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Enhanced photo-degradation of N-methyl-2-pyrrolidone (NMP) : influence of matrix components, kinetic study and artificial neural network modelling
ID
Kumar, Praveen
(
Avtor
),
ID
Verma, Shilpi
(
Avtor
),
ID
Kaur, Ramanpreet
(
Avtor
),
ID
Papac, Josipa
(
Avtor
),
ID
Kušić, Hrvoje
(
Avtor
),
ID
Lavrenčič Štangar, Urška
(
Avtor
)
PDF - Predstavitvena datoteka,
prenos
(2,66 MB)
MD5: 04365083B950E75708A17A7275151F8C
URL - Izvorni URL, za dostop obiščite
https://www.sciencedirect.com/science/article/pii/S0304389422005969
Galerija slik
Izvleček
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 (SO$_4$$^•$$^−$) and hydroxyl (HO$^•$) radicals in the UV-C photolysis treatment system. The operational parameters such as initial pH and concentration of NMP and PMS and water matrix elements were studied to understand their effects on degradation. At pH = 6.3, λ = 260 nm, initial concentration of NMP = 10 mg/L, PMS = 300 mg/L and carbonate ion = 150 mg/L, the degradation of NMP was found to be 97.5%, along with 26.86% of TOC removal. The bicarbonate ions, nitrate ions, and chloride ions showed the inhibitory effect on the degradation of NMP. The NMP degradation was governed by pseudo first order kinetics. SO$_4$$^•$$^−$ 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 R$^2$ 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.
Jezik:
Angleški jezik
Ključne besede:
N-methyl-2-pyrrolidone
,
kinetics
,
artificial neural network modelling
,
radical quenching
,
artificial neural network
,
UV
,
PMS
Vrsta gradiva:
Članek v reviji
Tipologija:
1.01 - Izvirni znanstveni članek
Organizacija:
FKKT - Fakulteta za kemijo in kemijsko tehnologijo
Status publikacije:
Objavljeno
Različica publikacije:
Objavljena publikacija
Leto izida:
2022
Št. strani:
12 str.
Številčenje:
Vol. 434, art. 128807
PID:
20.500.12556/RUL-137653
UDK:
544.526.2
ISSN pri članku:
0304-3894
DOI:
10.1016/j.jhazmat.2022.128807
COBISS.SI-ID:
103104515
Datum objave v RUL:
24.06.2022
Število ogledov:
653
Število prenosov:
144
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Objavi na:
Gradivo je del revije
Naslov:
Journal of hazardous materials
Skrajšan naslov:
J. hazard. mater.
Založnik:
Elsevier
ISSN:
0304-3894
COBISS.SI-ID:
25748224
Licence
Licenca:
CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:
http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:
To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.
Sekundarni jezik
Jezik:
Slovenski jezik
Ključne besede:
N-metil-2-pirolidon
,
PMS
,
UV
,
kinetika
,
umetno modeliranje nevralnih omrežij
Projekti
Financer:
ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
Številka projekta:
P1-0134
Naslov:
Kemija za trajnostni razvoj
Financer:
Drugi - Drug financer ali več financerjev
Program financ.:
Slovenia, Ministry of Education, Science and Sport
Številka projekta:
C3330–19-952015
Financer:
EC - European Commission
Program financ.:
European Regional Development Fund
Financer:
ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
Številka projekta:
N2-0188
Naslov:
Katalitsko in fotokatalitsko aktivni materiali za pretvorbo CO2 v koristne produkte
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