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• W2888453012 endingPage "836" @default.
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• W2888453012 abstract "Synergistic oxidation of ozone (O3) and hydrogen peroxide (H2O2) is an effective water treatment for the elimination of organic pollutants. In this study, 23 organic compounds were conducted to study the reaction rate constants during O3-H2O2 oxidation. Then, two- and three-dimensional quantitative structure-activity relationship (QSAR) models were established to investigate the factors influencing the reaction rate constants by using multiple linear regression method and comparative molecular similarity index analysis (CoMSIA) method, respectively. Both of the two models showed good performance on predicting the reaction rate constants, the associated statistical indices of 2D-QSAR and 3D-QSAR models were R2 = 0.898 and 0.952, q2 = 0.841 and 0.951, Qext2 = 0.968 and 0.970, respectively. But varied in the influence factors, as for the 2D-QSAR model, three quantum chemical parameters, included dipole moment, the largest change of charge in each atom during the nucleophilic attack, the maximum positive partial charge on a hydrogen atom linked with a carbon atom affected the reaction rate. While in the 3D-QSAR model, the electrostatic field played the most important role in evaluating the reaction rate with the contribution of 35.8%, followed by hydrogen bond acceptor and hydrophobic fields with the contribution of 24.9% and 23.2%, respectively. These two models provided predictive tools to study the influencing factors for the degradation of organics and might potentially be applied for estimating the removal properties of unknown organics in O3-H2O2 oxidation process." @default.
• W2888453012 created "2018-08-31" @default.
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• W2888453012 date "2018-12-01" @default.
• W2888453012 modified "2023-10-18" @default.
• W2888453012 title "2D-QSAR and 3D-QSAR simulations for the reaction rate constants of organic compounds in ozone-hydrogen peroxide oxidation" @default.
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• W2888453012 doi "https://doi.org/10.1016/j.chemosphere.2018.08.097" @default.
• W2888453012 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30193231" @default.
• W2888453012 hasPublicationYear "2018" @default.
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