An algorithm of calculating transport parameters of thermoelectric materials using single Kane band model with Riemann integral methods

Abstract

We develop an algorithm called SKBcal to conveniently calculate within minutes the thermoelectric transport parameters such as reduced Fermi level (η), electronic thermal conductivity (κe), lattice thermal conductivity (κl), Hall factor (A), effective mass (m*), quality factor (β) and theoretical zT within the framework of single Kane band (SKB) model. The generalized Fermi–Dirac integral for SKB model is integrated by left Riemann integral method. A concept of significant digits of relative error is involved to determine the accuracy of calculation. Furthermore, a combined program of "For" and "While" is coded to set up an iteration for refining the reduced Fermi level. To easily obtain the quality factor, we re-derive the expression into a formula related to carrier mobility. The results calculated by SKBcal are consistent with the data reported in the literatures.

Understanding the Role of Oxygen-Passivated Grain Boundary in Modulating the Thermoelectric Properties of Sb2Te3 Thin Film

“…Second, a substantial reduction in the band gap can be observed in the oxygen-doped sample compared to undoped Sb 2 Te 3 . For degenerate semiconductors with Kane-type band dispersion, the effective mass of carriers ( m *) is proportional to the band-gap energy ( E g ) through the relationship ℏ 2 k 2 2 m normalb * = E ( 1 + E E g ) …”

Exploiting the fraternal twin nature of thermoelectrics and topological insulators in Zintl phases as a tool for engineering new efficient thermoelectric generators

“…Depending on the nature and degeneracy of the bands, there are established theoretical models such as the Single parabolic Band (SPB) or the Single Kane Band (SKB) models applied to parabolic and non-parabolic bands, respectively, 141–143 which can be used to predict the various aspects of a TE materials properties including the interdependence of the various transport parameters. These models provide a good opportunity to make relevant predictions that can inform materials optimization and design.…”