Modelling Molecular Partitioning in Complex Media

拟议的研究重点是发展新的理论模型和方法，以估计环境中化学品的性质，这被认为对环境监测和监管政策工作很重要。我们特别关注缺乏坚实理论基础的问题领域，以开发新的，强大的预测技术。示例领域有：(1)在不同环境中形态发生变化的化学物质，其中任何一种形态的性质都不能充分代表分子的整体行为；(2)在其他化学溶剂的复杂混合物中，该分子在任何一种溶剂中的性质都不能充分代表该分子的整体行为的化学品；（三）在土壤、泥浆、生物组织等成分未知的环境中，现有的性质估计方法无法测定的化学品。

The proposed research focusses on the development of new theoretical models and methods for estimating the properties of chemicals in environments that are considered to be of importance in environmental monitoring and regulatory policy work. We are specifically focusing on the problematic areas that lack a solid theoretical foundation, to develop new, robust prediction techniques. Example areas are: (1) chemicals that change their form in different environments, for which the properties of any one of its forms do not adequately represent the molecule’s overall behaviour; (2) chemicals in complex mixtures of other chemical solvents for which the properties of that molecule in any one of the solvents do not adequately represent the molecule’s overall behaviour; (3) chemicals in environments of unknown composition such as soils, muds, or biological tissues, for which existing methods of property estimation are not usable. We use, as the basis for our work, a recently developed theory for the prediction of the properties of chemicals in liquids, the COSMO-RS method. This method uses as its starting point an accurate calculation of the chemical’s structure in a relaxed or fully solvated environment, along with the corresponding way in which the chemical’s electrons distribute themselves over the chemical backbone. Using these starting points, the theory can predict how much of a chemical will be found in water, air, or other liquids to a good level of accuracy. Our own work will address the above problem areas in the following ways: (1) the detailed chemistry of chemicals that change their form will be incorporated into models that explicitly account for the various forms present (2) chemicals present in mixtures of other chemical solvents will be treated by modelling the solvent mixture by one of several methods that either mimic the mixture or blend the properties of the individual solvents and (3) unknown composition environments will be represented by mathematically constructing an artificial solvent model whose properties are matched by mathematically fitting them to the properties of the unknown environment. The results of this work will aid in the development of new environmental monitoring approaches and techniques that will inform government regulatory policy of many chemicals and environments that fall into the categories noted above. They will also be used by environmental scientists in the field and laboratory to accurately measure concentrations and fates of such chemicals. Finally, extensions of these innovations will lead to new ways to theorize biomolecules in human and mammalian blood and tissues as part of whole-body fate models.