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Application of artificial neural network for comparison and modeling of the ultrasonic and stirrer assisted removal of anionic dye using activated carbon supported with nanostructure material
Author(s) -
Ghaedi Abdol Mohammad,
Karami Parisa,
Ghaedi Mehrorang,
Vafaei Azam,
Alipanahpour Dil Ebrahim,
Mehrabi Fatemeh
Publication year - 2018
Publication title -
applied organometallic chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.53
H-Index - 71
eISSN - 1099-0739
pISSN - 0268-2605
DOI - 10.1002/aoc.4050
Subject(s) - freundlich equation , langmuir , chemistry , activated carbon , adsorption , langmuir adsorption model , scanning electron microscope , ultrasonic sensor , analytical chemistry (journal) , coefficient of determination , sonication , nuclear chemistry , chromatography , materials science , composite material , organic chemistry , machine learning , computer science , physics , acoustics
In this study, a green approach has been described for the synthesis of copper sulfide nanoparticles loaded on activated carbon (CuS‐NP‐AC) and usability of it for the removal of sunset yellow (SY) dye by ultrasound‐assisted and stirrer has been compared. In addition, the artificial neural network (ANN) model has been employed for a forecasting removal percentage of SY dye using the results obtained. This material was characterized using scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The impact of variables, including initial dye concentration (mg/L), pH, adsorbent dosage (g), sonication time (min) and temperature (°C) on SY removal was studied. Fitting the experimental equilibrium data of different isotherm models such as Langmuir, Freundlich, Temkin and Dubinin–Radushkevich models display the suitability and applicability of the Langmuir model. Analysis of experimental adsorption data of different kinetic models including pseudo‐first and second order, Elovich and intraparticle diffusion models indicate the applicability of the second‐order equation model. The adsorbent (0.005 g) is applicable for successful removal of SY dye (> 98%) in short time (9 min) under ultrasound condition. A three layer ANN models with 8 and 6 neurons at hidden layer was selected as optimal models using stirrer and ultrasonic, respectively. These models displayed a good agreement between forecasted data and experimental data with the determination coefficient (R 2 ) of 0.9948 and 0.9907 and mean squared error (MSE) of 0.0001 and 0.0002 for training set using stirrer and ultrasonic, respectively.