Mechanical properties estimation of 2D–3D mixed organic-inorganic perovskites based on methylammonium and phenylethyl-ammonium system using a combined experimental and first-principles approach
Source abstract
Abstract
Hybrid organic-inorganic perovskites (HOIPs) are considered as one of the most promising candidates for photovoltaic application. Although, a lot of research has been done for improvement in efficiency and stability of the devices made from this material, enough attention has not been paid to the mechanical robustness of this material system. However, it is impossible to design flexible devices without having knowledge of the mechanical properties of HOIPs. Nanoindentation measurements have been used in the current study to evaluate the elastic modulus of thin films of 3D and 2D perovskite, i.e., methylammonium lead iodide (MAPbI 3), phenylethyl-ammonium based 2D perovskite [(PEA) 2PbI 4] and 2D–3D mixed perovskite. The elastic modulus for the 3D perovskite has been found to be ∼ 22.8 GPa, while it is ∼ 15.1 GPa for the 2D perovskite. First principles density functional theory (DFT) calculations done as part of the current work on pure 3D and 2D perovskites also corroborate our experimental results. The effect of the 2D–3D mixture on the elastic modulus has also been investigated, and it has been found the modulus values increases with the increase in the percentage of 3D perovskite within the 2D–3D perovskite mixture. Moreover, a change in the volume fraction of PEA in the 2D–3D mixed perovskite results in a mixture of quasi-2D perovskite in different proportions within the mixed perovskite. The knowledge gained by comparing DFT and experimental methodologies allows for the logical design of multilayer HOIPs with mechanical properties that are suitable for strain-intensive and flexible optoelectronic applications.
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Research context
OpenAlex topics: Perovskite Materials and Applications · Conducting polymers and applications · Organic and Molecular Conductors Research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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