Department of Chemistry, Wayne State University, Detroit, MI 48202, USA.
J Chromatogr A. 2023 Nov 8;1710:464430. doi: 10.1016/j.chroma.2023.464430. Epub 2023 Oct 5.
Revised descriptors for twenty-five polycyclic aromatic and related hydrocarbons (PAHs) forming a component of the Wayne State University (WSU) descriptor database are provided for use with the solvation parameter model. The descriptors are determined by the Solver method using experimental data for calibrated gas-liquid and reversed-phase liquid chromatographic retention factors and liquid-liquid partition constants in totally organic biphasic systems. The characteristic solvation properties of the PAHs are accounted for mainly by the additional dispersion interactions (E descriptor) and dipole-type interactions (S descriptor) resulting from the availability of easily polarizable electrons that complement typical dispersion interactions for saturated hydrocarbons. The descriptors afford acceptable prediction of the water-air partition constant (average absolute deviation AAD = 0.17, n = 22), octanol-air partition constant (AAD = 0.12, n = 20), and water-octanol partition constant (AAD = 0.10, n = 23). A two-parameter model containing only the V and B descriptors provides an unbiased prediction of aqueous solubility for the PAHs with an AAD = 0.26 (n = 22). The descriptors estimated by convenient chromatographic and partition constant measurements are demonstrated to be a viable alternative to the experimental determination of environmental properties otherwise only available by tedious, expensive, and low data throughput experimental techniques.
为了与溶剂参数模型一起使用,提供了 25 种多环芳烃和相关烃(PAHs)的修订描述符,这些描述符是 Wayne State 大学(WSU)描述符数据库的一部分。这些描述符是通过 Solver 方法根据实验数据确定的,用于校准气液和反相液相色谱保留因子以及完全有机双相系统中的液液分配常数。PAHs 的特征溶剂化性质主要由额外的色散相互作用(E 描述符)和偶极型相互作用(S 描述符)决定,这是由于容易极化的电子的可用性,这些电子补充了饱和烃的典型色散相互作用。这些描述符可以接受地预测水-空气分配常数(平均绝对偏差 AAD=0.17,n=22)、辛醇-空气分配常数(AAD=0.12,n=20)和水-辛醇分配常数(AAD=0.10,n=23)。仅包含 V 和 B 描述符的双参数模型为 PAHs 的水溶解度提供了无偏预测,平均绝对偏差 AAD=0.26(n=22)。通过方便的色谱和分配常数测量估计的描述符被证明是替代其他仅通过繁琐、昂贵和低数据吞吐量实验技术获得的环境特性的可行方法。