Statistical approach to modeling relationships of composition – structure – property I: Alkaline earth phosphate glasses

This paper introduces a methodology of accurate property predictions for amorphous materials (focusing on oxide phosphate glass) based on statistical composition (C) – structure (S) – property (P) modeling. Utilizing literature reported 31P MAS NMR data (Qn, δiso, η) of binary alkaline earth phospha...
Ausführliche Beschreibung

This paper introduces a methodology of accurate property predictions for amorphous materials (focusing on oxide phosphate glass) based on statistical composition (C) – structure (S) – property (P) modeling. Utilizing literature reported 31P MAS NMR data (Qn, δiso, η) of binary alkaline earth phosphate glasses RO-P2O5 (R = Mg, Ca, Sr, Ba), unified relationships of RO and Qn (n = 2, 3) were firstly established. A statistical approach to modeling mathematic relationships of C-S, S-P and then C-S-P for the alkaline earth binary phosphate glasses was illustrated step by step. The C-S models of Q2 and Q3 were then used to calculate Q2 and Q3 in the mixed alkaline earth (MAE) phosphate glass, MgO-CaO-P2O5, which in turn result in S-P models accurately tracks the glass properties, density, Young's modulus, glass transition temperature, and Microhardness. The S-P models were also used to simulate non-linear relationships of the MAE phosphate glasses as a function of Q2/(Q2+Q3) from the glass network structure view point in comparison with the property responses to the change of MgO/(MgO + CaO). Within the entire composition space of the alkaline earth phosphate glasses with RO/P2O5 ≤ 1, the statistical C-S-P modeling for predicting glass properties, including glass transition temperature, Young's modulus, density, etc., requires no assumptions on glass structures or other constraints as compared with other theoretically based modeling approaches. Ausführliche Beschreibung