Solubility of glasses in the system P2O5-CaO-MgO-Na2O-TiO2: Experimental and modeling using artificial neural networks

Phosphate glasses in the system P₂O₅-CaO-MgO-Na₂O-TiO₂ for use as degradable implant materials were produced. In order to classify their solubility behavior, dissolution experiments were performed in deionized water for 60 min at 98 °C. Resulting solutions were analyzed using ICP-OES. In addition, pH measurements were carried out in physiological NaCl solution. With increasing phosphorus oxide content, the glasses showed a higher solubility and gave lower pH values in aqueous solution. This was caused by changes in the glass structure, as long phosphate chains are more susceptible to hydration than smaller phosphate groups. These changes in glass structure were followed by ³¹P MAS-NMR experiments. Increasing sodium oxide concentrations in exchange for calcium or magnesium oxide also increased the glass solubility by disrupting ionic cross links between chains. By contrast, addition of titania made the glasses more stable towards dissolution by cross linking smaller phosphate groups. The aim of this study was to find a relationship between glass composition and solubility behavior. As classical linear methods of data analysis were unsuitable due to the complexity of the relationship, preliminary artificial neural networks analyses were performed and were found to be an interesting tool for modeling the solubility behavior of phosphate glasses.