Adsorption of tetracycline by polycationic straw: Density functional theory calculation for mechanism and machine learning prediction for tetracyclines' remediation

Abstract

The abuse of antibiotics causes serious environmental pollution, whose removal has become a hot topic. The adsorption of tetracycline (TC) on a prepared polycationic straw (MMS) was investigated. The kinetic, thermodynamic and adsorption isotherm models showed that adsorption of TC by MMS was a spontaneous, monolayer reaction with coexistence of physical and chemical process. Density functional theory indicated that the adsorption of TC resulted from electrostatic interaction and hydrogen bonds, which proved the mechanism of TC by macromolecular biomass for the first time. The expected and empirical values of TC adsorption showed a high fit degree, through predication of machine learning, indicating the feasibility and avoiding lots of experiments. Further, the adsorption ability of MMS to other TCs was predicted, founding that the highest removal efficiency was doxycycline, which provides a novel strategy for removal of other pollution and reduce of economic and time cost in practical application.

Keywords: Density functional theory; Machine learning; Straw; Tetracycline.