4.5 Article

Nonlinear Optical Materials: Predicting the First-Order Molecular Hyperpolarizability of Organic Molecular Structures

Journal

PHOTONICS
Volume 10, Issue 5, Pages -

Publisher

MDPI
DOI: 10.3390/photonics10050545

Keywords

first-order molecular hyperpolarizability; nonlinear optics; incoherent second harmonic generation; optical frequency converters; quantum chemical calculations; post-processing software; organic compounds

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Experimental nonlinear optics is expensive, but exploring the NLO responses of organic and inorganic compounds has opened new possibilities. This study simulated the beta values of 27 organic compounds using density functional theory and compared them with experimental analogs obtained by the Hyper-Rayleigh Scattering technique.
Experimental nonlinear optics (NLO) is usually expensive due to the high-end photonics and electronic devices needed to perform experiments such as incoherent second harmonic generation in liquid phase, multi-photon absorption, and excitation. Nevertheless, exploring NLO responses of organic and inorganic compounds has already opened a world of new possibilities. For example, NLO switches, NLO frequency converters, and a new way to obtain biological images through the incoherent second harmonic generation (SHG) originate from first-order molecular hyperpolarizability (beta). The microscopic effect of the coherent or incoherent SHG is, in fact, the beta. Therefore, estimating beta without using expensive photonic facilities will optimize time- and cost-efficiency to predict if a specific molecular structure can generate light with double its incident frequency. In this work, we have simulated the beta values of 27 organic compounds applying density functional theory (PBE0, TPSSh, wB97XD, B3LYP, CAM-B3LYP, and M06-2X) and Hartree-Fock methods using the Gaussian software package. The predicted beta was compared with the experimental analogs obtained by the well-known Hyper-Rayleigh Scattering (HRS) technique. The most reliable functionals were CAM-B3LYP and M06-2X, with an unsigned average error of around 25%. Moreover, we have developed post-processing software-Hyper-QCC, providing an effortless, fast, and reliable way to analyze the Gaussian output files.

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