We use cookies to ensure that we give you the best experience on our website. By continuing to browse this repository, you give consent for essential cookies to be used. You can read more about our Privacy and Cookie Policy.

Durham Research Online
You are in:

Structure and properties of alkali aluminosilicate glasses and melts: insights from deep learning

Le Losq, Charles and Valentine, Andrew and Mysen, Bjorn O. and Neuville, Daniel R. (2021) 'Structure and properties of alkali aluminosilicate glasses and melts: insights from deep learning.', Geochimica et cosmochimica acta., 314 . pp. 27-54.


Aluminosilicate glasses and melts are of paramount importance for geo- and materials sciences. They include most magmas, and are used to produce a wide variety of everyday materials, from windows to smartphone displays. Despite this importance, no general model exists with which to predict the atomic structure, thermodynamic and viscous properties of aluminosilicate melts. To address this, we introduce a deep learning framework, ‘i-Melt’, which combines a deep artificial neural network with thermodynamic equations. It is trained to predict 18 different latent and observed properties of melts and glasses in the K2O-Na2O-Al2O3-SiO2 system, including configurational entropy, viscosity, optical refractive index, density, and Raman signals. Viscosity can be predicted in the 100-1015 log10 Pa·s range using five different theoretical frameworks (Adam-Gibbs, Free Volume, MYEGA, VFT, Avramov-Milchev), with a precision equal to, or better than, 0.4 log10 Pa·s on unseen data. Density and optical refractive index (through the Sellmeier equation) can be predicted with errors equal or lower than 0.02 and 0.006, respectively. Raman spectra for K2O-Na2O-Al2O3-SiO2 glasses are also predicted, with a relatively high mean error of ∼25 % due to the limited data set available for training. Latent variables can also be predicted with good precisions. For example, the glass transition temperature, Tg, can be predicted to within 19 K, while the melt configurational entropy at the glass transition, Sconf(Tg), can be predicted to within 0.8 J mol-1 K-1. Applied to rhyolite compositions, i-Melt shows that the rheological threshold separating explosive and effusive eruptions correlates with an increase in the fraction of non-bridging oxygens in rhyolite melts as their alkali/Al ratio becomes larger than 1. Exploring further the effect of the K/(K+Na) ratio on the properties of alkali aluminosilicate melts with compositions varying along a simplified alkali magmatic series trend, we observe that K-rich melts have systematically different structures and higher viscosities compared to Na-rich melts. Combined with the effects of the K/(K+Na) ratio on other parameters, such as the solubility, solution mechanisms and speciation of volatile elements, this could ultimately influence the eruptive dynamics of volcanic systems emitting Na-rich or K-rich alkali magmas.

Item Type:Article
Full text:(P) Proof
Download PDF (In Press, Journal Pre-Proof)
Full text:(VoR) Version of Record
Available under License - Creative Commons Attribution 4.0.
Download PDF
Publisher Web site:
Publisher statement:© 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license
Date accepted:19 August 2021
Date deposited:07 September 2021
Date of first online publication:28 August 2021
Date first made open access:07 September 2021

Save or Share this output

Look up in GoogleScholar