Computational methods for adsorption study in wastewater treatment

Computation methods or molecular simulations can be used to identify materials with high adsorption capacity for wastewater treatment rapidly. They can also provide complementary insights into the dynamics of adsorption processes. In addition, molecular simulations can be used to understand the adsorption mechanism and the interaction between contaminants and adsorbents. Considering their applicability in wastewater treatment, computational methods have been widely used for adsorption studies. Due to affordability, most of these methods are based on density functional theory (DFT) calculations. However, molecular dynamics and Monte Carlo simulations have also been used to get insights into the adsorption of pollutants. With the growth of artificial intelligence, machine learning-based approaches have also been used to predict the adsorption capacity of materials. Despite the importance of computational methods in wastewater treatment, no review article summarizes the methods used in the literature. Therefore, we undertake to summarize, classify, and provide a detailed description of computational methods used in the adsorption studies for wastewater treatment. For each method, we review some outstanding works using the method and provide the advantages and limits of the method. Finally, future directions and possible improvements of the computational methods are suggested as perspectives.