Skip to main content
Log in

Development of a Unifying Framework for Modeling Multi-component Diffusion in Polymer Solutions

  • Published:
Journal of Solution Chemistry Aims and scope Submit manuscript

Abstract

In this work a unifying framework for modeling multi-component diffusion in mixed solvent polymer solutions is developed by introducing additional restrictions such as the Onsager reciprocal relations (ORR) and the quasi-equilibrium postulate. More specifically, three different multi-component diffusion models, namely the Zielinski and Hanley model, the Dabral et al. theory and the Alsoy–Duda model are revised by using the above restrictions which are based on sound principles of non-equilibrium thermodynamics. Realistic simulations for the solvent(s) evaporation from the water/acetone/cellulose acetate (CA) and formamide/acetone/CA systems were obtained by combining the above multi-component diffusion models with the ORR and the quasi-equilibrium postulate. It is believed that the results of this work could be used to further study diffusion in multi-component systems appearing in coating and membrane formation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Abbreviations

a i :

Auxiliary parameters

C i , C Ti :

Auxiliary parameter, dimensionless

C p :

Specific heat capacity, J·kg−1·K−1

C p0 :

Scaling factor, J·kg−1·K−1

D 0 :

Scaling factor, m2·s−1

\( \overline{D}_{ij} \) :

Maxwell–Stefan diffusion coefficient with respect to the mass concentration, m2·s−1

D ij :

Diffusion coefficient with respect to mass concentration, m2·s−1

\( D_{i}^{{}} \) :

Self diffusion coefficient of the i-th substance, m2·s−1

h :

Heat transfer coefficient, W·m2·K−1

j i,int :

Mass flux of the i-th substance at the liquid–gas interface, kg·m−2·s−1

\( \user2{J}_{i}^{ \ne } \),:

Mass flux defined relative to an arbitrary velocity, kg·m−2·s−1

k :

Thermal conductivity, W·m−1·K−1

\( L_{ij}^{{}} \) :

Conductivity coefficient between the i-th and j-th substance, kg2·J−1·m−1·s−1

L sup :

Support axial depth, m

M i :

Molecular weight of the i-th substance, kg·mol−1

R :

Universal gas constant, J·mol−1·K−1

\( R_{ij}^{{}} \) :

Resistance coefficient between the i-th and j-th substance, J·m·s·kg−2

s :

Position of the moving boundary, dimensionless

S :

Rate of entropy production per unit volume, J·K−1·m−3

t :

Time, s

T :

Temperature, K

T 0 :

Initial temperature, K

u i :

Volume fraction of i-th substance, dimensionless

u i0 :

Initial volume fraction of i-th substance, dimensionless

v i :

Local velocity, m·s−1

\( \user2{v}^{ \ne } \) :

Arbitrary velocity, m·s−1

V i :

Partial specific volume of the i-th substance, m3·kg−1

w i :

Weighting factors whose sum is equal to unity, dimensionless

X i :

Thermodynamic driving force for diffusion, J·kg−1·m−1

z :

Axial coordinate, m

γ i :

Activity coefficient, dimensionless

ΔΗ i :

i-th Substance latent heat of vaporization, J·kg−1

ε :

Emissivity of the polymer solution, dimensionless

η :

Dimensionless depth

Θ :

Dimensionless temperature

μ i :

Chemical potential of the i-th substance, J·kg−1

μ di :

Dimensionless chemical potential of the i-th substance

\( \varvec{\rho} \) :

Total mass density, kg·m−3

ρ 0 :

Scaling parameter, kg·m−3

ρ i :

Mass density of the i-th substance, kg·m−3

ρ s :

Density of the polymer solution, kg·m−3

σ :

Stefan–Boltzmann constant, W·m−2·K−4

τ :

Dimensionless time

Ψ :

Dissipation function, J·m−3·s−1

int:

Interface

s:

Solution

sup:

Properties and variables of the support

References

  1. Taylor, R., Krishna, R.: Multicomponent Mass Transfer. Wiley, New York (1993)

    Google Scholar 

  2. Cussler, E.L.: Diffusion Mass Transfer in Fluid Systems. Cambridge University Press, Cambridge (1997)

    Google Scholar 

  3. Slattery, J.C.: Advanced Transport Phenomena. Cambridge University Press, Cambridge (1999)

    Book  Google Scholar 

  4. Bird, R.B., Stewart, W.E., Lightfoot, E.N.: Transport Phenomena. Wiley, New York (2002)

    Google Scholar 

  5. Onsager, L., Fuoss, R.M.: Irreversible processes in electrolytes: diffusion, conductance, and viscous flow in arbitrary mixtures of strong electrolytes. J. Phys. Chem. 36, 2659–2778 (1932)

