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  • Title: Efficient and tunable enhancement of NLO performance for indaceno-based donor moiety in A-π-D-π-D-π-A type first DSSC design by end-capped acceptors.
    Author: Hassan AU, Sumrra SH, Mustafa G, Nazar MF, Zafar MN.
    Journal: J Mol Model; 2022 Dec 09; 29(1):4. PubMed ID: 36481993.
    Abstract:
    BACKGROUND: The organic dyes with non-fullerene acceptors (NFAs) have aided in the creation of competitive organic solar cells (OSCs) with long-term sustainability. A series of NFA dyes (IDIC-R1-IDIC-R9) have been designed by varying the end-capped fluorinated moieties (PD1-PD6) at indaceno (IDIC) core. METHODS: All the calculations were performed by density functional theory (DFT) and time-dependent DFT (TD-DFT)-based approaches. All the geometries were optimized at B3LYP/6-31G + (d,p) of DFT level at their ground state energies. Out of several density functionals, the CAM-B3LYP with 6-31G + (d,p) basis sets was selected after a benchmark study to carry out further calculations. All the dyes had their bandgaps in 0.11-3.12 eV while their starting reference dye had a bandgap value of 2.01 eV. RESULTS: Their ionization potential (IP) implied that these dyes have strong tendency to lose electrons. The λmax of the dyes was slightly redshifted from the IDIC (476 nm) and IDIC-R (479 nm) when changing solvent polarity from methanol to DCM and then chloroforms. The natural bond orbital (NBO) analysis showed the (S63)LP → (C61-C62)π* with highest stabilization energy. Their electron injection analysis showed that these dyes can be a good anode material against the aluminum and gold electrodes. The intramolecular charge transfer (ICT) process and stability of the dyes were investigated using frontier molecular orbital (FMO) and natural bond orbital (NBO) analysis. CONCLUSION: Among all dyes, IDIC-R8 has the highest linear polarizability and second-order hyperpolarizability (βtotal). All the dyes demonstrated promising non-linear optical (NLO) properties due to their low charge transfer barriers. Scientists would be able to exploit these properties to identify the best NLO materials for existing applications.
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