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

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 ino...

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Bibliographic Details
Main Authors: Francisco A. Santos, Carlos E. R. Cardoso, José J. Rodrigues, Leonardo De Boni, Luis M. G. Abegão
Format: Article
Language:English
Published: MDPI AG 2023-05-01
Series:Photonics
Subjects:
Online Access:https://www.mdpi.com/2304-6732/10/5/545
Description
Summary: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 (β). The microscopic effect of the coherent or incoherent SHG is, in fact, the β. Therefore, estimating β 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 β 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 β 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.
ISSN:2304-6732