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.

O estudo de soluções proteicas visando à modelagem e à simulação de processos de recuperação e purificação de bioprodutos passa necessariamente pelo estudo da não idealidade, em sentido termodinâmico, destas soluções. Para sistemas em que a concentração de proteína seja baixa, situação comumente presente nestes processos, a principal maneira de avaliar experimentalmente a não idealidade é por meio da determinação da pressão osmótica gerada pela proteína. Deste modo, os objetivos deste trabalho foram: estudar a influência de co-solventes na pressão osmótica de soluções proteicas, verificar a integridade das estruturas secundária e terciária das proteínas nessas soluções, e modelar termodinamicamente os dados de pressão osmótica obtidos. A pressão osmótica foi determinada diretamente por osmometria de membrana, usando soluções de referência com mesma concentração de co-solvente e pH, mas isentas de proteínas. Obtiveram-se dados de pressão osmótica, em função da concentração proteica, de cinco diferentes proteínas (albumina de soro bovino, imunoglobulina G humana, ovalbumina, -lactoglobulina e lisozima) em soluções contendo co-solventes como o polietileno glicol (de diversos tamanhos de cadeia) e sais (sulfato de amônio, sulfato de sódio e cloreto de sódio). Cada conjunto de dados foi obtido em pH e concentração de co-solvente constantes. Observou-se que a presença de co-solventes altera a pressão osmótica, mas este efeito é dependente da proteína, do co-solvente e sua concentração, e do pH da solução. Medidas de fluorescência e de dicroísmo circular das mesmas proteínas permitiram confirmar que elas mantêm sua integridade estrutural nesses meios, o que justifica o uso de equações volumétricas de estado com parâmetros constantes. Os dados de pressão osmótica em função da concentração proteica foram correlacionados por meio de uma equação volumétrica de estado, que combina um termo de esferas rígidas adesivas e um termo de perturbação de ordem zero (aproximação aleatória). O modelo proposto, embora simples, foi suficiente para correlacionar adequadamente o comportamento experimental. / The study of protein solutions aiming at the modeling and simulation of downstream processes entails the study of non-ideality (in thermodynamic sense) of these solutions. For systems wherein the protein concentration is low a situation often encountered in these processes the most important technique to experimentally evaluate this non-ideality is the determination of the osmotic pressure generated by the protein in solution. Thus, the objectives of this work were: to study the influence of co-solvents on the osmotic pressure of protein solutions, to verify the absence of change in the secondary and tertiary structure of proteins in these solutions, and to thermodynamically model the obtained osmotic pressure data. The osmotic pressure was directly measured through membrane osmometry, using protein-free reference solutions with the same pH and co-solvent concentration. The data of osmotic pressure were obtained as a function of protein concentration for five different proteins (bovine serum albumin, human immunoglobulin G, ovalbumin, - lactoglobulin and lysozyme) in solution with co-solvents such as polyethylene glycol (of various chain sizes) and salts (ammonium sulfate, sodium sulfate and sodium chloride). Each data set was obtained at constant pH and co-solvent concentration. It was observed that the presence of co-solvents do shift the osmotic pressure, but this effect is dependent on the protein, the co-solvent and its concentration, and the solution pH. Measurements of fluorescence and circular dichroism of these proteins confirmed that they maintain their structure unchanged in the media, which corroborates the use of volumetric equations of state with constant parameters. The osmotic pressure data as a function of protein concentration were correlated using a osmotic equation of state comprising a repulsive term of adhesive hard spheres and a zero-order perturbation term (random approximation). The proposed model, though simple, was sufficient to properly correlate the experimental behavior.

