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Quantification of water in glasses using microRaman analysis
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I use methods outlined in Le Losq et al. (2012) and Shea et al. (2012, 2014) to quantify total water contents in pyroclast glasses. The advantage of the technique is its high spatial resolution (~1 micron spotsize) and the absence of any special sample preparation requirements (e.g. double polishing). Raman is therefore particularly suited for analyses of vesicular glasses, where other mainstream analytical techniques such as FTIR are too limited by the large analytical area requirements. Limitations of the technique are mostly related to (1) the lower signal/noise ratio compared to other spectroscopic techniques, and (2) the need for calibration standards.



How does it work?

The sample is illuminated by a laser (e.g. 'green laser' with a wavelength of 532 nm), and different interactions typically occur:
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Raman scattering is a form of inelastic interaction (different frequency/wavelength as incident photons from the laser), where a photo is scattered after interacting with matter. The difference in energy between the incident and scattered photons are a function of the energy needed to excite molecules to higher vibrational modes. These vibrational modes typify different molecules in a glass (e.g. Si-O-Si, Si-O-Al linkages, 'loose' H-O-H molecules) and each set of molecules/linkages can also have different vibrational modes (e.g. bending, stretching).



What does the Raman spectrum of a glass look like?
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The spectrum of a typical water-bearing glass has at least three principal regions of interest.

(1) The 'low frequency' or TOT region (200-600 cm-1) usually contains vibrational modes associated with bridging tetrahedron-oxygen-tetrahedron linkages (TOT) (dominantly 4+ cations like Si or Ti).

(2) The 'high frequency' or TO region (800-1200 cm-1) includes modes related to non-bridging tetrahedron-oxygen molecules (4+ and 3+ cations like Si, Ti, Al, Fe). Network modifiers (the 2+ and 1+ cations) also work to modify these band intensities by breaking the tetrahedron network. Together the entire 200-1200 cm-1 region is referred to as the aluminosilicate framework region 'ASF' (Le Losq et al. 2012).

(3) The water species region (2800-3800 cm-1) includes modes associated with H2O and OH bending and stretching. At least four sub-bands are thought to compose the total water band, associated with the different species and their different vibrational modes.




The plot on the right shows three spectra, a raw (top), baseline-corrected (middle), and baseline- and long-corrected spectrum. Baseline fitting is one of the most challenging aspects of quantification using Raman due to the degrees of freedom and operator variability in defining a 'good' fit. Linear, polynomial and cubic spline fits are all still currently in use by different analysts.






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These plots show baseline-corrected spectra for a rhyolite (top), a phonolite (middle) and a pumice from the AD79 eruption of Vesuvius (bottom). In vesicular samples that have been made into thin sections, epoxy signals can pollute the glass spectra and may need to be corrected (by acquiring an epoxy spectrum and unmixing the signal).









How can Raman spectra be used for quantification of water?

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Unlike FTIR, where a simple law (Beer-lambert) linking absorbance to water and interaction material properties can be used to quantify water species directly, Raman spectra cannot be used in the same fashion because no simple law exists to correlate Raman intensity with water concentration. In addition, intensities are highly variable depending on the laser source intensity used, instrument/detector/laser stability, Therefore, an 'external' calibration is needed, where standards of known H2O concentration are measured, and their ASF and H2O intensities or integrated peak areas are used to determine the H2O concentration of an unknown. To ensure less dependence on acquisition properties, the ratio of the H2O over the ASF peak provides an 'internal' calibration.




This plot of normalized water concentration (C/(100-C) vs. the ratio of the water over the aluminosilicate integrated band areas shows a good linear correlation, which can be used for quantification (the slope is simply a multiplication factor which can be applied to the H2O/ASF ratio of an unknown). In this case, the two calibration slopes are different, revealing that perhaps instrument type and spectra treatment may have an important effect on the slope. Therefore, each analyst should ensure that his calibration line is valid for his setup and spectra treatment routine.




Examples of applications

1) Measuring water in highly vesicular pumice samples
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Residual H2O can vary even within a single clast. Different textural regions (dense and vesicular) appear to be associated with different water contents (low and high), also correlating with Cl and major elements. These variations are thought to indicate small-scale (micron-cm) scale degassing along preferential magma deformation zones. See Shea et al. (2014) for details.



