Due to their optimal bandgap size and large defect tolerance, nitrides are becoming pivotal materials in several optoelectronic devices, photovoltaics, and photocatalysts. A computational method that can accurately predict their electronic structures is indispensable for exploring new nitride materials. However, the relatively small bandgap of nitrides, which stems from the subtle balance between ionic and covalent bond characteristics, makes conventional density functional theory challenging to achieve satisfactory accuracy. Here, we employed a self-consistent hybrid functional where the Hartree–Fock mixing parameter is self-consistently determined and thus the empiricism of the hybrid functional is effectively removed to calculate the bandgaps of various nitride compounds. By comparing the bandgaps from the self-consistent hybrid functional calculations with the available experimental and high-level GW calculation results, we found that the self-consistent hybrid functional can provide a computationally efficient approach for quantitative predictions of nitride electronic structures with an accuracy level comparable to the GW method. Additionally, we aligned the band edge positions of various nitride compounds using self-consistent hybrid functional calculations, providing material design principles for heterostructures of nitride-based optoelectronic devices. We anticipate the wide use of the self-consistent hybrid functional for accelerating explorations and predictions of new nitride-based functional materials in various photoactive applications.
Assessment and prediction of band edge locations of nitrides using a self-consistent hybrid functional
Se-Jun Kim, Sébastien Lebègue, Hyungjun Kim, Won June Kim; Assessment and prediction of band edge locations of nitrides using a self-consistent hybrid functional. J. Chem. Phys. 14 July 2021; 155 (2): 024120. https://doi.org/10.1063/5.0054589
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