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Title page for ETD etd-07312015-123309

Type of Document Dissertation
Author Das, Gaurav
Author's Email Address gauravdas.ju@gmail.com
URN etd-07312015-123309
Title Predicting the thermophysical properties of molecules with anisotropic interaction and structure using the statistical associating fluid theory
Degree PhD
Department Chemical Engineering
Advisory Committee
Advisor Name Title
Clare McCabe Committee Chair
Florence Sanchez Committee Member
kenneth Debelak Committee Member
Peter T. Cummings Committee Member
  • statistical mechanics
  • aqueous chemistry
  • molecular simulation
  • electrolyte chemistry
  • Phase equilibria
Date of Defense 2015-05-20
Availability unrestricted
Over the last 25 years, the statistical associating fluid theory (SAFT) has been developed and refined in order to describe the thermophysical properties and phase behavior of a wide range of pure fluids. These include for example polymers, alcohols, water, refrigerant systems, carbon dioxide, amines, electrolytes, ionic liquids, biomolecules and nanoparticles. The success of SAFT is due to its molecular basis and firm roots in statistical mechanics that enable the theoretical framework to be systematically improved. In this work we rigorously incorporate the effects of anisotropic interactions, such as polar and electrostatic interactions or structural anisotropy, on the thermodynamic properties of fluids through modification of the reference fluid within the SAFT framework. Specifically, new theoretical approaches based on the SAFT-VR equation, which considers potential models of variable attractive range, are proposed. First, we implement a novel-modeling scheme for aromatic rings that enables the accurate theoretical description of benzene and the highly anisotropic alkylbenzenes. Second, we extend the SAFT-VR approach to the predictive study of aqueous electrolyte solutions, where a range of thermodynamic properties such as osmotic coefficient, water activity coefficient, Gibbs free energy of hydration, dielectric decay, and solution densities are studied and described with excellent accuracy and in most cases using only a single fitted parameter. The theoretical approach for aqueous electrolytes was then extended to describe mixed solvent electrolyte systems and the theory tested extensively against Monte Carlo simulations of model systems for validation before application to experimental mixed solvent electrolyte systems.
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