Evaluate the Performance of Fenton Process for the Removal of Methylene Blue from Aqueous Solution: Experimental, Neural Network Modeling and Optimization

In this study, the high silica ZSM‐5 carrier was modified with the iron species and applied as a heterogeneous electro‐Fenton (EF) catalyst for pharmaceutical pollutant degradation. The carrier was prepared by the hydrothermal method and followed by impregnation. The physicochemical properties were evaluated by field emission scanning electron microscopes (FE‐SEM), FT‐IR, X‐Ray diffraction (XRD), and N2 adsorption–desorption techniques. The impregnated carrier had high crystallinity, high specific surface area, and uniform dispersion of iron species. The effect of different operating conditions was studied on the phenazopyridine (PHP) degradation efficiency. The optimal efficiency of PHP degradation (ca. 92.5%) was obtained at pH of 3.0, the current density of 100 mA, catalyst loading of 0.2 g L−1, and T = 25°C. The data of kinetic showed that the degradation of PHP followed Pseudo‐First‐Order kinetic, including the high accuracy (R2 > 0.95). The developed catalyst had the high stability and reusability for the PHP degradation in the EF process, while the degradation efficiency dropped only 0.5% for the regenerated catalyst.

“…The residual concentration of PHP was determined using Jenway 6705 UV-vis spectrophotometer (England). The degradation efficiency was calculated by Equation (1).…”

Section: Ef Experimentsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Iron modified zeolite carrier for efficiently pharmaceutical pollutant degradation in heterogeneous electro‐Fenton: Influence factors and kinetic

Niaei

Rostamizadeh

2020

“…Nonetheless, ANNs have attracted considerable attention because of their ability to solve complex problems in various fields of engineering, including agriculture mechanical, environmental, civil, petroleum, and aerospace, among others 12‐22 . Furthermore, ANNs are commonly being used in many energy engineering problems and recently, numerous studies have been performed in ANNs modeling of various energy systems, such as solar energy, 23 building thermal load, 24 power generation systems, 25 etc.…”

Section: Introductionmentioning

confidence: 99%

The use of artificial neural networks to estimate optimum insulation thickness, energy savings, and carbon dioxide emissions

Küçüktopcu

Cemek

2020

This study examined artificial neural networks' (ANNs) applicability in modeling optimum insulation thickness (OIT), annual total net savings (ATS), and reduction of carbon dioxide emissions (RCO2) that result from insulating buildings. Data from insulation markets, economic parameters, fuel prices, and heating degree days (HDDs) were introduced into the model as input variables. To complete the most thorough analysis, three learning algorithms, Levenberg Marquardt (LM), Bayesian Regularization (BR), and Scaled Conjugate Gradient (SCG) were employed. Five statistical indexes were utilized to evaluate models' performances: determination coefficient (R2), root mean square error (RMSE), standard error of prediction (SEP), RMSE observations' standard deviation ratio (RSR), and average absolute percent relative error (AAPRE). Moreover, visualization techniques were used to assess the similarity between the OIT, ATS, and RCO2 values calculated and predicted. The results obtained clearly show that the LM model outperformed the BR and SCG models in all estimations. Thereafter, the developed ANNs model was validated for different cities. Overall, this model will provide an effective and straightforward guide for people working in the field to improve thermal insulation design, analysis, and implementation worldwide.

“…Textile industries are responsible for releasing massive amounts of effluents containing dyes. These are synthetic organic compounds 1 that can be used to color product substrates 2,3 . The most important class of color‐enhancing substances are azo dyes containing an azo group (–N=N–) in their structure, which color fibers 1,4 .…”

Section: Introductionmentioning

confidence: 99%

Fe₂O₃/MCM‐41 as catalysts for methyl orange degradation by Fenton‐like reactions

Santana

Bonfim

Cruz

et al. 2020

A large amount of contaminated industrial wastewater has aroused mounting concern by researchers and environmentalists. Dyes contained in industrial effluents are often quite persistent to biodegradation, which must be treated before being disposed of. In this context, the use of Fenton processes is a potential alternative to treat a wide range of dyes and other organic pollutants found in wastewater. Thus, several Fe2O3/MCM‐41 catalysts have been synthesized in the following molar ratio of SiO2/Fe2O3: 10, 20, 40, 100, and 200. They were characterized by N2 adsorption–desorption isotherm, X‐ray fluorescence (XRF), X‐ray diffraction (XRD), UV–vis spectroscopy and H2 temperature‐programmed reduction (H2‐TPR), and applied to degrade methyl orange dye (MO) via a heterogeneous Fenton reaction. Catalytic tests revealed that SiO2/Fe2O3 = 10 reached the highest activity due to greater availability of active sites which generated a larger quantity of hydroxyl (•OH) and perhydroxyl (•OOH) radicals. Furthermore, 70% of color removal has been achieved after 120 min at room temperature. Moreover, the systems moderately enhanced organic matter mineralization according to chemical oxygen demand (COD) testing. There was also catalytic activity loss in consecutive reaction cycles, which is probably due to dye molecules adsorption on active sites.