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Residual H2O also varies between different clasts from a single eruption unit (left figure shows low, modal and high vesicularity clasts from the AD79 eruption) and between different units. Data follows a H2O-vesicularity path dominated by outgassing (i.e. most of the degassing process has already happened). See Shea et al. (2012








2) Measuring water in highly crystalline samples
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Microlite-rich samples are also difficult to analyze with techniques that typically have coarser spatial resolution (FTIR, SIMS). Just like before, these problematic samples can be analyzed fairly well using microRaman. On the right is an example from a Mt. St. Helens breadcrust bomb (sample from Heather Wright) that is highly crystalline. A profile made of numerous spot analyses from the rim towards the interior of the bomb shows a slight decrease in H2O content, consistent with predictions that H2O continues to degas in the interior of bombs after fragmentation. In addition, the high variability of H2O is thought to be real and not an analytical artefact. This variability may be associated with microlite crystallization and spatially heterogeneous concentration of residual water (secondary boiling).





3) Assessing H2O heterogeneity in glassy samples
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example5A major question pertaining to analyses of experimental charges (e.g. for vesiculation or crystallization experiments) is whether water is homogeneous prior to and after the quench. Similarly, melt inclusions are a popular volatile time-capsule for petrologists and we often work under the assumption that H2O should be homogeneously distributed within the inclusions. Mapping H2O with Raman can therefore be helpful to test these questions and assumptions.



The maps shown on the right were acquired to determine whether the hydration experiments performed in Giachetti et al. (2015) contained water that was fairly well distributed accross the sample glasses. We were able to verify that even microlite-bearing charges did not display large/obvious variations in dissolved H2O contents.







The maps on the left show several melt inclusions with various degrees of H2O heterogeneity. Heterogeneity is often associated with microcrystalline phases.







4) Rehydration of glasses, diffusion modeling


Volcanic glasses can incorporate meteoric water at ambient temperatures during the 100s and 1000s of years following an eruption. Archaeologists and geologists ahave used this phenomenon to date artefacts and volcanic glasses in general (obsidian hydration dating). The high spatial resolution of Raman is useful here again to resolve such hydration rinds and develop diffusion models to extract either time information or H2O diffusivity information (if the sample age is independently known).


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The example above shows a trachyte obsidian from the Pu'u Wa'awa'a tephra sequence on the island of Hawaii. Raman H2O mapping and detailed concentration profiles suggest that significant secondary (meteoric) rehydration has occurred since the eruption (dated at around 110ka). From these profiles, we can extract crucial information about apparent/integrated H2O diffusivity at ambient temperature which is not readily available from laboratory experiments (it takes too long to develop hydration rinds at room temperature!).


Interested in quantification of H2O by Raman? Check out the SpeCTRa page for spectra treatment and analysis


More interesting reading on Raman...

Behrens H, Roux J, Neuville DR, Siemann M, 2006, Quantification of dissolved H2O in silicate glasses using confocal micro-Raman spectroscopy. Chem. Geol. 229: 96–112.

Di Muro A, Villemant B, Montagnac G, Scaillet B, Reynard B, 2006a, Quantification of water content and speciation in natural silicic glasses (phonolite, dacite, rhyolite) by confocal micro-Raman spectroscopy. Geochim. Cosmochim. Acta 70: 2868–2884

Le Losq C, Neuville DR, Moretti R, Roux J, 2012, Determination of water content in silicate glasses using Raman spectrometry: implications for the study of explosive volcanism. Am. Mineral. 97:779-790

Mercier M, Di Muro A, Giordano D, Métrich N, Lesne P, Pichavant M, Scaillet B, Clocchiatti R, Montagnac G, 2009, Influence of glass polymerisation and oxidation on micro-Raman water analysis in alumino-silicate glasses. Geochim.Cosmochim. Acta 73: 197–217

Mercier M, Di Muro A, Métrich N, Giordano D, Belhadj O, Mandeville C, 2010, Spectroscopic analysis (FTIR, Raman) of water in mafic and intermediate glasses and glass inclusions. Geochimica et Cosmochimica Acta 74: 5641–5656

Morizet,Y., Brooker, R. A., Iacono-Marziano, G. & Kjarsgaard, B. A. (2013). Quantification of dissolved CO2 in silicate glasses using Micro-Raman spectroscopy. American Mineralogist 98, 1788-1802

Thomas R, 2000, Determination of water contents of granite melt inclusions by confocal laser Raman microprobe spectroscopy. Am. Miner. 85: 868–872

Zajacz Z, Halter W, Malfait WJ, Bachmann O, Bodnar RJ, Hirschmann MM, Mandeville CW, 2005, A composition-independent quantitative determination of the water content in silicate glasses and silicate melt inclusions by confocal Raman spectroscopy. Contrib. to Mineral. and Petrol. 150: 631–642