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PAOFLOW-Aided Computational Materials Design

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Functional materials are essential to human welfare and to provide foundations for emerging industries. As an alternative route to experimental materials discovery, computational materials designs are playing an increasingly significant role in the whole discovery process. In this work, we use an in-house developed python utility: PAOFLOW, which generates finite basis Hamiltonians from the projection of first principles plane-wave pseudopotential wavefunctions on pseudo atomic orbitals(PAO) for post-process calculation on various properties such as the band structures, density of states, complex dielectric constants, diffusive and anomalous spin and charge transport coefficients. In particular, we calculated the dielectric function of Sr-, Pb-, and Bi-substituted BaSnO3 over wide concentration ranges. Together with some high-throughput experimental study, our result indicates the importance of considering the mixed-valence nature and clustering effects upon substitution of BaSnO3 with Pb and Bi. We also studied two prototype ferroelectric rashba semiconductors, GeTe and SnTe, and found the spin Hall conductivity(SHC) can be large either in ferroelectric or paraelectric structure phase. Upon doping, the polar displacements in GeTe can be sustained up to a critical hole concentration while the tiny distortions in SnTe vanish at a minimal level of doping. Moreover, we investigated the sensitivity of two dimensional group-IV monochalcogenides …
Date: December 2019
Creator: Wang, Haihang
System: The UNT Digital Library