Fractal-Like Kinetics of Adsorption Applied to the Solid/Solution Interface

Area of Science:

• Environmental Science
• Materials Science
• Chemical Engineering

Background:

• Adsorption is a key process for removing heavy metals from wastewater.
• Treated attapulgite shows potential as an adsorbent material.
• Accurate kinetic and equilibrium modeling is crucial for optimizing adsorption processes.

Purpose of the Study:

• To modify and validate the fractal-like multiexponential (f-mexp) equation for copper adsorption kinetics.
• To assess the predictive capability of artificial neural networks (ANNs) for adsorption efficiency.
• To analyze copper adsorption equilibrium using single-site and multisite occupancy models.

Main Methods:

• Modification of the f-mexp equation by incorporating a fractional fractal exponent.
• Kinetic modeling of copper adsorption onto treated attapulgite using the modified f-mexp equation and other classical models.
• Application of multilayer perceptron (MLP) and single-layer feedforward neural networks for predicting adsorption efficiency.
• Analysis of adsorption equilibrium data using Langmuir-Freundlich and other isotherm models.

Main Results:

• The modified f-mexp equation provided a superior fit to the experimental kinetic data compared to existing models.
• The multilayer perceptron neural network demonstrated higher accuracy in predicting copper removal efficiency under various conditions.
• Adsorption equilibrium data were well-described by the Langmuir-Freundlich isotherm, indicating no significant multisite occupancy effect.

Conclusions:

• The developed modified f-mexp equation is a robust tool for describing copper adsorption kinetics.
• ANNs, particularly MLP, offer a reliable method for predicting adsorption performance.
• Treated attapulgite, following Langmuir-Freundlich adsorption behavior, is effective for copper removal from aqueous solutions.