Title page for ETD etd-12022004-141526

Type of Document Master's Thesis
Author Oldland, Richard Justin
Author's Email Address roldland@vt.edu
URN etd-12022004-141526
Title Predicting Phase Equilibria Using COSMO-Based Thermodynamic Models and the VT-2004 Sigma-Profile
Degree Master of Science
Department Chemical Engineering
Advisory Committee
Advisor Name Title
Liu, Y. A. Committee Chair
Davis, Richey M. Committee Member
Marand, Eva Committee Member
  • VT-2004
  • computational thermodynamics
  • solvation thermodynamics
  • sigma profile
Date of Defense 2004-11-16
Availability unrestricted
Solvation-thermodynamics models based on computational quantum mechanics, such as the conductor-like screening model (COSMO), provide a good alternative to traditional group-contribution methods for predicting thermodynamic phase behavior. Two COSMO-based thermodynamic models are COSMO-RS (real solvents) and COSMO-SAC (segment activity coefficient). The main molecule-specific input for these models is the sigma profile, or the probability distribution of a molecular surface segment having a specific charge density. Generating the sigma profiles represents the most time-consuming and computationally expensive aspect of using COSMO-based methods. A growing number of scientists and engineers are interested in the COSMO-based thermodynamic models, but are intimidated by the complexity of generating the sigma profiles. This thesis presents the first free, open-literature database of 1,513 self-consistent sigma profiles, together with two validation examples. The offer of these profiles will enable interested scientists and engineers to use the quantum-mechanics-based, COSMO methods without having to do quantum mechanics. This thesis summarizes the application experiences reported up to October 2004 to guide the use of the COSMO-based methods. Finally, this thesis also provides a FORTRAN program and a procedure to generate additional sigma profiles consistent with those presented here, as well as a FORTRAN program to generate binary phase-equilibrium predictions using the COSMO-SAC model.
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