Phase-Separating Binary Polymer Mixtures: The Degeneracy of the Virial Coefficients and Their Extraction from Phase Diagrams

The Edmond-Ogston model for phase separation in binary polymer mixtures is based on a truncated virial expansion of the Helmholtz free energy up to the second-order terms in the concentration of the polymers. The second virial coefficients (B-11,B- B-12, B-22) are the three parameters of the model. Analytical solutions are presented for the critical point and the spinodal in terms of molar concentrations. The calculation of the binodal is simplified by splitting the problem into a part that can be solved analytically and a (two-dimensional) problem that generally needs to be solved numerically, except in some specific cases. The slope of the tie-lines is identified as a suitable parameter that can be varied between two well-defined limits (close to and far away from the critical point) to perform the numerical part of the calculation systematically. Surprisingly, the analysis reveals a degenerate behavior within the model in the sense that a critical point or tie-line corresponds to an infinite set of triplets of second virial coefficients (B-11,B- B-12, B-22). Since the Edmond-Ogston model is equivalent to the Flory- Huggins model up to the second order of the expansion in the concentrations, this degeneracy is also present in the Flory-Huggins model. However, as long as the virial coefficients predict the correct critical point, the shape of the binodal is relatively insensitive to the specific choice of the virial coefficients, except in a narrow range of values for the cross-virial coefficient B-12.

Automated summary

The Edmond-Ogston model is based on a truncated virial expansion of the Helmholtz free energy in binary polymer mixtures. The model's key parameters are the second virial coefficients. Analytical solutions are presented for the critical point and spinodal, with the calculation of the binodal simplified by splitting the problem into parts that may be solved analytically or numerically.