jens Gutzmer\",\"doi\":\"10.1016/j.tmater.2025.100050\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This study documents a significant enhancement to the recently introduced Mounted Single Particle Characterization and Mineralogical Analyses (MSPaCMAn) workflow for particulate samples by X-ray computed tomography analyses. This enhancement is used to quantify the abundance of small grains of rare earth minerals within particulate samples of iron ore. In the studied samples, rare earth minerals are typically present as minute grains. The small size creates challenges for X-ray computed tomography due to the well-known partial volume and blurring effects. This effect is particularly pronounced when the sizes of grains start to approach the sizes of voxels. The enhanced MSPaCMAn workflow incorporates new steps to improve the reliability of mineral characterization by simultaneously analyzing the grey values and geometrical properties of rare earth mineral grains and their host minerals. The refined workflow also enables the comprehensive characterization of particle surfaces. The results of the MSPaCMAn were validated by scanning electron microscopy-based automated mineralogy and X-ray powder diffraction data. The study is a step towards accurate and reproducible mineralogical quantification of particulate processing samples using X-ray 3D imaging.</div></div>\",\"PeriodicalId\":101254,\"journal\":{\"name\":\"Tomography of Materials and Structures\",\"volume\":\"7 \",\"pages\":\"Article 100050\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-01-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Tomography of Materials and Structures\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2949673X25000038\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Tomography of Materials and Structures","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2949673X25000038","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
3D mineral quantification of particulate materials with rare earth mineral inclusions: Achieving sub-voxel resolution by considering the partial volume and blurring effect
This study documents a significant enhancement to the recently introduced Mounted Single Particle Characterization and Mineralogical Analyses (MSPaCMAn) workflow for particulate samples by X-ray computed tomography analyses. This enhancement is used to quantify the abundance of small grains of rare earth minerals within particulate samples of iron ore. In the studied samples, rare earth minerals are typically present as minute grains. The small size creates challenges for X-ray computed tomography due to the well-known partial volume and blurring effects. This effect is particularly pronounced when the sizes of grains start to approach the sizes of voxels. The enhanced MSPaCMAn workflow incorporates new steps to improve the reliability of mineral characterization by simultaneously analyzing the grey values and geometrical properties of rare earth mineral grains and their host minerals. The refined workflow also enables the comprehensive characterization of particle surfaces. The results of the MSPaCMAn were validated by scanning electron microscopy-based automated mineralogy and X-ray powder diffraction data. The study is a step towards accurate and reproducible mineralogical quantification of particulate processing samples using X-ray 3D imaging.