Accurate Prediction of Band Structure of FeS(2): A Hard Quest of Advanced First-Principles Approaches

精确预测 FeS(2) 的能带结构:先进第一性原理方法的艰巨探索

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Abstract

The pyrite and marcasite polymorphs of FeS(2) have attracted considerable interests for their potential applications in optoelectronic devices because of their appropriate electronic and optical properties. Controversies regarding their fundamental band gaps remain in both experimental and theoretical materials research of FeS(2). In this work, we present a systematic theoretical investigation into the electronic band structures of the two polymorphs by using many-body perturbation theory with the GW approximation implemented in the full-potential linearized augmented plane waves (FP-LAPW) framework. By comparing the quasi-particle (QP) band structures computed with the conventional LAPW basis and the one extended by high-energy local orbitals (HLOs), denoted as LAPW + HLOs, we find that one-shot or partially self-consistent GW (G (0) W (0) and GW (0), respectively) on top of the Perdew-Burke-Ernzerhof (PBE) generalized gradient approximation with a converged LAPW + HLOs basis is able to remedy the artifact reported in the previous GW calculations, and leads to overall good agreement with experiment for the fundamental band gaps of the two polymorphs. Density of states calculated from G (0) W (0)@PBE with the converged LAPW + HLOs basis agrees well with the energy distribution curves from photo-electron spectroscopy for pyrite. We have also investigated the performances of several hybrid functionals, which were previously shown to be able to predict band gaps of many insulating systems with accuracy close or comparable to GW. It is shown that the hybrid functionals considered in general fail badly to describe the band structures of FeS(2) polymorphs. This work indicates that accurate prediction of electronic band structure of FeS(2) poses a stringent test on state-of-the-art first-principles approaches, and the G (0) W (0) method based on semi-local approximation performs well for this difficult system if it is practiced with well-converged numerical accuracy.

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