Predicting Composition-Structure Relations in Alkali Borosilicate Glasses Using Statistical Mechanics
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...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2019-07-01
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| Series: | Frontiers in Materials |
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| Online Access: | https://www.frontiersin.org/article/10.3389/fmats.2019.00175/full |
| _version_ | 1818946797522911232 |
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| author | Mikkel S. Bødker Søren S. Sørensen John C. Mauro Morten M. Smedskjaer |
| author_facet | Mikkel S. Bødker Søren S. Sørensen John C. Mauro Morten M. Smedskjaer |
| author_sort | Mikkel S. Bødker |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-20T08:20:43Z |
| format | Article |
| id | doaj.art-4303817d8a4b45559e058c97d4fc32c1 |
| institution | Directory Open Access Journal |
| issn | 2296-8016 |
| language | English |
| last_indexed | 2024-12-20T08:20:43Z |
| publishDate | 2019-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Materials |
| spelling | doaj.art-4303817d8a4b45559e058c97d4fc32c12022-12-21T19:47:01ZengFrontiers Media S.A.Frontiers in Materials2296-80162019-07-01610.3389/fmats.2019.00175473914Predicting Composition-Structure Relations in Alkali Borosilicate Glasses Using Statistical MechanicsMikkel S. Bødker0Søren S. Sørensen1John C. Mauro2Morten M. Smedskjaer3Department of Chemistry and Bioscience, Aalborg University, Aalborg, DenmarkDepartment of Chemistry and Bioscience, Aalborg University, Aalborg, DenmarkDepartment of Materials Science and Engineering, The Pennsylvania State University, University Park, PA, United StatesDepartment of Chemistry and Bioscience, Aalborg University, Aalborg, DenmarkPredicting 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.https://www.frontiersin.org/article/10.3389/fmats.2019.00175/fullglassborosilicatesmodelingstatistical mechanicsstructure |
| spellingShingle | Mikkel S. Bødker Søren S. Sørensen John C. Mauro Morten M. Smedskjaer Predicting Composition-Structure Relations in Alkali Borosilicate Glasses Using Statistical Mechanics Frontiers in Materials glass borosilicates modeling statistical mechanics structure |
| title | Predicting Composition-Structure Relations in Alkali Borosilicate Glasses Using Statistical Mechanics |
| title_full | Predicting Composition-Structure Relations in Alkali Borosilicate Glasses Using Statistical Mechanics |
| title_fullStr | Predicting Composition-Structure Relations in Alkali Borosilicate Glasses Using Statistical Mechanics |
| title_full_unstemmed | Predicting Composition-Structure Relations in Alkali Borosilicate Glasses Using Statistical Mechanics |
| title_short | Predicting Composition-Structure Relations in Alkali Borosilicate Glasses Using Statistical Mechanics |
| title_sort | predicting composition structure relations in alkali borosilicate glasses using statistical mechanics |
| topic | glass borosilicates modeling statistical mechanics structure |
| url | https://www.frontiersin.org/article/10.3389/fmats.2019.00175/full |
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