Predicting Composition-Structure Relations in Alkali Borosilicate Glasses Using Statistical Mechanics

Mikkel S. Bødker, Søren S. Sørensen, John C. Mauro, Morten M. Smedskjaer

Research output: Contribution to journalArticle

Abstract

Predicting the atomic-scale structure of multicomponent glasses from their composition and thermal history would greatly accelerate the discovery of new engineering and functional glasses. A statistical mechanics-based approach has recently been applied to predict the composition-structure evolution in binary oxide glasses by determining the relative entropic and enthalpic contributions to the bonding preferences. In this work, we first establish the network modifier-former interaction parameters in sodium silicate and sodium borate glasses to predict the structural evolution in sodium borosilicate glasses. Due to the significant variations in the experimentally determined structural speciation in borosilicate glasses, we perform classical molecular dynamics (MD) simulations to establish and validate our structural model. We also show that the statistical mechanical model naturally accounts for the difference in structural speciation from MD simulations and NMR experiments, which in turn arises from the difference in cooling rate and thus thermal history of the glasses. Finally, we demonstrate the predictive capability of the model by accurately accounting for the structural evolution in potassium borosilicate glasses without using any adjustable model parameters. This is possible, because all the interaction parameters are already established in the potassium silicate, potassium borate, and sodium borosilicate glasses, respectively.

Original languageEnglish (US)
Article number175
JournalFrontiers in Materials
Volume6
DOIs
StatePublished - Jul 26 2019

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Statistical mechanics
Borosilicate glass
Alkalies
Glass
Potassium
Chemical analysis
Sodium
Silicates
Molecular dynamics
Sodium borate
Computer simulation
Oxides
Nuclear magnetic resonance
Cooling
Experiments

All Science Journal Classification (ASJC) codes

  • Materials Science (miscellaneous)

Cite this

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title = "Predicting Composition-Structure Relations in Alkali Borosilicate Glasses Using Statistical Mechanics",
abstract = "Predicting the atomic-scale structure of multicomponent glasses from their composition and thermal history would greatly accelerate the discovery of new engineering and functional glasses. A statistical mechanics-based approach has recently been applied to predict the composition-structure evolution in binary oxide glasses by determining the relative entropic and enthalpic contributions to the bonding preferences. In this work, we first establish the network modifier-former interaction parameters in sodium silicate and sodium borate glasses to predict the structural evolution in sodium borosilicate glasses. Due to the significant variations in the experimentally determined structural speciation in borosilicate glasses, we perform classical molecular dynamics (MD) simulations to establish and validate our structural model. We also show that the statistical mechanical model naturally accounts for the difference in structural speciation from MD simulations and NMR experiments, which in turn arises from the difference in cooling rate and thus thermal history of the glasses. Finally, we demonstrate the predictive capability of the model by accurately accounting for the structural evolution in potassium borosilicate glasses without using any adjustable model parameters. This is possible, because all the interaction parameters are already established in the potassium silicate, potassium borate, and sodium borosilicate glasses, respectively.",
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Predicting Composition-Structure Relations in Alkali Borosilicate Glasses Using Statistical Mechanics. / Bødker, Mikkel S.; Sørensen, Søren S.; Mauro, John C.; Smedskjaer, Morten M.

In: Frontiers in Materials, Vol. 6, 175, 26.07.2019.

Research output: Contribution to journalArticle

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