Exploring the role of quantum‐mechanical descriptors in the concentration‐dependent adsorption of aromatic organic compounds by multiwalled carbon nanotubes

Abstract

AbstractAn accurate quantitative prediction for concentration‐dependent adsorption of organic compounds by carbon‐nanotubes (CNTs) is increasingly in demand to evaluate not only their applications but also risk associated using CNTs. This is often carried out using poly‐parameter linear‐solvation‐energy‐relationships (pp‐LSERs) based on adsorbate descriptors. This work examines the predictivity of existing pp‐LSERs in the prediction of adsorption of aromatic organic compounds by multi‐walled CNTs (MWCNTs) at five different adsorbate concentrations, and compares that with the predictivity of quantum‐mechanical models while revealing an essential role of electron‐correlation. Notably, the most influencing descriptor for the adsorption was found to be the mean polarizability but that arising from the quantum‐mechanical exchange interactions between electrons of the same spin. This work also proposes reliable predictive models based on a combination of the quantum‐mechanical descriptors and pp‐LSER's descriptors, which were applied to predict the adsorption of nucleobases and steroid hormones, with Progesterone found to be maximally adsorbed.