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In this work, quantum chemical analysis was used to predict the degradation potential of a recalcitrant dye, Acid blue 113, by hydrogen peroxide, ozone, hydroxyl radical and sulfate radical. Geometry optimization and frequency calculations were performed at ‘Hartree Fock’, ‘Becke, 3-parameter, Lee–Yang–Parr’ and ‘Modified Perdew-Wang exchange combined with PW91 correlation’ levels of study using 6-31G* and 6-31G** basis sets. The Fourier Transform-Raman spectra of Acid blue 113 were recorded and a complete analysis on vibrational assignment and fundamental modes of model compound was performed. Natural bond orbital analysis revealed that Acid blue 113 has a highly stable structure due to strong intermolecular and intra-molecular interactions. Mulliken charge distribution and molecular electrostatic potential map of the dye also showed a strong influence of functional groups on the neighboring atoms. Subsequently, the reactivity of the dye towards the oxidants was compared based on the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy values. The results showed that Acid blue 113 with a HOMO value -5.227 eV exhibits a nucleophilic characteristic, with a high propensity to be degraded by ozone and hydroxyl radical due to their lower HOMO-LUMO energy gaps of 4.99 and 4.22 eV respectively. On the other hand, sulfate radical and hydrogen peroxide exhibit higher HOMO-LUMO energy gaps of 7.92 eV and 8.10 eV respectively, indicating their lower reactivity towards Acid blue 113. We conclude that oxidation processes based on hydroxyl radical and ozone would offer a more viable option for the degradation of Acid blue 113. This study shows that quantum chemical analysis can assist in selecting appropriate advanced oxidation processes for the treatment of textile effluent.

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A series of 21 compounds isolated from Curcuma zedoaria was subjected to cytotoxicity test against MCF7; Ca Ski; PC3 and HT-29 cancer cell lines; and a normal HUVEC cell line. To rationalize the structure–activity relationships of the isolated compounds; a set of electronic; steric and hydrophobic descriptors were calculated using density functional theory (DFT) method. Statistical analyses were carried out using simple and multiple linear regressions (SLR; MLR); principal component analysis (PCA); and hierarchical cluster analysis (HCA). SLR analyses showed that the cytotoxicity of the isolated compounds against a given cell line depend on certain descriptors; and the corresponding correlation coefficients (R2) vary from 0%–55%. MLR results revealed that the best models can be achieved with a limited number of specific descriptors applicable for compounds having a similar basic skeleton. Based on PCA; HCA and MLR analyses; active compounds were classified into subgroups; which was in agreement with the cell based cytotoxicity assay.

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