Removal of Pharmaceutical Pollutants from Wastewater Using 2D Covalent Organic Frameworks (COFs): An in Silico Engineering Study

The increasing amounts of emerging contaminants (ECs) in aquatic ecosystems are becoming one of the serious environmental issues. Therefore, the efficient removal of ECs is of urgent importance. Herein, a computational technique of molecular dynamics (MD) and the density functional theory (DFT) were employed to assess the adsorption affinity of three regenerable covalent organic frameworks (COFs), namely, DAAQ-TFP, COF-78, and COF-OEt, for the removal of six different ECs from the different pharmaceutical groups, including atenolol, carbamazepine, ciprofloxacin, diclofenac, ibuprofen, and gemfibrozil. Detailed analyses showed that DAAQ-TFP and COF-78 were more efficient in removing atenolol (100%) and carbamazepine (100%) with Gibbs free energy values of -24.48 and -21.15 kJ/mol, respectively. COF-OEt possessed the highest absolute value of the Gibbs free energy, interaction energy, and adsorption affinity in removing ciprofloxacin (88%), diclofenac (63%), ibuprofen (100%), and gemfibrozil (100%). The hydrogen bond formation and van der Waals forces were introduced as the primary adsorption mechanisms. In addition, it was shown that COFs with a pore-based structure have lower capability for the removal of pollutants. The primary aim of this research work is to introduce efficient and regenerable COFs as a promising adsorbent for the removal of pharmaceutical pollutants.