A sulfur vacancy-related defect has been recently experimentally identified as the source of unintentional n-type doping in pyrite FeS2, a potential earth-abundant, nontoxic, ultralow-cost absorber for thin film solar cells. Historically, however, theory has not supported this possibility, as simple S mono-vacancies have high formation energies, as well as donor state energies inconsistent with experiment. Here, we use density functional theory to perform a detailed and systematic study of S vacancies in pyrite, considering not only mono-vacancies but also multiple forms of vacancy clusters. We first confirm that the S mono-vacancy indeed produces a donor state too far from the conduction band minimum to explain recent experiments. Four configurations of S di-vacancies are then investigated, leading to the finding that S-S dimer vacancies induce an elevated donor state near the middle of the gap. Importantly, significant binding energy for defect clustering occurs for both this defect and a trans-S di-vacancy, which features two mono-vacancies across a common Fe coordination center. We then combine these defects to construct a tetra-vacancy complex, calculating a deep donor state 0.41 eV below the conduction band minimum, thus achieving the best agreement to date with the experimental value of 0.23 eV. There is a yet more sizable binding energy associated with this tetra-vacancy, suggesting that further vacancy clustering is likely in pyrite. We then outline how initial vacancy incorporation, as a source for clustering, could occur, via routes governed by either thermal equilibrium or kinetic trapping of surface-created vacancies during pyrite crystal growth. This study thus advances S vacancy clusters as the defects likely responsible for the n-type doping effects observed in pyrite FeS2, advancing the understanding of doping in this promising photovoltaic material.
Bibliographical noteFunding Information:
Work was supported by the customers of Xcel Energy through a grant from the Renewables Development Fund. The authors would like to thank the Minnesota Super Computing institute for generous computing resources. The authors thank Hung Q. Pham for useful discussion during the project.
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