Abstract

High-performance thermoelectric (TE) materials rely on semiconductors with suitable intrinsic properties for which carrier concentrations can be controlled and optimized. To demonstrate the insights that can be gained in computational analysis when both intrinsic properties and dopability are considered in tandem, we combine the prediction of TE quality factor (intrinsic properties) with first-principles simulations of native defects and carrier concentrations for the binary Sn chalcogenides SnS, SnSe, and SnTe. The computational predictions are compared to a comprehensive data set of previously reported TE figures-of-merit for each material, for both p-type and n-type carriers. The combined analysis reveals that dopability limits constrain the TE performance of each Sn chalcogenide in a distinct way. In SnS, TE performance for both p-type and n-type carriers is hindered by low carrier concentrations, and improved performance is possible only if higher carrier concentrations can be achieved by suitable extrinsic dopants. For SnSe, the p-type performance of the Cmcm phase appears to have reached its theoretical potential, while improvements in n-type performance may be possible through tuning of electron carrier concentrations in the Pnma phase. Meanwhile, assessment of the defect chemistry of SnTe reveals that p-type TE performance is limited by, and n-type performance is not possible due to, the material’s degenerate p-type nature. This analysis highlights the benefits of accounting for both intrinsic and extrinsic properties in a computation-guided search, an approach that can be applied across diverse sets of semiconductor materials for TE applications.

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