Approximate chemical analysis of volcanic glasses using Raman spectroscopy

Abstract

The effect of chemical composition on the Raman spectra of a series of natural calcalkaline silicate glasses has been quantified by performing electron microprobe analyses and obtaining Raman spectra on glassy filaments (~450 µm) derived from a magma mingling experiment. The results provide a robust compositionally‐dependent database for the Raman spectra of natural silicate glasses along the calcalkaline series. An empirical model based on both the acquired Raman spectra and an ideal mixing equation between calcalkaline basaltic and rhyolitic end‐members is constructed enabling the estimation of the chemical composition and degree of polymerization of silicate glasses using Raman spectra. The model is relatively insensitive to acquisition conditions and has been validated using the MPI‐DING geochemical standard glasses1 as well as further samples. The methods and model developed here offer several advantages compared with other analytical and spectroscopic methods such as infrared spectroscopy, X‐ray fluorescence spectroscopy, electron and ion microprobe analyses, inasmuch as Raman spectroscopy can be performed with a high spatial resolution (1 µm2) without the need for any sample preparation as a nondestructive technique. This study represents an advance in efforts to provide the first database of Raman spectra for natural silicate glasses and yields a new approach for the treatment of Raman spectra, which allows us to extract approximate information about the chemical composition of natural silicate glasses using Raman spectroscopy. We anticipate its application in handheld in situ terrestrial field studies of silicate glasses under extreme conditions (e.g. extraterrestrial and submarine environments). © 2015 The Authors Journal of Raman Spectroscopy Published by John Wiley & Sons Ltd

Raman spectra of Martian glass analogues: A tool to approximate their chemical composition

“…This is evident, for example, when comparing the rhyolitic (sample Y12, iron‐poor) end‐member spectrum reported in Di Genova et al . [] with the iron‐rich rhyolite spectrum showed in Di Genova et al . [] (sample Fsp1).…”

“…Moreover, Raman spectroscopy has also been developed as a tool to investigate volcanic (calc‐alkaline) glasses and approximate their chemical composition [ Di Genova et al ., ], to estimate the iron oxidation state of iron‐rich basaltic glasses and alkali‐ and silica‐rich glasses [ Di Genova et al ., ], as well as to determine the presence of water in silicate glasses [e.g., Thomas , ; Zajacz et al ., ; Behrens et al ., ; Le Losq et al ., ].…”

“…Here we expand the compositionally dependent Raman database recently presented [ Di Genova et al ., , ] to iron‐rich basaltic and rhyolitic melts relevant to Mars. Those papers have shown how the presence of iron, and its oxidation state, greatly affects the Raman spectral features of glasses.…”

“…Assuming a linear mixing model for the evolution of the acquired spectra, we retrieve a Raman parameter, which is then employed to estimate the chemical composition of glassy samples. The linear assumption has been validated in previous studies [ Di Genova et al ., , ] as enabling the extraction of quantitative information from Raman spectra. Here we confirm that a more complex parameterization of the spectra is not required.…”

A New Parameterization of Volcanic Ash Complex Refractive Index Based on NBO/T and SiO2 Content

“…NBO/T has potential advantages over simply using SiO 2 content, which we will test in this study, as it allows further discrimination of absorption features between different silicate compositions. The dependence of the T–O − bond absorption feature on the degree of silicate polymerization has previously been used in remote‐sensing applications for determining rock composition in the infrared (e.g., Walter & Salisbury, ) and more recently in estimating composition using Raman spectroscopy (e.g., Di Genova et al, ). While silicate infrared absorption is the basis for the remote sensing of volcanic ash clouds, the ability to determine ash composition from infrared spectra is only beginning to be explored (Clarisse et al, ; Gangale et al, ).…”