Removal of volatile organic compounds (VOCs) from indoor or outdoor environments is an urgent challenge for the protection of human populations. Inorganic sorbents such as zeolites are a promising solution to tackle this issue. Using dispersion corrected periodic DFT calculations, we have studied the interaction between sodium-exchanged faujasite zeolite and a large set of VOCs including aromatics, oxygenates and chlorinated compounds. The computed interaction energies range from about −25 (methane) to −130 kJ/mol (styrene). Methane is by far the less interacting specie with the NaY zeolite. All other VOCs present interaction energies higher in absolute value than 69 kJ/mol. Most of them show a similar adsorption strength, between −70 and −100 kJ/mol. While the electrostatic interactions are important in the case of oxygenates and acrylonitrile, van der Waals interactions predominate in hydrocarbons and chlorides. By monitoring the variation of molecular bond lengths of the different VOCs before and after adsorption, we have then evaluated the tendency of adsorbate to react and form by-products, since a significant stretching would evidently lead to the activation of the bond. While hydrocarbons, tetrachloroethylene and acrylonitrile seem to be not activated upon adsorption, all oxygenates and 1,1,2-trichloroethane could possibly react once adsorbed.

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By the functional B3LYP and M05-2X of DFT and in two bases set, more and more extended (6-311G and 6-311G (d, p)), theoretical study of antioxidant properties of four hydrazones was carried out. The calculations made concern the geometrical, spectroscopic and electronic parameters of the molecules. Analysis of the results relating to the geometrical parameters was carried out by calculating interatomic distances, relative errors between calculated values and those obtained experimentally by X-ray diffraction found in the literature. The 13 C NMR spectra were calculated by GIAO (Gauge Including Atomic Orbitals) methods, and the results were subjected to statistical analysis by calculating Mean Absolute Deviation (MAD), Root Mean. Square (RMS) and the correlation coefficient (R 2 ), in comparison with experimental spectra. The analysis of the results of calculations of various electronic parameters (hardness (η), softness (S), electronegativity (χ), electrophile index (ω), energy gap (HOMO-LUMO)) reveals that, overall, the methods M05-2X/6-311G (d, p) and B3LYP/6-311G (d, p) found that (R) -(−) -carvone salicylhydrazone (N 2 ) is the most antioxidant molecule of the four molecules and also classify them according to their stability. This confirms the results obtained on the antitrypanosomal activity, the toxicity, the cytotoxicity and the selectivity of the synthesized compounds.

Several methods exist when seeking to experimentally evaluate the antioxidant properties of a natural bioactive substance. In the case of flavonoids, the methods used are mainly based on the experimental determination of the percentage of inhibition (IC50) or the redox potential (E). In the present work, a prediction study of the redox potential E and the inhibitory concentration LogIC50 was carried out, using the AM1 and HF/6-311G(d,p) method. At the end of this study, three (03) QSPR models were validated and retained, one (01) for the prediction of the redox potential and four (02) for the prediction of the inhibitory concentration : The Redox Prediction Model, developed at the AM1 approximation level, for which 96.43 of the experimental variance is explained by the descriptors : E= -0,29 + 0,22EHomo + 0,11ELumo - 0,05 The Inhibitory Concentration Prediction Models, developed at the AM1 level, for which 96.35⁒ of the experimental variance is explained by the descriptors : LogIC50 = -4,92 + 11,37EHomo + 34,36ELumo + 0,67 The Inhibitory Concentration Prediction Model, developed at the HF/6-311G level (d, p), for which 99.96⁒ of the experimental variance is explained by the descriptors. LogIC50 = 62,40 + 80,25 EHomo - 28,44Elumo + 52,01S - 71,26 η - 6,11μ The development of these QSPR models represents a significant advance in predicting the antioxidant properties of bioactive molecules such as flavonoids based on descriptors calculated by quantum chemical methods.