Exploring the Defect Landscape and Dopability of Chalcogenide Perovskite BaZrS 3

作者：Rushik Desai, Shubhanshu Agarwal, Kiruba Catherine Vincent, Alejandro Strachan, Rakesh Agrawal, Arun Mannodi‐Kanakkithodi · 发表于：The Journal of Physical Chemistry C · 年份：2025 · DOI：10.1021/acs.jpcc.5c01597 · 被引用次数：9 · 研究领域：Perovskite Materials and Applications、Chalcogenide Semiconductor Thin Films、Advanced Thermoelectric Materials and Devices

BaZrS 3 is a chalcogenide perovskite that has shown promise as a photovoltaic absorber, but its performance is limited because of defects and impurities, which have a direct influence on carrier concentrations. Functional dopants that show lower donor-type or acceptor-type formation energies than naturally occurring defects can help tune the optoelectronic properties of BaZrS 3 . In this work, we applied first-principles computations to comprehensively investigate the defect landscape of BaZrS 3, including all intrinsic defects and a set of selected impurities and dopants. BaZrS 3 intrinsically exhibits n-type equilibrium conductivity under both S-poor and S-rich conditions, which remains largely unchanged in the presence of O and H impurities. La and Nb dopants created stable donor-type defects which make BaZrS 3 even more n-type, whereas As and P dopants formed amphoteric defects with relatively high formation energies. This work highlights the difficulty of creating p-type BaZrS 3 owing to the low formation energies of donor defects, both intrinsic and extrinsic. Defect formation energies were also used to compute expected defect concentrations and make comparisons with experimentally reported values. Our dataset of defects in BaZrS 3 paves the path for training machine learning models to subsequently perform larger-scale prediction and screening of defects and dopants across many chalcogenide perovskites, including cation-site or anion-site alloys.