An Approach to Determining the Partition Coefficients between Solid and Air Phases for Organic Compounds Using the QSPR

An important metric for evaluating the emission of chemicals from solid materials and the subsequent human exposure is the partition coefficient between the material and air (Kma). Current correlations for calculating Kma are typically limited to a narrow range of chemical-material combinations and do not account for temperature variations. This study aims to expand the prediction of Kma to a broader range of chemical-material pairings using a quantitative structure property relationship (QSPR) approach. A dataset comprising 991 measured Kma values for I179 chemical compounds across 22 distinct material categories was compiled. The prediction of Kma was achieved through a multiple linear regression model that incorporates several key variables, including temperature, material type, enthalpy of vaporization (∆Hv), and the chemical partition coefficient between octanol and air (Koa). Internal and external validation confirmed that the model is robust, reliable, and exhibits strong predictive performance (R²ext > 0.78). Additionally, the model demonstrates a high degree of fit to the experimental data, along with a modified R² of 0.93. Moreover, a generalized QSPR model has been created to forecast Kma based solely on temperature and chemical properties, with an adjusted R² = 0.84, thus eliminating the need to specify a particular material type. These QSPR-based correlations will enable Rapid analysis predictions of human exposure to chemicals in materials, with particular applicability to furniture and building materials.