Bødker Mikkel S, Mauro John C, Youngman Randall E, Smedskjaer Morten M
Department of Chemistry and Bioscience , Aalborg University , 9220 Aalborg , Denmark.
Department of Materials Science and Engineering , The Pennsylvania State University , University Park , Pennsylvania 16802 , United States.
J Phys Chem B. 2019 Feb 7;123(5):1206-1213. doi: 10.1021/acs.jpcb.8b11926. Epub 2019 Jan 24.
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 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.
预测氧化物玻璃原子尺度结构和性能的成分演变对于设计先进应用的新材料至关重要。最近，一种基于统计力学的方法已被用于预测二元磷酸盐玻璃中的成分-结构演变，而拓扑约束理论（TCT）在过去十年中已被用于预测各种氧化物和非氧化物玻璃系统中的结构-性能演变。在这项工作中，我们将这两种方法结合起来，以便能够定量预测玻璃化转变温度的成分依赖性和超结构单元的数量。研究对象是硼酸锂玻璃系统，因为它们具有有趣的结构特征（例如硼反常现象），并且有丰富的结构和性能数据可用。在这些玻璃中，当添加锂改性剂时，硼的平均配位数首先增加，然后随着网络解聚而降低。首先，基于文献中的硼核磁共振光谱数据，我们通过考虑键合偏好的相对焓和熵贡献，对硼酸锂玻璃的结构演变进行了统计描述。我们表明，仅基于少数玻璃成分的实验结构信息，就可以预测整个玻璃结构的演变（包括短程和中程）。然后我们表明，所开发的结构模型可以与先前建立的TCT模型相结合，以预测玻璃化转变温度的成分演变。因此，这项工作为具有定制性能的玻璃的计算设计开辟了一条新途径。
