期刊
INTERNATIONAL JOURNAL OF CHEMICAL REACTOR ENGINEERING
卷 19, 期 9, 页码 901-912出版社
WALTER DE GRUYTER GMBH
DOI: 10.1515/ijcre-2021-0092
关键词
ANN; hybrid nanofluid; MWCNT's; RSM; sonophotocatalytic reactor
资金
- SERB DST [EEQ/2017//000152]
- MHRD GOVT. OF INDIA NEW DELHI
This study investigates the efficiency of a novel 3D artificially illuminated sono-photocatalytic reactor in removing toxic fragments from industrial wastewater, achieving 99% dye degradation within 40 minutes. Response surface methodology and artificial neural network methods were used to optimize the process, revealing significant impact of input parameters on the response variable. With a high R-2 value of 0.999, the engineered multilayer perceptron ANN successfully validated the experimental findings, showing promising potential as a pre-treatment step for producing low toxic intermediates in industrial wastewater treatment.
The present study investigates the efficiency of a novel 3D artificially illuminated sono-photocatalytic reactor filled with the suspension of Ti+4 coated Al(OH)(3)-MWCNT's hybrid nanofluid in removing toxic fragments from the industrial wastewater. Within 40 min of reaction time, the synergistic effect of sonication induced photocatalysis achieved 99 percent dye degradation. Using response surface methodology (RSM-CCD) and artificial neural network (ANN) methods, the behaviour of the process in terms of reactor independent variables on dye removal was investigated and optimised. Both approaches proved to have a very good performance in modelling of the process and from RSM model, the optimum experimental conditions were at 0.5 vol% nanofluid concentration, 60 degrees C nanofluid temperature, and 60 min reaction time. Besides that, a quadratic polynomial equation (R-2 = 0.984) well describes the equilibrium data. Furthermore, the study of variance (ANOVA) approach revealed that the input parameters and their interactions had a substantial impact on the response variable. With an R-2 value of 0.999, the engineered multilayer perceptron ANN successfully validated the experimental findings. Given the significant improvement in photocatalytic degradation of industrial wastewater, the current research can be viewed as a promising pre-treatment step for producing low toxic intermediates.
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