A network problem: Modelling alkali-silicate glasses with RMC

Structural models of four potassium-silicate glasses, (K2O)(x)(SiO2)(1-x) with x = 0, 0.15, 0.25 and 0.45, have been created using the reverse Monte Carlo (RMC) method. The current use of RMC for creating topologically constrained models of amorphous materials is described in detail. The models are based on the simultaneous combination of neutron diffraction and Si-29 magic angle spinning NMR data, thr latter for the first time. We show that the predictions of Modified Random Network theory are consistent with the data. It is found that models whose topology is determined by short-range chemical bonding constraints and the macroscopic density are able to reproduce all details of the structure factor, including its complex form at low momentum transfer. It is not necessary to 'build in' specific ring structures or other complex units beforehand; these arise naturally as a consequence of the constraints of density and chemical bonding.