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

• Adsorption affinity of 30 pollutant to a clay polymer nanocomposite (CPN) was measured.
• Adsorption affinity was correlated to the pollutant properties by QSAR.
• A proposed model identified the adsorption mechanisms and gave a prediction of log kd.
• This method can screen for pollutants that will be effectively removed by sorbents.

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 (kd) and pollutant chemical–physical properties. The adsorption isotherms at a wide range of concentrations were fitted to the Freundlich equation and the logkd 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 logkd 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.

Figure optionsDownload as PowerPoint slide