Perovskite solid solutions–a Monte Carlo study of the deep earth analogue (K, Na)MgF3

Abstract

Understanding the behaviour of solid solutions over wide ranges of temperature and pressure remains a major challenge to both theory and experiment. Here we report a detailed exchange Monte Carlo study using a classical ionic model of the model perovskite parascandolaite-neighborite (K,Na)MgF 3 solid solution and its end-members for temperatures in the range 300-1000 K and pressures from 0-8 GPa. Full account is taken of the local environment of the individual cations, clustering and thermal effects. Properties considered include the crystal structure, phase transitions, the thermodynamics of mixing and the non-ideality of the solid solution. Clustering of the potassium ions is examined via a short-range order parameter. Where experimental data are available for comparison, agreement is very good.

Microstructure Maps of Complex Perovskite Materials from Extensive Monte Carlo Sampling Using Machine Learning Enabled Energy Model

“…In addition to mapping the mixing energies over the composition space, CSRO analysis can provide insights into the tendency toward phase segregation. In this study, we employed the Warren–Cowley short-range order (SRO) parameter α to analyze the tendency toward phase segregation between atomic pairs. , The SRO parameter α is defined as where the subscript A–B specifies the atomic pair (e.g., MA–FA or Br–I), P A–B is the conditional probability of finding atom type B in the specified neighbor shell of atom A, and C B is the nominal concentration of atom B. Therefore, α A–B = 0 implies a randomly distributed binary alloy, whereas a positive/negative α A–B implies the tendency for A–B segregation/mixing.…”

“…In this study, we employed the Warren−Cowley short-range order (SRO) parameter α to analyze the tendency toward phase segregation between atomic pairs. 47,48 The SRO parameter α is defined as…”