Abstract
ABSTRACT Non-linear optical (NLO) parameter of a series of donor–acceptor substituted N-salicylidene-4-benzenesulfonylaniline (SBSA) derivatives with a contrast of first hyperpolarisability has been investigated using density functional-based theory. The derivative of SBSA with both the donor and acceptor substitution (NMe2-SBSA-NO2) exhibits the highest first hyperpolarisability ( ∼ 3 × 103 a.u in gas phase) value. Frequency and solvent polarity responsive behaviours of first hyperpolarisability are utilised to demonstrate the variation of NLO as switchable electrical parameter. Each of the studied compounds displays very high NLO response at frequency corresponding to the absorption maxima of their electronic state. Likewise, the increase of solvent polarity induces a substantial increase of first hyperpolarisability. The computation of NLO responsive first hyperpolarisability by varying the frequency and solvent dielectric constant within a wide domain is very tedious and time-consuming. To overcome the lacuna, we implemented machine learning tools such as artificial neural networks (ANNs), fuzzy logic (FL) and adaptive neuro-fuzzy inference system (ANFIS) to predict the computation data of the NMe2-SBSA-NO2 and moderately good results were obtained using ANFIS as soft computing tool.
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