Dataset Information

Adsorption of tetracycline antibiotic onto modified zeolite: Experimental investigation and modeling.

ABSTRACT: Artificial Neural Networks (ANNs) model and Adaptive Neuro-Fuzzy Inference System (ANFIS) were used to estimate and predict the removal efficiency of tetracycline (TC) using the adsorption process from aqueous solutions. The obtained results demonstrated that the optimum condition for removal efficiency of TC were 1.5 g L-1 modified zeolite (MZ), pH of 8.0, initial TC concentration of 10.0 mg L-1, and reaction time of 60 min. Among the different back-propagation algorithms, the Marquardt-Levenberg learning algorithm was selected for ANN Model. The log sigmoid transfer function (log sig) at the hidden layer with ten neurons in the first layer and a linear transfer function were used for prediction of the removal efficiency. Accordingly, a correlation coefficient, mean square error, and absolute error percentage of 0.9331, 0.0017, and 0.56% were obtained for the total dataset, respectively. The results revealed that the ANN has great performance in predicting the removal efficiency of TC.•ANNs used to estimate and predict tetracycline antibiotic removal using the adsorption process from aqueous solutions.•The model's predictive performance evaluated by MSE, MAPE, and R2.

SUBMITTER: Dolatabadi M

PROVIDER: S-EPMC7184631 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Adsorption of tetracycline antibiotic onto modified zeolite: Experimental investigation and modeling.

Dolatabadi Maryam M Mehrabpour Marjan M Esfandyari Morteza M Ahmadzadeh Saeid S

MethodsX 20200418

Artificial Neural Networks (ANNs) model and Adaptive Neuro-Fuzzy Inference System (ANFIS) were used to estimate and predict the removal efficiency of tetracycline (TC) using the adsorption process from aqueous solutions. The obtained results demonstrated that the optimum condition for removal efficiency of TC were 1.5 g L<sup>-1</sup> modified zeolite (MZ), pH of 8.0, initial TC concentration of 10.0 mg L<sup>-1</sup>, and reaction time of 60 min. Among the different back-propagation algorithms, ...[more]

PMID: 32368508

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Project description:Wettability alterations, permeability reduction of reservoir rocks, and oil production decline may occur as a consequence of asphaltene adsorption and deposition on the surfaces of oil reservoir rocks. Magnetite and other iron minerals are abundant in the rock composition of sandstone reservoirs and cause problems by precipitation and adsorption of polar components of crude oil. The main purpose of this study was to investigate the adsorption of six asphaltene samples of various origins onto the magnetite surface. Characterization of magnetite was performed by Brunauer-Emmett-Teller (BET), Fourier transform infrared spectroscopy (FTIR), and X-ray fluorescence (XRF). Also, FTIR, dynamic light scattering (DLS), and elemental analysis were performed to characterize asphaltenes. Static and dynamic adsorption experiments were carried out to investigate the effects of the water phase, adsorbent size, flow rate, and asphaltene compositions on asphaltene uptake by the magnetite. The results showed that an increase in the nitrogen content and aromatic nature of asphaltenes increased their adsorption on magnetite. The addition of water to the adsorption tests significantly reduced the adsorption amount of asphaltenes on the magnetite. A considerable decrease in asphaltene adsorption was observed with an increase in the flow rate in dynamic tests. This shows that higher flow rates reduce the interaction between adsorbed asphaltenes and asphaltene aggregates in the solution, which reduces the uptake of more asphaltenes. Moreover, adsorbed asphaltene components with a weaker bond are detached from the magnetite surface, which can be attributed to the physisorption of asphaltenes. Eventually, four well-known adsorption isotherm models, namely, Langmuir, Dubinin-Radushkevich, Temkin, and Freundlich were utilized to find the mechanisms of asphaltene adsorption onto the magnetite surface. The Freundlich model seems to provide better estimates for the adsorption of asphaltenes on the magnetite surface. The findings of this study render insights into the better management of oil production in formations with iron-containing rocks.

Dataset Information

Adsorption of tetracycline antibiotic onto modified zeolite: Experimental investigation and modeling.

Publications

Adsorption of tetracycline antibiotic onto modified zeolite: Experimental investigation and modeling.

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