Ab initio study of mechanical and thermal properties of GeTe-based and PbSe-based high-entropy chalcogenides.

Scientific reports(2023)

引用 0|浏览1
暂无评分
摘要
GeTe-based and PbSe-based high-entropy compounds have outstanding thermoelectric (TE) performance and crucial applications in mid and high temperatures. Recently, the optimization of TE performance of high-entropy compounds has been focused on reducing thermal conductivity by strengthening the phonon scattering process to improve TE performance. We report a first-principles investigation on nine GeTe-based high-entropy chalcogenide solid solutions constituted of eight metallic elements (Ag, Pb, Sb, Bi, Cu, Cd, Mn, and Sn) and 13 PbSe-based high-entropy chalcogenide solid solutions: PbSbSnSeTeS (x = 0.1, 0.2, 0.25, 0.3, 0.35, 0.4, 0.45, and y = 0) and PbSbSnSeTeS (y = 0.05, 0.1, 0.15, 0.2, 0.25 and x = 0.25). We have investigated the mechanical properties focusing on Debye temperature (Θ), thermal conductivity (κ), Grüneisen parameter (γ), dominant phonon wavelength (λ), and melting temperature (T). We find that the lattice thermal conductivity is significantly reduced when GeTe is alloyed into the following compositions: GeSbPbTe, GeAgSbPbBiTe, and GeAgSbPbMnBiTe. This reduction is due to the mass increase and strain fluctuations. The results also show that GeAgSbPbBiTe solid solution has the lowest Young's modulus (30.362 GPa), bulk and shear moduli (18.626 and 12.359 GPa), average sound velocity (1653.128 m/sec), Debye temperature (151.689 K), lattice thermal conductivity (0.574 W.m.K), dominant phonon wavelength (0.692 Å), and melting temperature (535.91 K). Moreover, GeAgSbPbBiTe has the highest Grüneisen parameter with a reduced and temperature-independent lattice thermal conductivity. The positive correlation between Θ and κ is revealed. Alloying of PbSe-based high-entropy by Sb, Sn, Te, and S atoms at the Se and Pb sites resulted in much higher shear strains resulted in the reduction of phonon velocity, a reduced Θ, and a lower lattice thermal conductivity.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要