Identification and characterization of non-flammable azeotropic mixtures for precision cleaning
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The goal of this thesis is to provide methods that can be used to search for new azeotropes with specific desired properties, and methods to characterize these new azeotropes. All azeotrope possibilities that were examined in this study were low-boiling azeotropes composed of non-aqueous solvents, and the desired properties were for the azeotropes to be non-flammable and have good solvency against hydrocarbon grease. In this study, azeotropes were formed for use in cleaning applications, specifically vapor degreasing. For cleaning applications, the most important quality of the azeotrope is solvency. However, in a vapor degreaser flammability is an issue. To obtain the desired solvency in an azeotrope, the Hansen Solubility Parameters (HSPs) were used to decide what solvents were good candidates. However, the solvents that were found from this search were flammable. In an attempt to get the desired properties, the solvents were paired with non-flammable solvents that had similar boiling points to obtain a blend with good solvency and no flammability. Then, these pairs were mixed and distilled to identify whether the pairs formed low-boiling azeotropes. The resulting azeotropes were characterized by obtaining their boiling point, flash point, thermal expansion coefficient, surface tension, density, viscosity and composition. The boiling points were obtained from the distillation process. The flash points were found using a modified ASTM D56 method. Thermal expansion coefficients were obtained through the dependence of the density on temperature. The surface tension and density were obtained using a DuNouy ring tensiometer. Viscosity was found using a ball drop viscometer. Finally, the composition was found using Raman spectroscopy. All these standard procedures can be found in the appendix. A solubility parameter-based model for predicting azeotropic behavior in binary mixtures was explored as an extension of the results of this thesis work. The goal of this model is to predict the likelihood that a given pair of solvents will form a low-boiling azeotrope. Such a model would save time in the laboratory, reduce personnel exposure, and reduce waste by steering the researchers away from unpromising mixtures that are unlikely to form azeotropes.