Regression model, artificial intelligence, and cost estimation for phosphate adsorption using encapsulated nanoscale zero-valent iron

Mahmoud, Ahmed S.; Mostafa, Mohamed K.; Nasr, Mahmoud

doi:10.1080/01496395.2018.1504799

Cited by 49 publications

(25 citation statements)

References 35 publications

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“…On the other side, as the solution pH increased over pH PZC , the number of negatively charged sites increased; hence, the negative charges tended to cover the biochar surface. These patterns would increase the repulsive forces among active sites (either positive sites at pH < pH PZC or negative sites at pH > pH PZC ), reducing the migration of MEG from the bulk solution to the surface of the adsorbent [30]. Overall, results indicated that the neutral condition favored the adsorption of MEG onto biochars; hence, pH = 7 was selected throughout this study.…”

Section: Biochar Characterizationmentioning

confidence: 99%

“…This section represents the economic aspects associated with the adsorption of MEG onto biochar-based material, following the procedures reported by Mahmoud et al [30] and Hamdy et al [42]. The optimal experimental conditions (pH = 7, adsorbent dosage = 2 g/L, and adsorption time = 60 min at 25 °C), equivalent to the highest adsorption capacities, were used for the economic evaluation.…”

Section: Environmental Prospects and Cost Estimationmentioning

confidence: 99%

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Synthesis of sludge-derived biochar modified with eggshell waste for monoethylene glycol removal from aqueous solutions

et al. 2020

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In this study, the pyrolysis of sewage sludge was employed to prepare a biochar (BC) adsorbent that was modified using eggshell wastes, obtaining eggshell-modified biochar (EMBC). The adsorbent material was used for the removal of monoethylene glycol (MEG) from aqueous solutions under various adsorption conditions. Results showed that the specific surface area of EMBC (i.e., 3.95 m 2 /g) was approximately twofold higher than that of BC, implying that the application of eggshell waste would improve the surface adsorption performance. The optimum adsorption pH value was 7, achieving MEG removal efficiencies of 29.9% for BC and 89.9% for EMBC using adsorbent dosage = 2 g/L, initial MEG concentration = 100 mg/L, and 25 °C within 60 min. The adsorption mechanisms were illustrated regarding XRD, FTIR, and SEM, demonstrating that surface adsorption, pore-filling, precipitation, and complexation contributed to the adsorption process. The adsorption data fitted well to the Langmuir isotherm model with the maximum monolayer adsorption capacity of 12.20 mg/g, implying a reversible physisorption mechanism. Based on a techno-economic feasibility assessment, the preparation of BC and EMBC adsorbents for the treatment of 1 m 3 of wastewater-containing ethylene glycol would require capital costs of 4.80 and 6.50 US$, respectively. The selling of adsorbents and the economic benefit of tertiary treated water showed adequate annual profitability with payback periods of 12.97 and 6.79 years for the BC and EMBC scenarios, respectively. Hence, the study succeeded in preparing efficient and low-cost adsorbents that could be used for the tertiary treatment of petrochemical industrial wastewater containing toxic environmental pollutants.

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Section: Biochar Characterizationmentioning

confidence: 99%

Section: Environmental Prospects and Cost Estimationmentioning

confidence: 99%

Synthesis of sludge-derived biochar modified with eggshell waste for monoethylene glycol removal from aqueous solutions

et al. 2020

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“…The network type is multilayer perceptron backpropagation and it is one of the best commonly used neural network architectures. 44,57 Results and Discussions Characterization of nZVI and GT-nZVI Figure 2A displays the SEM characterization image of the prepared powder nZVI before treatment. The nZVI formed regular as well as irregular surface structure with an average size of 40 nm.…”

Section: Discussionmentioning

confidence: 99%

“…The neural network model adapted operating coverable (pH, dose, time, stirring rate, and concentration) by connecting weight and bias through a continuous progression to build the artificial neural network architectures for color removal (target) as shown in Figure 7. 44,74 Each color contaminant removal was calculated using training and testing techniques without any excluded as explained in Table 8.…”

Section: Discussionmentioning

confidence: 99%

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Comparative Studies of Using Nano Zerovalent Iron, Activated Carbon, and Green Synthesized Nano Zerovalent Iron for Textile Wastewater Color Removal Using Artificial Intelligence, Regression Analysis, Adsorption Isotherm, and Kinetic Studies

Karam

Zaher

Mahmoud

2020

Air, Soil and Water Research

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Daily, a big extent of colored, partially treated textile effluents drained into the sanitation systems causing serious environmental concerns. Therefore, the decolorization treatment process of wastewater is crucial to improve effluent quality. In the present study, 3 different sorbent materials, nano zerovalent iron (nZVI), activated carbon (AC), and green-synthesized nano zerovalent iron (GT-nZVI), have been prepared for raw textile wastewater decolourization. The prepared nanomaterials were characterized via X-ray diffraction (XRD) spectroscopy, scanning electron microscopy (SEM), energy dispersive X-ray (EDX) analysis, and UV-Vis absorption spectroscopy. In addition, the effect of different operating parameters such as pH, contact time, and stirring rate on the color removal efficiency was extensively studied to identify the optimum removal conditions. The reaction temperature, adsorbent dose, and initial color concentration were fixed during the experiments at room temperature, 0.7 g/L, and 350 and 50 mg/L Pt/Co color unit, respectively. Moreover, adsorption and reaction kinetics were analyzed using different isotherms and models. For simulating the adsorption process, artificial neural network (ANN) data were compatible with the result of regression analysis derived from response surface methodology (RSM) optimization. Our results showed the higher ability of nZVI, AC, and GT-nZVI in textile wastewater color removal. At pH 5, contact time 50 minutes, and stirring rate 150 rpm, nZVI showed good color removal efficiency of about 71% and 99% for initial color concentrations of 350 and 50 mg/L Pt/Co color unit, respectively. While slightly higher color removal ability of about 72% and 100% was achieved by using AC at pH 8, contact time 70 minutes, and stirring rate 250 rpm. Finally, the largest ability of color removal about 85% and 100% was recorded for GT-nZVI at pH 7, contact time 40 minutes, and stirring rate 150 rpm. This work shows the enhanced color removal ability of GT-nZVI as a potential textile wastewater decolourization material, opening the way for many industrial and environmental applications.

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Enhanced Phosphate Sequestration by Alginate-based Aerogel Granules Functionalized with Nanoscale Zerovalent Iron

Bhattacharjee,

Shanableh,

Sadik

2024

J Polym Environ

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Regression model, artificial intelligence, and cost estimation for phosphate adsorption using encapsulated nanoscale zero-valent iron

Cited by 49 publications

References 35 publications

Synthesis of sludge-derived biochar modified with eggshell waste for monoethylene glycol removal from aqueous solutions

Synthesis of sludge-derived biochar modified with eggshell waste for monoethylene glycol removal from aqueous solutions

Comparative Studies of Using Nano Zerovalent Iron, Activated Carbon, and Green Synthesized Nano Zerovalent Iron for Textile Wastewater Color Removal Using Artificial Intelligence, Regression Analysis, Adsorption Isotherm, and Kinetic Studies

Enhanced Phosphate Sequestration by Alginate-based Aerogel Granules Functionalized with Nanoscale Zerovalent Iron

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