Abstract
The emergence of perovskite solar cell materials is expected to end the quest for sustainable and affordable energy from the sun mainly due to their appreciating power conversion efficiency (PCE) (>25 %) within a decade after their discovery. Despite their impressive performance in the laboratory, the large-scale production of perovskite-based optoelectronic materials is limited by their structural instability in ambient conditions. When exposed to water, excessive heat or oxygen, the material degrades concomitantly. In this thesis, we outline a three-step comprehensive scheme towards the attainment of robust perovskites for optoelectronic applications using density functional theory, ab initio thermodynamics and a machine learning based Bayesian optimization structural search. Our procedure consist of three steps. In the first step, we developed a scheme to curate potential inorganic coating materials from an existing database. Our selection criterion focused on large band gap (≥ 3 eV) binary and ternary semiconductors with lattices comparable to our perovskite substrates. We also filtered out candidates that are reactive with water. Without performing the actual interface calculations, we assumed perfect interfaces and calculated the lattice mismatch between the coating-perovskites. In the end, we curated 93 potential coating candidates. In the second step, we studied surface models of CsPbI3 and MAPbI3 by analysing their structural and electronic properties. For these perovskites, we studied the cubic (Pm3m) and orthorhombic (Pnma) polymorphs of CsPbI3 as well as the tetragonal (I4cm) phase of MAPbI3. In all three phases, we investigated (001) surface models with MAI-, CsI- and PbI2-terminations (CsI-T, MAI-T and PbI2-T). For these terminations, we studied the clean surfaces and a series of reconstructed surface models by removing and adding constituent elements as well as their complexes. We find clean CsI-T and MAI-T to be more stable than PbI2-T models. Additionally, we find CsI-T and MAI-T models with removed and added nonpolar complexes to be more stable than those with polar constituents. Our band structure analysis revealed no mid gap states despite changes in atomic positions in the models. The final step combines steps 1 and 2 to study the coating-perovskite interface. Here, we investigated ZnO, SrZrO3 and ZrO2 as coatings on CsI-T and three reconstructed surface models with added PbI2 and CsI units . The registries of the interface were identified with Bayesian optimization. Using DFT, we determine the final atomic structure at the interfaces through structural relaxations and explore the level alignments at the interfaces with hybrid DFT calculations. Our analysis of the level alignment at the coating-perovskite interfaces reveal no detrimental mid-gap states, but substrate-dependent valence and conduction band offsets. While ZnO and SrZrO3 act as insulators on CsPbI3, ZrO2 might be suitable as electron transport layer with the right interface engineering.
Translated title of the contribution | Robust Hybrid Perovskites Photovoltaics from Organic-Inorganic Materials |
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Original language | English |
Qualification | Doctor's degree |
Awarding Institution |
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Print ISBNs | 978-952-64-0778-4 |
Electronic ISBNs | 978-952-64-0779-1 |
Publication status | Published - 2022 |
MoE publication type | G5 Doctoral dissertation (article) |
Keywords
- perovskites
- density functional theory
- surface
- interface
- coating
- substrate