Asbestos fibre identification by Raman microspectroscopy

Bard, Delphine; Yarwood, J.; Tylee, Barry

doi:10.1002/(sici)1097-4555(199710)28:10<803::aid-jrs151>3.0.co;2-7

Cited by 54 publications

(46 citation statements)

References 2 publications

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“…4) agrees well with literature data of chrysotile (e.g., Bard et al 1997;Kloprogge et al 1999;Rinaudo et al 2003;Auzende et al 2004). However, Kloprogge et al (1999) list additional Raman bands at 374, 607, 629, and 709 cm -1 originating from band deconvolution in the low-frequency range.…”

Section: Raman and Ftir Spectra At Ambient Conditionssupporting

confidence: 91%

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The dehydroxylation of chrysotile: A combined in situ micro-Raman and micro-FTIR study

Trittschack

Grobéty

2013

American Mineralogist

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One of the most important mechanisms releasing water in subducting slabs of oceanic crust is connected to the dehydration of serpentinized oceanic rocks. This study reports on a detailed investigation of the transition from chrysotile-an important serpentine mineral-to forsterite through the release of water.The dehydroxylation of natural chrysotile and the subsequent phase change to forsterite was studied by in situ micro-Raman and micro-FTIR spectroscopy in the temperature range of 21 to 871 C. Comparisons were made with previously published data of lizardite-1T. Micro-Raman spectra obtained in the low-frequency (100-1200 cm -1 ) and high-frequency ranges (3500-3800 cm -1 ) were complemented by micro-FTIR measurements between 2500 and 4000 cm -1 to study changes in the chrysotile structure as a function of dehydroxylation progress. In general, room-temperature chrysotile bands lie at higher wavenumbers than equivalent bands of lizardite-1T except of three bands positioned at 301.7, 317.5, and 345.2 cm -1 . Different band assignments of chrysotile and lizardite-1T Raman spectra from literature are compared. The most striking assignments concern the three aforementioned Raman bands and those lying between 620 and 635 cm -1 . The present data support a chrysotile-or at least curved TO layer related origin of the latter. Deconvolution of overlapping OH stretching bands at room temperature revealed the presence of five (FTIR) and four (Raman) bands, respectively. A slight change in the ditrigonal distortion angle during heating and the effects of a radius-dependent dehydroxylation progress can be shown. Furthermore, it was possible to identify a quenchable talclike phase immediately after the onset of the dehydroxylation at 459 C. Main bands of this phase are positioned at 184.7, 359.2, and 669.1 cm -1 and a single OH band at 3677 cm -1, and are thus quite similar to those reported for dehydroxylating lizardite-1T. Their appearance coincides with the formation of forsterite. A maximum in the integral intensity of the talc-like intermediate is reached at 716 C. At higher temperatures, the intermediate phase breaks down and supports the accelerated growth of forsterite. The lack of OH bands with the concomitant appearance of broad chrysotile-related modes in the low-frequency range after heating the sample to 871 C indicates the presence of a heavily disordered phase still resembling chrysotile. However, there are no spectral evidences for further Si-and/ or Mg-rich amorphous phases during the dehydroxylation and no indications for a relationship between the breakdown of the talc-like phase and the growth of enstatite as previously reported in literature.

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Section: Raman and Ftir Spectra At Ambient Conditionssupporting

confidence: 91%

“…In general, older literature document just two IR active bands at 3651 and 3697 cm -1 (Farmer 1974) and two Raman active bands at around 3685 and 3700 cm -1 (Bard et al 1997), respectively. These findings are mostly caused by the lack of band deconvolution.…”

Section: Raman and Ftir Spectra At Ambient Conditionsmentioning

confidence: 99%

The dehydroxylation of chrysotile: A combined in situ micro-Raman and micro-FTIR study

Trittschack

Grobéty

2013

American Mineralogist

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“…To realize sorting, it is necessary to understand the physical and chemical properties of waste (e.g., density or electromagnetic property) and to determine whether the waste contains asbestos. The purpose of studies on the identification of asbestos [13][14][15][16] is to develop an accurate method for asbestos analysis. Bassani et al [17] reported the use of remote sensing to detect asbestos in roofing sheets, which enabled scanning…”

Section: Introductionmentioning

confidence: 99%

Grouping by Visual Appearance of Construction and Demolition Waste for Sorting Time Reduction with the Aim of Removing Asbestos-Containing Materials

Asakura¹,

Nakagawa²

2017

Int J Waste Resour

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“…To realize sorting, it is necessary to understand the physical and chemical properties, such as density and magnetic property, or to determine whether the waste contains asbestos fiber or not. The purpose of studies on the identification of asbestos [10][11][12][13] is to develop an accurate method for asbestos analysis. The use of remote sensing to detect asbestos in roofing sheets, which enabled scanning of ACM by batch in large urban areas was reported [14].…”

Section: Introductionmentioning

confidence: 99%

Determination and Sorting of Asbestos-Containing Material by Visual Observation

Asakura¹

2014

AJEP

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Abstract:A rapid method for the determination of asbestos fiber at an intermediate treatment facility for construction and demolition waste (CDW) is required. Although the rapid method which involves visual observation has been developed, the determination accuracy and time are unknown. The purpose of this study was to determine the identification rate of asbestos-containing material (ACM: > 0.1w%), the time required for asbestos fiber determination by visual observation, and the asbestos content in CDW. After participating in a short training course for ACM determination, persons who did not have any knowledge of asbestos fiber determination were able to determine ACM in CDW by visual observation. Using the results of visual observation, an ACM sorting model was formulated. The model enabled simulation of asbestos content after sorting by inputting asbestos content distribution into CDW before sorting. However, 0.35 w% of asbestos still remained in the non-ACM fraction, i.e., the content was > 0.1 w%. The relationship between the number of sorters and the total sorting time for disaster waste from the Great East Japan Earthquake was presented. It was found that a very long time and a large number of people were required for sorting.

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Asbestos fibre identification by Raman microspectroscopy

Cited by 54 publications

References 2 publications

The dehydroxylation of chrysotile: A combined in situ micro-Raman and micro-FTIR study

The dehydroxylation of chrysotile: A combined in situ micro-Raman and micro-FTIR study

Grouping by Visual Appearance of Construction and Demolition Waste for Sorting Time Reduction with the Aim of Removing Asbestos-Containing Materials

Determination and Sorting of Asbestos-Containing Material by Visual Observation

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