Statistical Mechanical Modeling of Borate Glass Structure and Topology: Prediction of Superstructural Units and Glass Transition Temperature

Mikkel Sandfeld Bødker, John C. Mauro, Randall E. Youngman, Morten Mattrup Smedskjær

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

4 Citationer (Scopus)

Resumé

Predicting the compositional evolution of the atomic-scale structure and properties of oxide glasses is important for designing new materials for advanced applications. A statistical mechanics-based approach has recently been applied to predict the composition-structure evolution in binary phosphate glasses, while topological constraint theory (TCT) has been applied in the last decade to predict the structure-property evolution in various oxide and nonoxide glass systems. In this work, we couple these two approaches to enable quantitative predictions of the compositional dependence of glass transition temperature and the population of superstructural units. The object of the study is the lithium borate glass system because they feature interesting structural characteristics (e.g., boron anomaly), and ample structure and property data are available. In these glasses, the average coordination number of boron first increases when lithium modifiers are added and then later decreases accompanied by network depolymerization. First, on the basis of 10 B nuclear magnetic resonance spectroscopy data from literature, we present a statistical description of the structural evolution in lithium borate glasses by accounting for the relative enthalpic and entropic contributions to the bonding preferences. We show that the entire glass structure evolution (both short- and intermediate-range) can be predicted based on experimental structural information for only a few glass compositions. We then show that the developed structural model can be combined with a previously established TCT model to predict the compositional evolution of the glass transition temperature. This work thus opens a new avenue for the computational design of glasses with tailored properties.

OriginalsprogEngelsk
TidsskriftJournal of Physical Chemistry Part B: Condensed Matter, Materials, Surfaces, Interfaces & Biophysical
Vol/bind123
Udgave nummer5
Sider (fra-til)1206-1213
Antal sider8
ISSN1520-6106
DOI
StatusUdgivet - 7 feb. 2019

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Borates
borates
glass transition temperature
topology
Topology
Glass
glass
predictions
Constraint theory
lithium borates
Lithium
Boron
Oxides
boron
Glass transition temperature
depolymerization
Depolymerization
Statistical mechanics
oxides
magnetic resonance spectroscopy

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title = "Statistical Mechanical Modeling of Borate Glass Structure and Topology: Prediction of Superstructural Units and Glass Transition Temperature",
abstract = "Predicting the compositional evolution of the atomic-scale structure and properties of oxide glasses is important for designing new materials for advanced applications. A statistical mechanics-based approach has recently been applied to predict the composition-structure evolution in binary phosphate glasses, while topological constraint theory (TCT) has been applied in the last decade to predict the structure-property evolution in various oxide and nonoxide glass systems. In this work, we couple these two approaches to enable quantitative predictions of the compositional dependence of glass transition temperature and the population of superstructural units. The object of the study is the lithium borate glass system because they feature interesting structural characteristics (e.g., boron anomaly), and ample structure and property data are available. In these glasses, the average coordination number of boron first increases when lithium modifiers are added and then later decreases accompanied by network depolymerization. First, on the basis of 10 B nuclear magnetic resonance spectroscopy data from literature, we present a statistical description of the structural evolution in lithium borate glasses by accounting for the relative enthalpic and entropic contributions to the bonding preferences. We show that the entire glass structure evolution (both short- and intermediate-range) can be predicted based on experimental structural information for only a few glass compositions. We then show that the developed structural model can be combined with a previously established TCT model to predict the compositional evolution of the glass transition temperature. This work thus opens a new avenue for the computational design of glasses with tailored properties.",
author = "B{\o}dker, {Mikkel Sandfeld} and Mauro, {John C.} and Youngman, {Randall E.} and Smedskj{\ae}r, {Morten Mattrup}",
year = "2019",
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T1 - Statistical Mechanical Modeling of Borate Glass Structure and Topology: Prediction of Superstructural Units and Glass Transition Temperature

AU - Bødker, Mikkel Sandfeld

AU - Mauro, John C.

AU - Youngman, Randall E.

AU - Smedskjær, Morten Mattrup

PY - 2019/2/7

Y1 - 2019/2/7

N2 - Predicting the compositional evolution of the atomic-scale structure and properties of oxide glasses is important for designing new materials for advanced applications. A statistical mechanics-based approach has recently been applied to predict the composition-structure evolution in binary phosphate glasses, while topological constraint theory (TCT) has been applied in the last decade to predict the structure-property evolution in various oxide and nonoxide glass systems. In this work, we couple these two approaches to enable quantitative predictions of the compositional dependence of glass transition temperature and the population of superstructural units. The object of the study is the lithium borate glass system because they feature interesting structural characteristics (e.g., boron anomaly), and ample structure and property data are available. In these glasses, the average coordination number of boron first increases when lithium modifiers are added and then later decreases accompanied by network depolymerization. First, on the basis of 10 B nuclear magnetic resonance spectroscopy data from literature, we present a statistical description of the structural evolution in lithium borate glasses by accounting for the relative enthalpic and entropic contributions to the bonding preferences. We show that the entire glass structure evolution (both short- and intermediate-range) can be predicted based on experimental structural information for only a few glass compositions. We then show that the developed structural model can be combined with a previously established TCT model to predict the compositional evolution of the glass transition temperature. This work thus opens a new avenue for the computational design of glasses with tailored properties.

AB - Predicting the compositional evolution of the atomic-scale structure and properties of oxide glasses is important for designing new materials for advanced applications. A statistical mechanics-based approach has recently been applied to predict the composition-structure evolution in binary phosphate glasses, while topological constraint theory (TCT) has been applied in the last decade to predict the structure-property evolution in various oxide and nonoxide glass systems. In this work, we couple these two approaches to enable quantitative predictions of the compositional dependence of glass transition temperature and the population of superstructural units. The object of the study is the lithium borate glass system because they feature interesting structural characteristics (e.g., boron anomaly), and ample structure and property data are available. In these glasses, the average coordination number of boron first increases when lithium modifiers are added and then later decreases accompanied by network depolymerization. First, on the basis of 10 B nuclear magnetic resonance spectroscopy data from literature, we present a statistical description of the structural evolution in lithium borate glasses by accounting for the relative enthalpic and entropic contributions to the bonding preferences. We show that the entire glass structure evolution (both short- and intermediate-range) can be predicted based on experimental structural information for only a few glass compositions. We then show that the developed structural model can be combined with a previously established TCT model to predict the compositional evolution of the glass transition temperature. This work thus opens a new avenue for the computational design of glasses with tailored properties.

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DO - 10.1021/acs.jpcb.8b11926

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VL - 123

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JO - Journal of Physical Chemistry Part B: Condensed Matter, Materials, Surfaces, Interfaces & Biophysical

JF - Journal of Physical Chemistry Part B: Condensed Matter, Materials, Surfaces, Interfaces & Biophysical

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