Cost-effective method for computational prediction of thermal conductivity in optical materials based on cubic oxides

In this paper we report on a computationally cost-effective method designed to estimate the thermal conductivity of optical materials based on cubic oxide including mixed ones, i.e. solid solutions of different oxides. The proposed methodology take advantage from Density Functional Theory (DFT) calculations to extract essential structural parameters and elastic constants which represent the inputs for revised versions of Slack and Klemens equations relating thermal conductivity to elastic constants. Slack equation is modified by the introduction of a corrective factor that incorporates the Grüneisen parameter γ, while in the revised Klemens equation a distortion parameter $$ accounting for the impact of point defects on lattice symmetry is added, which is a critical factor in determining thermal conductivity in optical materials with mixed compositions. The theoretical results were found in good agreement with experimental data, showing the reliability of our proposed methodology.