Quantitative structure activity relationship (QSAR) modeling for adsorption of organic compounds by activated carbon based on Freundlich adsorption isotherm - Siyi Ding; Yefan Yang; Ting Tan; Qunshan Wei; Zhemin Shen; Qiong Liu; Xinshan Song; Yuhui Wang; Charles Nzila; Christopher W.K. Chow (PLoS ONE, 2025)
The Freundlich isotherm parameters K and 1/n are typically regarded as empirical constants. However, the underlying theoretical basis for the widespread applicability of the Freundlich isotherm in describing adsorption processes for diverse organic compounds remains unclear. In this study, we successfully elucidated the reason by developing two optimal quantitative structure-activity relationship (QSAR) models: one correlating K with quantum chemical parameters and another linking 1/n to these parameters. The modeling results demonstrated that both K and 1/n exhibit strong correlations with specific quantum chemical descriptors, indicating that the empirical Freundlich isotherm’s applicability is fundamentally linked to the molecular structural characteristics of organic compounds. Key quantum parameters influencing K were identified as ∑q(O + N), q(CH+) max , ELUMO, Fukui(-) max , and Wiberg(C-C) min , suggesting that charge distribution, carbon bond energy, and active site energy are the primary factors governing adsorption efficiency on activated carbon. The QSAR model for 1/n yielded similarly novel and consistent insights, showing that the value of 1/n also correlated with molecular structural characteristics. Both models were rigorously validated and confirmed to be stable, robust, and accurate through standard statistical evaluations. These QSAR models can now be employed to identify whether an organic compound would conform to the Freundlich Isotherm and predict the adsorption efficiency of this compound by activated carbon based on their quantum chemical parameters. As to the practical implications, this study provides a convenient reference method for assessing the applicability of activated carbon adsorption in treating emerging organic pollutants in drinking water plants and a theoretical foundation for developing intelligent management systems in water treatment facilities.