卤化物
结晶
成核
钙钛矿(结构)
溶剂
化学
无机化学
二甲基乙酰胺
相(物质)
化学工程
材料科学
结晶学
有机化学
工程类
作者
Mriganka Singh,Maged Abdelsamie,Qihua Li,Tim Kodalle,Do Kyung Lee,Simon Arnold,Davide Raffaele Ceratti,Jonathan Slack,Craig P. Schwartz,Christoph J. Brabec,Shuxia Tao,Carolin M. Sutter‐Fella
标识
DOI:10.1021/acs.chemmater.3c00799
摘要
Triple cation, mixed halide perovskite compositions have been reported to be more thermally stable, exhibit fewer phase impurities, and show higher power conversion efficiency and better reproducibility than single cation perovskites. In this work, we explain the formation of Cs0.05FA0.81MA0.14Pb(I0.85Br0.15)3 via a multimodal in situ study combining structural information from synchrotron grazing-incidence wide-angle X-ray scattering (GIWAXS) and optical properties from photoluminescence (PL) spectroscopy with density functional theory calculations (DFT). The focus here is on the effects of the solvent and antisolvent during crystallization. The predominantly used solvents N,N-dimethylformamide (DMF), dimethyl sulfoxide (DMSO), and the antisolvent chlorobenzene (CB) as well as the solvent–antisolvent–precursor interactions are investigated. Given the high elemental complexity and mutual interdependencies between solvent, antisolvent, and perovskite precursors, we found significant differences in the crystallization pathways. DMF-pure precursors show the formation of the DMF-containing intermediate phase and the nucleation of compositionally distinct perovskite phases, while when DMSO is added, only crystalline α- and δ-phases were found. In addition, the presence of DMSO helps the formation of α-perovskite. Coordination energy and bond order (BO) calculations support our experimental findings. Dripping of CB induces nucleation at room temperature, slows the α-phase formation rate, and appears to reduce the nucleation radius. These findings provide novel insights into solvent, antisolvent, and perovskite precursor interactions and their formation pathways. The complexity of interactions between solvents and reagents highlights the importance of understanding these effects to further improve the reproducibility and optimize processing conditions.
科研通智能强力驱动
Strongly Powered by AbleSci AI