An Automated Ab Initio Approach for Identifying Small Band Gap Ferroelectric

ORAL

Abstract

Small band gap ferroelectrics are scarce and yet hold promise for optoelectronics applications. In this work, we leverage the electronic and symmetry requirements that give rise to ferroelectricity to search for new small band gap ferroelectrics using the Materials Project and Inorganic Crystal Structure Database. We create an automated workflow that combines database queries, symmetry tools and high-throughput DFT to identify candidate classes of ferroelectrics. Using density functional theory and beyond, we reveal accurate band gap trends for new and previously synthesized compounds. The effect of chemical doping on the polarization and energy barrier is discussed for select cases.

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Authors

  • Tess Smidt

    Physics Department, UC Berkeley; Molecular Foundry, Lawrence Berkeley National Lab

  • Sebastian Reyes-Lillo

    Molecular Foundry, Lawrence Berkeley National Lab; Department of Physics, University of California Berkeley, Physics Department, UC Berkeley; Molecular Foundry, Lawrence Berkeley National Lab

  • Jeffrey Neaton

    University of California, Berkeley; Lawrence Berkeley National Laboratory, Lawrence Berkeley Natl Lab/UC Berkeley, Physics Department, UC Berkeley, The Molecular Foundry, LBNL \& Kavli Energy NanoSciences Institute at Berkeley, Berkeley, CA, Molecular Foundry, Lawrence Berkeley National Lab; Department of Physics, University of California Berkeley; Kavli Energy NanoSciences Insitute, Molecular Foundry, LBNL; Dept. of Physics, UC Berkeley; Kavli ENSI, UC Berkeley; Molecular Foundry, LBNL; Kavli Energy Nanosciences Institute at Berkeley, Dept. of Physics, UC Berkeley \& Lawrence Berkeley National Lab (USA), Molecular Foundry, LBNL, Dept. of Physics, UC-Berkeley and Kavli ESNI at Berkeley, Molecular Foundry, Lawrence Berkeley National Laboratory, Physics Department, UC Berkeley; Molecular Foundry, Lawrence Berkeley National Lab; Kavli Energy NanoSciences Institute at Berkeley