O estudo de soluções proteicas visando à modelagem e à simulação de processos de recuperação e purificação de bioprodutos passa necessariamente pelo estudo da não idealidade, em sentido termodinâmico, destas soluções. Para sistemas em que a concentração de proteína seja baixa, situação comumente presente nestes processos, a principal maneira de avaliar experimentalmente a não idealidade é por meio da determinação da pressão osmótica gerada pela proteína. Deste modo, os objetivos deste trabalho foram: estudar a influência de co-solventes na pressão osmótica de soluções proteicas, verificar a integridade das estruturas secundária e terciária das proteínas nessas soluções, e modelar termodinamicamente os dados de pressão osmótica obtidos. A pressão osmótica foi determinada diretamente por osmometria de membrana, usando soluções de referência com mesma concentração de co-solvente e pH, mas isentas de proteínas. Obtiveram-se dados de pressão osmótica, em função da concentração proteica, de cinco diferentes proteínas (albumina de soro bovino, imunoglobulina G humana, ovalbumina, -lactoglobulina e lisozima) em soluções contendo co-solventes como o polietileno glicol (de diversos tamanhos de cadeia) e sais (sulfato de amônio, sulfato de sódio e cloreto de sódio). Cada conjunto de dados foi obtido em pH e concentração de co-solvente constantes. Observou-se que a presença de co-solventes altera a pressão osmótica, mas este efeito é dependente da proteína, do co-solvente e sua concentração, e do pH da solução. Medidas de fluorescência e de dicroísmo circular das mesmas proteínas permitiram confirmar que elas mantêm sua integridade estrutural nesses meios, o que justifica o uso de equações volumétricas de estado com parâmetros constantes. Os dados de pressão osmótica em função da concentração proteica foram correlacionados por meio de uma equação volumétrica de estado, que combina um termo de esferas rígidas adesivas e um termo de perturbação de ordem zero (aproximação aleatória). O modelo proposto, embora simples, foi suficiente para correlacionar adequadamente o comportamento experimental. / The study of protein solutions aiming at the modeling and simulation of downstream processes entails the study of non-ideality (in thermodynamic sense) of these solutions. For systems wherein the protein concentration is low a situation often encountered in these processes the most important technique to experimentally evaluate this non-ideality is the determination of the osmotic pressure generated by the protein in solution. Thus, the objectives of this work were: to study the influence of co-solvents on the osmotic pressure of protein solutions, to verify the absence of change in the secondary and tertiary structure of proteins in these solutions, and to thermodynamically model the obtained osmotic pressure data. The osmotic pressure was directly measured through membrane osmometry, using protein-free reference solutions with the same pH and co-solvent concentration. The data of osmotic pressure were obtained as a function of protein concentration for five different proteins (bovine serum albumin, human immunoglobulin G, ovalbumin, - lactoglobulin and lysozyme) in solution with co-solvents such as polyethylene glycol (of various chain sizes) and salts (ammonium sulfate, sodium sulfate and sodium chloride). Each data set was obtained at constant pH and co-solvent concentration. It was observed that the presence of co-solvents do shift the osmotic pressure, but this effect is dependent on the protein, the co-solvent and its concentration, and the solution pH. Measurements of fluorescence and circular dichroism of these proteins confirmed that they maintain their structure unchanged in the media, which corroborates the use of volumetric equations of state with constant parameters. The osmotic pressure data as a function of protein concentration were correlated using a osmotic equation of state comprising a repulsive term of adhesive hard spheres and a zero-order perturbation term (random approximation). The proposed model, though simple, was sufficient to properly correlate the experimental behavior.

The potential applications of dispersed and self-assembled nanoparticles depend critically on accurate control and prediction of their phase behavior. The chemical potential is essential in describing the equilibrium distribution of all components present in every phase of a system and is useful as a building block for constructing phase diagrams. Furthermore, the chemical potential is a sensitive indicator of the local environment of a molecule or particle and is defined in a mathematically rigorous manner in both classical and statistical thermodynamics. The goal of this research is to use simulations and experiments to understand how particle size and composition affect the particle chemical potential of attractive nanoparticle-polymer mixtures. The expanded ensemble Monte Carlo (EEMC) simulation method for the calculation of the particle chemical potential for a nanocolloid in a freely adsorbing polymer solution is extended to concentrated polymer mixtures. The dependence of the particle chemical potential and polymer adsorption on the polymer concentration and particle diameter are presented. The perturbed Lennard-Jones chain (PLJC) equation of state (EOS) for polymer chains1 is adapted to calculate the particle chemical potential of nanocolloid-polymer mixtures. The adapted PLJC equation is able to predict the EEMC simulation results of the particle chemical potential by introducing an additional parameter that reduces the effects of polymer adsorption and the effective size of the colloidal particle. Osmotic pressure measurements are used to calculate the chemical potential of nanocolloidal silica in an aqueous poly(ethylene oxide) (PEO) solution at different silica and PEO concentrations. The experimental data was compared with results calculated from Expanded Ensemble Monte Carlo (EEMC) simulations. The results agree qualitatively with the experimentally observed chemical potential trends and illustrate the experimentally-observed dependence of the chemical potential on the composition. Furthermore, as is the case with the EEMC simulations, polymer adsorption was found to play the most significant role in determining the chemical potential trends. The simulation and experimental results illustrate the relative importance of the particles size and composition as well as the polymer concentration on the particle chemical potential. Furthermore, a method for using osmometry to measure chemical potential of nanoparticles in a nanocolloid-mixture is presented that could be combined with simulation and theoretical efforts to develop accurate equations of state and phase behavior predictions. Finally, an equation of state originally developed for polymer liquid-liquid equilibria (LLE) was demonstrated to be effective in predicting nanoparticle chemical potential behavior observed in the EEMC simulations of particle-polymer mixtures.