Keywords :
halide perovskites; NMR spectroscopy; periodic DFT calculations; structure elucidation; Accurate prediction; Dynamic property; Halide perovskites; NMR chemical shifts; Periodic density functional theory; Solid-state NMR spectroscopy; Structural feature; Tandem solar cells; Catalysis; Biochemistry; Drug Discovery; Physical and Theoretical Chemistry; Organic Chemistry; Inorganic Chemistry
Abstract :
[en] Solid state NMR spectroscopy is swiftly emerging as useful tool to characterize the structure, composition and dynamic properties of lead halide perovskites. On the other hand, interpretation of solid state NMR signatures is often challenging, because of the potential presence of many overlapping signals in small range of chemical shifts, hence complicating the extraction of detailed structural features. Here, we demonstrate the reliability of periodic Density Functional Theory in providing theoretical support for the NMR characterization of halide perovskite compounds, considering nuclei with spin I=1/2. For light 1H and 13C nuclei, we predict NMR chemical shifts in good agreement with experiment, further highlighting the effects of motional narrowing. Accurate prediction of the NMR response of 207Pb nuclei is comparably more challenging, but we successfully reproduce the downshift in frequency when changing the halide composition from pure iodine to pure bromine. Furthermore, we confirm NMR as ideal tool to study mixed halide perovskite compounds, currently at the limelight for tandem solar cells and color-tunable light emission.
Funding text :
This work has been supported by Agence Nationale de la Recherche, project ANR‐18‐CE05‐0026 (MORELESS). Computational investigations were conducted thanks to HPC resources provided by [TGCC/CINES/IDRIS] under the allocation 2020‐A0010907682 made by GENCI. . warmly thanks Prof. , Prof. and Prof. for useful discussions. The authors warmly acknowledge the reviewers for their useful comments and suggestions, which overall contributed to the quality of the manuscript. C. Q Regis Gautier Nicolas Mercier Jens DittmerThis work has been supported by Agence Nationale de la Recherche, project ANR-18-CE05-0026 (MORELESS). Computational investigations were conducted thanks to HPC resources provided by [TGCC/CINES/IDRIS] under the allocation 2020-A0010907682 made by GENCI. C. Q. warmly thanks Prof. Regis Gautier, Prof. Nicolas Mercier and Prof. Jens Dittmer for useful discussions. The authors warmly acknowledge the reviewers for their useful comments and suggestions, which overall contributed to the quality of the manuscript.
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