Unveiling Adsorption Mechanisms of Organic Pollutants onto Carbon Nanomaterials by Density Functional Theory Computations and Linear Free Energy Relationship Modeling

Predicting adsorption of organic pollutants onto carbon nanomaterials (CNMs) and understanding the adsorption mechanisms are of great importance to assess the environmental behavior and ecological risks of organic pollutants and CNMs. By means of density functional theory (DFT) computations, we investigated the adsorption of 38 organic molecules (aliphatic hydrocarbons, benzene and its derivatives, and polycyclic aromatic hydrocarbons) onto pristine graphene in both gaseous and aqueous phases. Polyparameter linear free energy relationships (pp-LFERs) were developed, which can be employed to predict adsorption energies of aliphatic and aromatic hydrocarbons on graphene. Based on the pp-LFERs, contributions of different interactions to the overall adsorption were estimated. As suggested by the pp-LFERs, the gaseous adsorption energies are mainly governed by dispersion and electrostatic interactions, while the aqueous adsorption energies are mainly determined by dispersion and hydrophobic interactions. It was also revealed that curvature of single-walled carbon nanotubes (SWNTs) exhibits more significant effects than the electronic properties (metallic or semiconducting) on gaseous adsorption energies, and graphene has stronger adsorption abilities than SWNTs. The developed models may pave a promising way for predicting adsorption of environmental chemicals onto CNMs with in silico techniques.