Modeling of Adsorption by Artificial Neural Networks

The combination of computational power and theoretical approaches has enabled the solution of complex problems in chemistry. In wastewater treatment, it is challenging to model nonlinear and complex techniques using classical methods, as these models cannot understand the relationships between the different parameters that affect the process. For instance, the adsorption process is a commonly used process for removing contaminants from wastewater. The adsorption technique requires two elements: the adsorbent material and the pollutant; however, the complexity of molecule-surface interactions makes the simulation challenging. The utilization of artificial neural networks in the adsorption process is crucial. Considering that ANN provides close prediction results for adsorption performance and materials efficiency, which helps to design and improve the next generation of adsorbent materials.