Experimental Determinations and Modelling of the Viscosity of Multicomponent Natural Silicate Melts: Volcanological Implications

The main objective of this study is to investigate and model the
viscosity of multicomponent natural silicate melts and constrain
the compositional effects which affect such a parameter. The
results of this study, relevant to all petrological and
volcanological processes which involve some transport mechanism,
will be applied to volcanic setting. An extensive experimental
study was performed, which constituted the basis for the general
modelling of Newtonian viscosity in terms of composition and
temperature. Composition, viscosity and density of selected samples
were investigated at different water contents. The experimental
method involved measuring the viscosity of dry and hydrated melts
under superliquidus and supercooled conditions. In the high
temperature range (1050 – 1600 °C) viscosities from 10-0.5 to 105
Pa·s were obtained using a concentric cylinder apparatus.
Measurements of both dry and hydrated samples in the low
temperature (616-860 °C) - high viscosity (108.5 – 1012 Pa·s)
interval, from glassy samples quenched after high temperature
viscometry, were performed using the dilatometric method of
micropenetration. Hydrated samples measured in the supercooled
state were synthesized, using a piston cylinder apparatus, between
1100° and 1600° C at 10 kbar. Water contents were measured using
the Karl Fischer Titration (KFT) method. Fourier-Transform Infrared
(FTIR) spectroscopy was used before and after the experiments in
order to check that the water content was homogeneously distributed
in the samples and that water had not been lost. Major element
compositions of the dry remelted samples were determined using an
electron microprobe. Newtonian viscosities of silicate liquids were
investigated in a range between 10-1 to 1011.6 Pa s and
parameterised using the non-linear 3 parameter (ATVF, BTVF and T0)
TVF equation. The data provided in this work are combined also with
previous data from Whittington et al. (2000, 2001); Dingwell et al.
(1996); Neuville et al. (1993). There are strong numerical
correlations between parameters (ATVF, BTVF and T0) that mask the
effect of composition. Wide ranges of ATVF, BTVF and T0 values can
be used to describe individual datasets. This is true even when the
data are numerous, well-measured and span a wide range of
experimental conditions. In particular, “strong” liquids (liquids
that are Arrhenian or slightly deviate from Arrhenian behaviour)
place only minor restrictions on the absolute ranges of ATVF, BTVF
and T0. Therefore, strategies for modelling the effects on
compositions should be built around high-quality datasets collected
on non-Arrhenian liquids. x The relationships between important
quantities such as the fragility F, characterizing the deviation
from Arrhenian rheological behaviour, are quantified in terms of
the chemical, structure-related parameter NBO/T. Initial addition
of network modifying elements to a fully polymerised liquid (i.e.
NBO/T=0) results in a rapid increase in F. However, at NBO/T values
above 0.4-0.5 further addition of a network modifier has little
effect on fragility. This parameterisation indicates that this
sharp change in the variation of fragility with NBO/T is due to a
sudden change in the configurational properties and rheological
regimes, owing to the addition of network modifying elements. The
resulting TVF parameterisation has been also used to build up a
predictive model for Arrhenian to non-Arrhenian melt viscosity. The
model accommodates the effect of composition via an empirical
parameter called here the “structure modifier” (SM). SM is the
summation of molar oxides of Ca, Mg, Mn, half of the total iron
Fetot, Na and K. This approach is validated by the highly
predictive capability of the viscosity model. The model reproduces
all the original data set with about 10%, of the measured values of
logη over the entire range of composition in the temperature
interval 700-1600 °C. The combination of calorimetric and
viscosimetric data has enabled a simple expression to be used to
predict shear viscosity at the glass transition, that is the
temperature which defines the transition from a liquid-like to a
solid-like rheological behaviour. The basis for this stems from the
equivalence of the relaxation times for both enthalpy and shear
stress relaxation in a wide range of silicate melt compositions
(Gottsmann et al., 2002). A shift factor that relates cooling rate
data with viscosity at the glass transition appears to be slightly
dependent on the melt composition. Finally, the effect of water
content on decreasing the viscosity of silicate melts has also been
parameterised using a modified TVF expression (Giordano et al.,
2000). This leads to an improvement in our knowledge of the
non-Arrhenian behaviour of silicate melts over a wide compositional
range from basaltic to rhyolitic and from trachytic to peralkaline
phonolite compositions in the temperature interval pertaining to
volcanic and subvolcanic processes. The viscosities of natural
hydrous basaltic liquids are shown to be lower than those of
hydrous phonolites, whereas thachytes show viscosity that are
higher than those of phonolites and lower that those of rhyolites.
This is consistent with the style of eruption associated with these
compositions, with trachytes generating eruptions that are
dominantly explosive (e.g. xi Phlegrean Fields volcano), compared
to the highly explosive style of rhyolitic volcanoes, the mixed
explosive-effusive style of phonolitic volcanoes (e.g. Vesuvius)
and the dominantly effusive style of basalts. Variations in
composition between the trachytes translate into differences in
liquid viscosity of nearly two orders of magnitude in dry
conditions, and less than one order of magnitude in hydrous
conditions. These differences increase significantly when the
estimated eruptive temperatures of different eruptions at Phlegrean
Fields are taken into account. At temperatures close to those of
natural magmas and in the case of low viscosity hydrous liquids the
uncertainty of the calculations is large, although it cannot be
quantified, due to a lack of measurements under these conditions.