Predicting the thermal responses and radiopacity of multicomponent zinc–silicate bioglasses: A focus on ZnO, La2O3, SiO2 and TiO2

Regression surface modeling has been applied to examine and predict the network connectivity (NC), thermal properties and radiopacity of a series of La2O3–TiO2 doped zinc–silicate (Zn–Si) bioglasses. The objective of this work is to provide new regression models based on a design of mixture (DOM) approach for predicting the NC, thermal responses and radiopacity for phosphate free, Zn–Si bioglasses that include variable ratios of SiO2, ZnO, La2O3 and TiO2. To ensure a comprehensive examination of the composition–property relationships, the experimental design varied the ratios of SiO2, ZnO, La2O3 and TiO2 within the glass network. Regression models were deployed to analyze data derived from NC calculations, differential scanning calorimetry and axial CT scans. It was observed that, for the glasses examined, the NC ranged from 2.41 to 2.83. The observed values of glass transition temperature (Tg) ranged from 597 to 690 °C and for the first point of crystallization temperature (Tp1) it was observed that the values ranged from 620 to 700 °C. Both Tg and Tp1 regression models predominantly showed that an increase in La2O3 (at the expense of ZnO) results in an increase of both thermal properties. In addition, increasing the La2O3/ZnO ratio is also observed to result in a shift towards achieving higher levels of radiopacity. In general, regression modeling of the radiopacity data indicated that increased loadings of La2O3, TiO2 and ZnO are required at the expense of SiO2 in order to increase the radiopaque nature of the glasses. The application of this methodology provides a more statistically robust approach over existing models that exist in the literature for predicting the properties of multi-component zinc–silicates doped with La2O3 and TiO2.