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Polymers having many ionizable groups in their molecular structure are called Polyelectrolytes. They are extensively used in industries like papermaking, food processing, medicine and pharmaceuticals, water purification, oil field exploration, cosmetic formulation etc. In spite of wide applicability its current status of knowledge is precursory due complexity of their behavior in solution as well as at interface. Solution properties of polyelectrolytes are extensively studied in last 40 years to understand their behavior. The activity is important thermodynamic property. From activity we can get most of thermodynamic properties like interaction parameter, free energy of dilution of the polyelectrolyte, degree of dissociation of polyelectrolytes etc.Several models of Polyelectrolytes thermodynamics have been proposed. Two general approaches have been used to model Polyelectrolytes thermodynamics, spherical and cylindrical (chain) models. Two of the successful models to explain and predict commonly measured properties of polyelectrolytes such as osmotic coefficient and counterion activity coefficients have been proposed by Manning and Oosawa. Most of these models are applicable at infinite dilution only may be due to weak inter chain interactions. An Excess Gibb’s free energy model can predict properties at finite concentrations of polyelectrolytes, which is combination of Manning model and Local composition model.Vapor pressure osmometry and isothermal Titration Microcalorimetry are experimental methods to determine the thermodynamic properties of polymer solvent system. Osmometry helps to understand the thermodynamics of polymer solutions as it determines the value of osmotic pressure, which in turn gives the value of thermodynamic parameters. Isothermal Titration Microcalorimetry gives the heat of dilution directly from which we can calculate activity of the solution.The osmotic coefficient and activity of water in aqueous NaPSS solution are found out using Vapor pressure osmometry and Isothermal titration calorimeter at different temperatures. The results are compared with result obtained by an excess Gibb’s free energy model. Measured data show good agreement with available literature data at that temperature.

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 1981. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND SCIENCE. / Bibliography: leaves 43-44. / by Miral Eonhah Kim-E. / M.S.

Thesis (Sc. D.)--University of Michigan, 1960. / Abstracted in Dissertation abstracts, v. 21 (1960) no. 8, p. 2220. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references.

Thesis (Ph. D.)--Institute of Paper Chemistry, 1969. / Includes bibliographical references (p. 77-79).

Balancing plant growth between vegetative and reproductive status is crucial for producing high quality greenhouse tomatoes while maintaining high productivity in long crop production seasons. In the tomato industry, certain plant morphological characteristics are used to classify plant growth status as vegetative, reproductive or balanced. Each growth status has been associated with distinct greenhouse environments which reduce or enhance transpiration.The effect of different transpiration on vegetative, reproductive or balanced plant growth status as defined by a set of plant morphological characteristics was investigated. To validate the practical significance of such classification, growth status was quantified as the relationship between variations in morphological characteristics and the fresh weight distributed between reproductive and vegetative organs.Two electrical conductivity (EC) levels of the nutrient solution, high and standard EC, were combined with two potential transpiration environments, low and high potential transpiration. All treatment combinations were contrasted with a reference greenhouse environment similar to the industry standard.Electrical conductivity had the greatest effect on morphological characteristics which were reduced in size with high EC. For each EC level, the response decreased for increasing potential transpiration. Stem diameter had the greatest sensitivity to the different treatment combinations. For the standard EC and for the range of potential transpirations achieved, stem diameter varied within a relatively narrow range, close to the industry standard 'threshold' used to classify a balanced tomato plant. A reproductive plant growth status, as evaluated by a smaller value than this threshold, was observed only with high EC. No vegetative plants were produced within any potential transpiration or EC treatment combination.High EC decreased the cumulative total fresh weight production by the same magnitude for all potential transpirations. Potential transpiration had a minimal effect on the total fresh weight production or on its components. As a result, the fresh weight ratio between reproductive and vegetative plant organs was similar for most potential transpiration environments, regardless of variations in stem diameter. Therefore, within the range of potential transpiration environments achieved, the distinction between vegetative and reproductive growth status as an indicator of fresh weight distribution and fruit yields could not be quantitatively validated.

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Thermodynamic relationships are used to predict several physicochemical properties of organic compounds. As described in chapter one, the UPPER model (Unified Physicochemical Property Estimation Relationships) has been used to predict nine essential physicochemical properties of pure compounds. It was developed almost 25 years ago and has been validated by the Yalkowsky group for almost 2000 aliphatic, aromatic, and polyhalogenated hydrocarbons. UPPER is based on a group of additive and nonadditive descriptors along with a series of well-accepted thermodynamic relationships. In this model, the two-dimensional chemical structure is the only input needed. Chapter (1) extends the applicability of UPPER to hydrogen bonding and non-hydrogen bonding aromatic compounds with several functional groups such as alcohol, aldehyde, ketone, carboxylic acid, carbonate, carbamate, amine, amide, nitrile as well as aceto, and nitro compounds. The total data set includes almost 3000 compounds. Aside from the enthalpies and entropies of melting and boiling, no training set is used for the calculation of the properties. The results show that UPPER enables a reasonable estimation of all the considered properties. Chapter (2) uses modification of the van't Hoff equation to predict the solubility of organic compounds in dry octanol as explained in chapter two. The equation represents a linear relationship between the logarithm of the solubility of a solute in octanol to its melting temperature. More than 620 experimentally measured octanol solubilities, collected from the literature, are used to validate the equation without using any regression or fitting. The average absolute error of the prediction is 0.66 log units. Chapter (3) compares the use of a statistic based model for the prediction of aqueous solubility to the existing general solubility equation (GSE).