DOE OSTI2019
In this paper, we report the computational investigation of a series of ternary $X_4Y_2Z$ and $X_5Y_2Z_2$ compounds with $X$ =Mg, Ca, Sr, Ba; $Y$ =P, As, Sb, Bi; and $Z$ =S, Se, Te. The compositions for these materials were predicted through a search guided by machine learning, while the structures were resolved using the minima hopping crystal structure prediction method. Based on ab initio calculations, we predict that many of these phases are thermodynamically stable. In particular, 21 of the $X_4Y_2Z$ compounds crystallize in a tetragonal structure with $I\bar{4}2d$ symmetry, and exhibit band gaps in the range of 0.8 and 1.8 eV, well suited for various energy applications. We show that several candidates (in particular $X_4Y_2$ Te and $X_4\mathrm{Sb_2Se}$) exhibit good photo absorption in the visible range, while others (e.g., $\mathrm{Ba_4Sb_2Se}$) show excellent thermoelectric performance due to high power factors and extremely low lattice thermal conductivities.