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Modeling Dipolar Molecules with PCP-SAFT: A Vector Group-Contribution Method.

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This study introduces a new Vector-GC method for predicting thermodynamic properties using perturbed-chain polar (PCP)-SAFT models. The method accurately accounts for molecular symmetry in dipolar substances, improving predictions for vapor pressure and liquid density.

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Area of Science:

  • Chemical Engineering
  • Thermodynamics
  • Computational Chemistry

Background:

  • Predicting thermodynamic properties is crucial for chemical process development when experimental data is scarce.
  • Statistical associating fluid theory (SAFT) equations of state, like PCP-SAFT, are powerful tools for thermodynamic modeling.
  • Current group-contribution (GC) methods for PCP-SAFT have limitations in handling the dipole term, especially for molecules with multiple dipolar groups due to symmetry effects.

Purpose of the Study:

  • To develop an improved group-contribution (GC) method for the dipole term of perturbed-chain polar (PCP)-SAFT that accounts for molecular symmetry.
  • To enhance the predictive accuracy and applicability of GC methods for dipolar substances in thermodynamic modeling.
  • To provide an open-source, adaptable framework for future development and application of GC methods in SAFT.

Main Methods:

  • Proposed a vector-addition-based (Vector-GC) method for the dipole term of PCP-SAFT, utilizing molecular 3D structure information.
  • Predicted molecular dipole moments via vector addition of bond contributions, addressing symmetry effects.
  • Combined the Vector-GC method with established sum rules for other PCP-SAFT parameters, creating a consistent GC approach for dipolar substances.

Main Results:

  • The Vector-GC method demonstrated improved predictions for vapor pressure and liquid density compared to methods neglecting the dipole term.
  • Successfully enabled differentiation between cis- and trans-isomers, highlighting its sensitivity to molecular structure.
  • Validated against experimental data for nonassociating oxygenated and halogenated substances.

Conclusions:

  • The Vector-GC method significantly enhances the predictive capabilities and expands the applicability of group-contribution methods for PCP-SAFT.
  • The open-source availability of the Vector-GC method and its regression framework promotes wider adoption and further research.
  • This approach overcomes limitations in current GC methods, enabling more accurate thermodynamic property predictions for complex dipolar molecules.