Computational identification of promising thermoelectric materials among known quasi-2D binary compounds

Quasi low-dimensional structures are abundant among known thermoelectric materials, primarily because of their low lattice thermal conductivities. In this work, we have computationally assessed the potential of 427 known binary quasi-2D structures in 272 different chemistries for thermoelectric performance. To assess the thermoelectric performance, we employ an improved version of our previously developed descriptor for thermoelectric performance [Yan et al., Energy Environ. Sci., 2015, 8, 983]. The improvement is in the explicit treatment of van der Waals interactions in quasi-2D materials, which leads to significantly better predictions of their crystal structures and lattice thermal conductivities. The improved methodology correctly identifies known binary quasi-2D thermoelectric materials such as Sb2Te3, Bi2Te3, SnSe, SnS, InSe, and In2Se3. As a result, we propose candidate quasi-2D binary materials, a number of which have not been previously considered for thermoelectric applications.