July 15, 2002

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.

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

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By Ludwig-Maximilians-Universität München