Modeling binding of organic pollutants to a clay–polycation adsorbent using quantitative structural–activity relationships (QSARs)

Abstract The adsorption of organic pollutants to a novel adsorbent–polyvinyl-pyridine- co -styrene–montmorillonite nanocomposite was quantified and modeled. To elucidate the adsorption mechanisms, experimental methods and QSAR analysis were combined, searching for correlations between the pollutant-nanocomposite adsorption coefficient ( k d ) and pollutant chemical–physical properties. The adsorption isotherms at a wide range of concentrations were fitted to the Freundlich equation and the log k d values were extracted at a low, environmentally significant, concentration. A significant regression was achieved with QSAR, predicting adsorption affinity by four meaningful descriptors: adsorption was positively correlated to heat of formation, number of hydrogen acceptor groups and the partitioning coefficient, and was negatively correlated to molecular mass. The resulting model predicted log k d for test pollutants with an average deviation of only 0.77 log units from the experimental values. Consequently, this method could be applied to better understand adsorption mechanisms and to screen for compatibility between pollutants and a variety of novel and commonly used adsorbents.