Temperature Dependent Predictive Models for Vapor Pressures of Oxygen-Containing Polycyclic Aromatic Hydrocarbons

Guanghui Ding, Mihua Shao, Jing Zhang
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Abstract

Based on quantum chemical descriptors and topological descriptors, temperature-dependent predictive models for vapor pressures (P) of oxygen-containing polycyclic aromatic hydrocarbons (OPAHs) were developed following a variable selecetion procedure. The cross-validated Q 2 cum of the final model, 0.930, shows that the model has good predictive ability and robustness. In view of difficulties to measurements of P of OPAHs, the model could be used to estimate P values at different temperatures. The main factors influencing logP values of OPAHs, from important to less important, are hydrogen bond force, intermolecular dispersive interactions, electrostatic interactions, temperature and entropic factor.
含氧多环芳烃蒸气压的温度依赖预测模型
基于量子化学描述符和拓扑描述符,建立了含氧多环芳烃(OPAHs)蒸汽压(P)的温度依赖预测模型。经交叉验证,最终模型的Q值为0.930,表明模型具有较好的预测能力和鲁棒性。考虑到OPAHs的P值难以测量,该模型可用于估算不同温度下的P值。影响OPAHs logP值的主要因素由重要到次要依次为氢键力、分子间色散相互作用、静电相互作用、温度和熵因子。
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