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Impressive Thermoelectric Figure of Merit in Two-Dimensional Tetragonal Pnictogens: a Combined First-Principles and Machine-Learning Approach.

Supriya GhosalSuman ChowdhuryDebnarayan Jana
Published in: ACS applied materials & interfaces (2021)
Over the past decade, two-dimensional materials have gained a lot of interest due to their fascinating applications in the field of thermoelectricity. In this study, tetragonal monolayers of group-V elements (T-P, T-As, T-Sb, and T-Bi) are systematically analyzed in the framework of density functional theory in combination with the machine-learning approach. The phonon spectra, as well as the strain profile, dictate that these tetragonal structures are geometrically stable as well as they are potential candidates for experimental synthesis. Electronic analysis suggests that tetragonal pnictogens offer a band gap in the semiconducting regime. Thermal transport characteristics are investigated by solving the semiclassical Boltzmann transport equation. Exceptionally low lattice thermal conductivity has been observed as the atomic number increases in the group. The high Seebeck coefficient and electrical conductivity as well as the low thermal conductivity of T-As, T-Sb, and T-Bi lead to the generation of a very high thermoelectric figure of merit as compared to standard thermoelectric materials. Furthermore, the thermoelectric conversion efficiency of these materials has been observed to be much higher, which ensures their implications in thermoelectric device engineering.
Keyphrases
  • density functional theory
  • machine learning
  • molecular dynamics
  • artificial intelligence
  • big data
  • deep learning
  • magnetic resonance imaging
  • risk assessment
  • single molecule
  • high speed
  • contrast enhanced