The Modelling of Thermodynamically Difficult Systems

热力学困难系统的建模

• 批准号: 9521406
• 负责人: Stanley Sandler
• 金额: $ 34.5万
• 依托单位: University of Delaware
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1996
• 资助国家: 美国
• 起止时间: 1996-06-15 至 2000-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9521406&HistoricalAwards=false
• 关键词: Modelling; Thermodynamically; Difficult; Systems

9521406 Sandler Experimental measurements are very time consuming, and it is not practical to measure the thermodynamic properties and phase behavior of all substances and mixtures, that are of importance for chemical and pharmaceutical processing, for environmental and safety engineering, and for other aspects of chemical processing. Therefore, it is important to have accurate prediction or at least correlation methods. This proposal deals with research on the development of predictive models the thermodynamical properties and phase equilibria of industrially important, but complex mixtures. Three different types of mixtures will be considered: hydrogen-bonding fluids, protein solutions and colloidal systems. Hydrogen-bonding fluids are poorly described by current group contribution methods as documented in this proposal. The reason is that the extent and strength of hydrogen bonding is strongly influenced by functional groups on a molecule adjacent to the hydrogen-bonding groups. We have shown this both experimentally and from ab initio quantum mechanics calculations. We are now proposing to develop a new generation of prediction methods based on a combination of group contribution methods for the generalizable dispersive forces, and molecule-specific quantum chemistry calculations for hydrogen bonding. Protein solutions and their purification are important in many bio-processing applications. The research being proposed here involves the use of molecular thermodynamic and statistical mechanical modeling and computer simulation to develop predictive models for the partitioning of proteins in aqueous two-phase systems and for protein precipitation. Colloids lie between the macroscopic and microscopic regimes of matter, and are of interest because their behavior influences many emerging technologies in chemical, biochemical, and pharmaceutical processing. There are two scales of phase behavior in liquid-in-liquid colloidal systems. At the macroscale is liquid-liquid phase separation, or macroscopic phase equilibrium. The microscale behavior is the formation of microstructures in some (or all) of the separated phases. Many important characteristics of liquid colloids are dictated by the microstructures that form. However, to investigate the microstructure, one first needs to have an understanding of the macroscopic phase behavior as this identifies the phase boundaries within which microstructures are formed. Thermodynamic modeling of such systems has been rather simple, and has not captured the temperature and pressure dependence of the macroscopic phase boundaries of liquid colloidal systems. Here we are proposing research on the modeling of macroscopic phase behavior of liquid-in-liquid colloids using modern thermodynamic methods to provide a more accurate description of the changes in the macroscopic phase boundaries of colloidal systems with variations in temperature, pressure and composition. ***

9521406桑德勒实验测量非常耗时，而且测量所有物质和混合物的热力学性质和相行为是不现实的，这些物质和混合物对化学和药物加工、环境和安全工程以及化学加工的其他方面具有重要意义。因此，重要的是要有准确的预测或至少是相关的方法。这项建议涉及对开发预测模型的研究，预测模型的热力学性质和工业上重要但复杂的混合物的相平衡。将考虑三种不同类型的混合物：氢键流体、蛋白质溶液和胶体体系。目前的基团贡献方法不能很好地描述氢键流体，如本提案中所述。原因是氢键的程度和强度受到与氢键相邻的分子上官能团的强烈影响。我们已经通过实验和从头算量子力学计算证明了这一点。我们现在建议开发基于基团贡献方法的新一代预测方法，该方法结合用于泛化色散力的基团贡献方法和用于氢键的分子特有的量子化学计算。蛋白质溶液及其纯化在许多生物处理应用中都是重要的。本文提出的研究涉及使用分子热力学和统计力学模型和计算机模拟来开发蛋白质在双水相体系中的分配和蛋白质沉淀的预测模型。胶体介于物质的宏观和微观之间，之所以引起人们的兴趣，是因为它们的行为影响着化学、生物化学和制药加工中的许多新兴技术。在液-液胶体体系中，存在两种尺度的相行为。在宏观尺度上是液-液相分离，或宏观相平衡。微观行为是在部分(或全部)分离相中形成微结构。液体胶体的许多重要特征是由形成的微观结构决定的。然而，要研究微观结构，首先需要了解宏观相行为，因为这识别了在其中形成微结构的相边界。这类体系的热力学模型一直相当简单，并没有捕捉到液体胶体体系宏观相界的温度和压力依赖关系。在这里，我们建议利用现代热力学方法对液-液胶体的宏观相行为进行建模研究，以更准确地描述胶体体系宏观相界随温度、压力和组成的变化。***