Heavy Liquid Separation Method for Enhancement of Trace Asbestos Detection

Powder X-ray diffraction (XRD) is a widely accepted technique for detecting trace asbestos content in solid samples. However, accurately quantifying asbestos concentrations below 0.5 wt% presents significant challenges with XRD alone. To address this limitation, we conducted a meticulous quantitativ...

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Veröffentlicht in:Crystals (Basel) 2024-01, Vol.14 (2), p.127
Hauptverfasser: Chornkrathok, Sasithorn, Dera, Przemyslaw, Nguyen, Phuong Q. H., Downs, Robert T.
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Sprache:eng
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Zusammenfassung:Powder X-ray diffraction (XRD) is a widely accepted technique for detecting trace asbestos content in solid samples. However, accurately quantifying asbestos concentrations below 0.5 wt% presents significant challenges with XRD alone. To address this limitation, we conducted a meticulous quantitative analysis using XRD on synthetic samples of talc-based powder spiked with varying amounts of natural tremolite and anthophyllite asbestos. At concentrations exceeding 0.5 wt%, both tremolite and anthophyllite displayed distinct XRD peaks. Yet, at lower concentrations (0.1 wt% and 0.05 wt%), the diffraction peaks of the contaminants became less prominent. To improve detection sensitivity, we explored different protocols of heavy liquid separation utilizing sodium polytungstate (SPT) to concentrate asbestos relative to the other mineral components. The optimized protocol, employing SPT with a density of 2.89 g/cm3, effectively separated amphibole asbestos from lighter, commonly associated minerals, like talc, clinochlore, and mica. Subsequent powder XRD analysis of the heavy fraction confirmed the successful removal of non-target materials, enhancing the diffraction peaks of tremolite and anthophyllite. Tremolite exhibited comparatively less weight loss than anthophyllite during this separation process. This study establishes the theoretical and practical viability of employing centrifugation in a heavy liquid to separate tremolite and anthophyllite from talc, providing valuable insights for asbestos detection and quantification in challenging scenarios.
ISSN:2073-4352
2073-4352
DOI:10.3390/cryst14020127