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Enhanced photo-degradation of N-methyl-2-pyrrolidone (NMP): Influence of matrix components, kinetic study and artificial neural network modelling (CROSBI ID 311146)

Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija

Kumar, Praveen ; Verma, Shilpi ; Kaur, Ramanpreet ; Papac, Josipa ; Kušić, Hrvoje ; Lavrenčič Štangar, Urška Enhanced photo-degradation of N-methyl-2-pyrrolidone (NMP): Influence of matrix components, kinetic study and artificial neural network modelling // Journal of hazardous materials, 434 (2022), 128807, 12. doi: 10.1016/j.jhazmat.2022.128807

Podaci o odgovornosti

Kumar, Praveen ; Verma, Shilpi ; Kaur, Ramanpreet ; Papac, Josipa ; Kušić, Hrvoje ; Lavrenčič Štangar, Urška

engleski

Enhanced photo-degradation of N-methyl-2-pyrrolidone (NMP): Influence of matrix components, kinetic study and artificial neural network modelling

This study investigates the degradation of N-methyl-2-pyrrolidone (NMP) by UV-C and UV-C/PMS-treatment processes. The degradation of NMP was less than 2% by UV-C photolysis. To enhance the degradation, PMS was used as a source of sulphate (SO4• −) and hydroxyl (HO•) radicals in the UV-C photolysis treatment system. The operational parameters such as initial pH and concentration of NMP and PMS and water matrix elements were studied to understand their effects on degradation. At pH = 6.3, λ = 260 nm, initial concentration of NMP = 10 mg/L, PMS = 300 mg/L and carbonate ion = 150 mg/L, the degradation of NMP was found to be 97.5%, along with 26.86% of TOC removal. The bicarbonate ions, nitrate ions, and chloride ions showed the inhibitory effect on the degradation of NMP. The NMP degradation was governed by pseudo first order kinetics. SO4• − was found to be the dominating degradation species through the radical quenching studies. The intermediates formed during the degradation were identified through LC-MS analysis, and a degradation pathway was proposed. The experimental data was successfully validated through the application of the developed ANN model. The R2 between expected and experimental outcomes was 0.97. The developed ANN model was successful in predicting the degradation of NMP in the given reaction conditions with the prediction accuracy of 90.91% and RMSE of 3.54.

N-methyl-2-pyrrolidone ; PMS ; UV ; kinetics ; radical quenching ; artificial neural network

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Podaci o izdanju

434

2022.

128807

12

objavljeno

0304-3894

1873-3336

10.1016/j.jhazmat.2022.128807

Povezanost rada

Interdisciplinarne tehničke znanosti, Kemijsko inženjerstvo

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