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Techniques for the Evolution of Robust Pentose-fermenting Yeast for Bioconversion of Lignocellulose to Ethanol
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Bioethanol production optimization: a thermodynamic analysis.

Víctor H Alvarez1, Elmer Ccopa Rivera, Aline C Costa

  • 1School of Chemical Engineering, State University of Campinas, P.O. Box 6066, 13083-970, Campinas, SP, Brazil.

Applied Biochemistry and Biotechnology
|April 18, 2008
PubMed
Summary
This summary is machine-generated.

This study models vapor-liquid equilibrium for bioethanol production, improving congener separation predictions. Enhanced UNIFAC model parameters accurately forecast congener concentrations in gas phases.

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Area of Science:

  • Chemical Engineering
  • Thermodynamics
  • Separation Processes

Background:

  • Bioethanol production involves complex separation steps, particularly in the flash vessel where ethanol and congeners are separated.
  • Accurate phase equilibrium data is crucial for optimizing continuous extractive processes and minimizing energy consumption.
  • Existing models may not sufficiently predict the behavior of binary mixtures containing ethanol and various organic congeners.

Purpose of the Study:

  • To investigate and model the vapor-liquid equilibrium (VLE) of binary mixtures relevant to the flash vessel in a continuous bioethanol production process.
  • To evaluate the Predictive Soave-Redlich-Kwong (PSRK) equation of state with modified parameters for VLE calculations.
  • To assess the performance of the UNIFAC model with new molecular parameters (r and q) for predicting congener concentrations in the gas phase.

Main Methods:

  • Utilized the Predictive Soave-Redlich-Kwong (PSRK) equation of state for thermodynamic modeling.
  • Employed the UNIFAC (UNIquac Functional group Activity Coefficients) model with original and modified molecular parameters (r and q).
  • Focused on binary mixtures containing bioethanol and common congeners such as acetic acid, acetaldehyde, furfural, methanol, and 1-pentanol.

Main Results:

  • The PSRK equation of state was applied to model the VLE of binary mixtures.
  • The introduction of new molecular parameters (r and q) into the UNIFAC model significantly improved prediction accuracy.
  • The modified UNIFAC model demonstrated enhanced ability to predict congener concentrations in the gas phase for both binary and ternary systems.

Conclusions:

  • The modified UNIFAC model offers superior accuracy for predicting vapor-liquid equilibrium in bioethanol-related mixtures.
  • Accurate phase equilibrium modeling is essential for optimizing the design and operation of separation units in bioethanol production.
  • This research provides a more reliable tool for engineers designing continuous extractive processes for bioethanol, leading to improved efficiency and purity.