Kettlewell Brenna, Boyd Daniel
School of Biomedical Engineering, Dalhousie University, Halifax, NS B3H 4R2, Canada.
Department of Applied Oral Sciences, Faculty of Dentistry, Dalhousie University, 5981 University Avenue, P.O. Box 15000, Halifax, NS B3H 4R2, Canada.
Materials (Basel). 2024 Apr 28;17(9):2073. doi: 10.3390/ma17092073.
This study employs a systematic and predictive modelling approach to investigate the structure and properties of multi-component borate glasses. In particular, this work is focused on understanding the individual and interaction effects of multiple constituents on several material properties. By leveraging advanced modeling techniques, this work examines how the inclusion and variation of BO, CaF, TiO, ZnO, and NaCO influence the glass network, with particular attention to modifier fractions ≥ 30 mol%. This research addresses the gap in knowledge regarding the complex behavior of borate glasses in this high modifier fraction range, known as the borate anomaly, where prediction of glass structure and properties becomes particularly challenging. The use of a design of mixtures (DoM) approach facilitated the generation of polynomial equations indicating the influence of mixture components on various responses, enabling the prediction and optimization of glass properties over broad compositional ranges despite being within the anomalous region. This methodical approach not only advances our understanding of borate glass systems but also underscores the importance of predictive modelling in the accelerated design and development of novel glass materials for diverse applications.
本研究采用系统的预测建模方法来研究多组分硼酸盐玻璃的结构和性能。具体而言，这项工作专注于理解多种成分对几种材料性能的单独作用和相互作用影响。通过利用先进的建模技术，本研究考察了BO、CaF、TiO、ZnO和NaCO的加入及变化如何影响玻璃网络，特别关注改性剂含量≥30摩尔%的情况。本研究填补了在该高改性剂含量范围内硼酸盐玻璃复杂行为方面的知识空白，该范围被称为硼酸盐异常，在此范围内预测玻璃结构和性能极具挑战性。采用混合设计（DoM）方法有助于生成多项式方程，表明混合物成分对各种响应的影响，从而能够在广泛的成分范围内预测和优化玻璃性能，尽管处于异常区域内。这种有条不紊的方法不仅增进了我们对硼酸盐玻璃系统的理解，还强调了预测建模在加速设计和开发用于各种应用的新型玻璃材料方面的重要性。
