journal article·2024-01Open access

Uncovering the structural and photoelectric properties of perovskite crystals by joint multifaceted characterization and theoretical analysis

Aochen Du, Xingke Zheng, Genzhuang Li, Yun Ye, Enguo Chen, Sheng Xu, Tailiang Guo

Abstract

The potential of organic-inorganic hybrid perovskites, owing to their distinct photoelectric attributes and boosted photoluminescence stability, has garnered substantial attention. Despite comprehensive examinations of the synthesis and optical characteristics of FAPbBr 3 crystals, the understanding of their microstructure's implication on photoelectric applications, their electronic configuration, and electron-phonon interplay remains vague. In this study, we detailed the electronic configuration, phonon dispersion, and vibrational properties using density functional theory. We further calculated the formation enthalpy stability diagram. Characterization and calculation of the crystalline structure were accomplished via Rietveld refinement. Phonon dispersion curves, as well as total and partial phonon densities of states, were also calculated. The theoretical results align well with experimental Fourier infrared and Raman spectra. Beyond elementary characterization, we explored the photoelectric qualities of FAPbBr 3 crystals, thereby reaffirming the outstanding photoelectric attributes and extensive application potential. A non-contact fixed-point lighting device was designed based on the principle of electromagnetic induction coils, which proved the uniformity of crystal luminescence. According to the first principle, FAPbBr 3 possesses a Poisson ratio of 0.32, indicative of high flexibility, emphasizing their superb photoelectric characteristics and vast application scope.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Perovskite Materials and Applications · Solid-state spectroscopy and crystallography · Luminescence Properties of Advanced Materials

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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