Electron, phonon and thermoelectric properties of Cu7PS6 crystal calculated at DFT level

Abstract

The promising class of the environment-friendly thermoelectrics is the copper-based argyrodite-type ion-conducting crystals exhibiting just extraordinary low thermal conductivity below the glass limit associated with the molten copper sublattice leading to a softening of phonon modes. To explain why the argyrodite structure containing copper ions favors the low thermal conductivity, we have utilized the ab initio calculations of the electron, phonon, and thermoelectric properties of Cu7PS6 crystal in the framework of the density functional and Boltzmann transport theories. To obtain the reliable thermoelectric properties of Cu7PS6, we take into account the dependence of the electron effective mass m* on the redundant carrier concentration n. We propose to use the Burstein–Moss effect for the calculation of the electron effective mass m* of a semiconductor. We have found the strong nonlinear character of copper atom vibrations in Cu7PS6 which exceeds substantially the similar values for phosphorous and sulfur atoms. The large vibration nonlinearity of the copper atoms found in Cu7PS6 explains the diffusion-like heat transfer and the relatively low coefficient of the lattice thermal conductivity (κ = 0.7 W/(m K)), which is favorable to achieve the large thermoelectric figure of merit.

Weak-Bonding Elements Lead to High Thermoelectric Performance in BaSnS3 and SrSnS3: A First-Principles Study

“…The absolute valence band maximum (VBM) and conduction band minimum (CBM) energies used in the fitting are corrected by deep core level according to the theory proposed by Wei et al The accuracy of the scattering rates generated by AMSET has been tested in many other IV–VI group compounds including SnO 2 , SnS, SnSe, PbS, and PbTe by yielding consistent results with the state-of-the-art EPW code . Furthermore, there have been a variety of studies implemented with the AMSET code calculating the electrical properties of compounds, such as RECuZnP 2 , Cu 7 PS 6 , Cs 3 Cu 2 I 5 , RFeO 3 , and BaBi 2 O 6 , which proves its robustness for a vast selection of materials. Finally, the scattering rates, combined with energy eigenvalues extracted from an interpolated dense k -grid of 37 × 77 × 21, are used as inputs for BoltzTraP2 to yield the electrical conductivity σ, Seebeck coefficient S , and carrier thermal conductivity κ e through the Onsager reciprocal relation …”

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A Novel Methodology Based on a Deep Neural Network and Data Mining for Predicting the Segmental Voltage Drop in Automated Guided Vehicle Battery Cells

“…Generally, the uneven charge distribution that is caused by the diffusion effect of an electrolyte in the presence of a charging current can be approximated by a first-order low-pass filter. In [39], the authors analyze why the structure of argyrodite containing copper ions contributes to its low thermal conductivity. To this end, they studied the electronic, phonon, and thermoelectric properties of a Cu7PS6 crystal, which was calculated at the DFT level, in the context of the density functional theory and Boltzmann transfer theory.…”