Prediction of soil sorption coefficients with a conductor‐like screening model for real solvents

Using a general theory for partition coefficients based on a quantum chemically derived conductor‐like screening model for real solvents σ‐moment descriptors, the logarithmic soil sorption coefficients log K OC of a database of 440 compounds has been successfully correlated, achieving a standard deviation (root‐means‐squared [RMS]) of 0.62 log‐units on the training set and a predictive RMS of 0.72 log‐units on a more demanding test set. The quality of this generally applicable predictive approach is almost the same as that of a regression of log K OC with experimental log K OW values, which are the best correlations currently available. The error of this new predictive method is only approximately 43% of the error of a recently published model using a different quantum chemically based approach.