Cubic halide perovskites as potential low thermal conductivity materials: A combined approach of machine learning and first-principles calculations

Thermal conductivity is the key factor affecting thermoelectric properties of materials. Here, machine-learning techniques combined with first-principles calculations are used to identify the cubic halide perovskites CsBBr3 (B = Ca, Cd, and Sn) with ultralow thermal conductivity. Based on the Boltzmann transport equation within the relaxation time approximation, we demonstrate this type of perovskites have remarkably low lattice thermal conductivities kappa(L) similar to 0.4 - 1 W/mK at 300 K. We employ the self-consistent phonon theory incorporating both cubic and quartic anharmonicity, which is considered from the bubble and loop self-energy diagrams rather than many-body perturbation theory. We show that the approach yields a cubic-tetragonal phase transition of CsCaBr3 at temperature T-c = 226 - 265 K, in good agreement with the experimental value of 239 K. An anomalously temperature dependence of kappa L is observed in CsCdBr3, where the coherent term account for 26% of the total lattice thermal conductivity. We also demonstrate that the hardening of vibrations in low-lying phonon modes offset the phonon population effect as temperature increases by reducing the available phase space.