    Google Scholar 

  6. Onsager, L.: Theories and problems of liquid diffusion. Ann. N.Y. Acad. Sci. 46, 241–265 (1945)

    Article  CAS  Google Scholar 

  7. Vrentas, J.S., Duda, J.L.: Diffusion in polymer–solvent systems. I. Re-examination of the free-volume theory. J. Polym. Sci. Part B 15, 403–416 (1977)

    CAS  Google Scholar 

  8. Vrentas, J.S., Duda, J.L.: Diffusion in polymer–solvent systems II. A predictive theory for the dependence of diffusion coefficients on temperature, concentration and molecular weight. J. Polym. Sci. Part B 15, 417–439 (1977)

    CAS  Google Scholar 

  9. Vrentas, J.S., Duda, J.L., Ling, H.C.: Free-volume theories for self-diffusion in polymer–solvent systems. I. Conceptual differences in theories. J. Polym. Sci. 22, 459–469 (1984)

    CAS  Google Scholar 

  10. Vrentas, J.S., Duda, J.L., Ling, H.C.: Enhancement of impurity removal from polymer films. J. Appl. Polym. Sci. 30, 4499–4516 (1985)

    Article  CAS  Google Scholar 

  11. Dabral, M., Francis, L.F., Scriven, L.E.: Drying process paths of ternary polymer solution coating. AIChE J. 48, 25–37 (2002)

    Article  CAS  Google Scholar 

  12. Zielinski, J.M., Hanley, B.F.: Practical friction-based approach to modelling multicomponent diffusion. AIChE J. 45, 1–12 (1999)

    Article  CAS  Google Scholar 

  13. Alsoy, S., Duda, J.L.: Modeling of multicomponent drying of polymer films. AIChE J. 45, 896–905 (1999)

    Article  CAS  Google Scholar 

  14. Price Jr, P.E., Romdhane, I.H.: Multicomponent diffusion theory and its applications to polymer–solvent systems. AIChE J. 49, 309–322 (2003)

    Article  CAS  Google Scholar 

  15. Kirkaldy, J.S., Weichert, D., Zia-Ul-Haq, : Diffusion in multicomponent metallic systems. VI. Some thermodynamic properties of the D matrix and the corresponding solutions of the diffusion equations. Can. J. Phys. 41, 2166–2173 (1963)

    Article  CAS  Google Scholar 

  16. Tyrrell, H.J.V., Harris, K.R.: Diffusion in Liquids. A Theoretical and Experimental Study. Butterworths, London (1984)

    Google Scholar 

  17. Verros, G.D., Xentes, G.K.: Development of a unifying framework for the restrictions in multi-component diffusion close to equilibrium. J. Solution Chem. doi:10.1007/s10953-013-0018-6

  18. Schmitt, A., Craig, J.B.: Frictional coefficient formalism and mechanical equilibrium in membranes. J. Phys. Chem. 81, 1338–1342 (1977)

    Article  CAS  Google Scholar 

  19. Miller, D.G.: Thermodynamics of irreversible processes: the experimental verification of the Onsager reciprocal relations. Chem. Rev. 60, 15–37 (1960)

    Article  CAS  Google Scholar 

  20. Hirschfelder, J.O., Curtiss, C.F., Bird, R.B.: Molecular Theory of Gases and Liquids. Wiley, New York (1964)

    Google Scholar 

  21. de Groot, S.R., Mazur, P.: Non-Equilibrium Thermodynamics. Dover Publications, New York (1984)

    Google Scholar 

  22. Kuiken, G.D.C.: Thermodynamics of Irreversible Processes—Applications to Diffusion and Rheology. Wiley, New York (1994)

    Google Scholar 

  23. Demirel, Y.A., Sandler, S.I.: Nonequilibrium thermodynamics in engineering and science. J. Phys. Chem. B 108, 31–43 (2004)

    Article  CAS  Google Scholar 

  24. Onsager, L.: Reciprocal relations in irreversible processes I. Phys. Rev. 37, 405–426 (1931)

    Article  CAS  Google Scholar 

  25. Onsager, L.: Reciprocal relations in irreversible processes II. Phys. Rev. 37, 2265–2279 (1931)

    Article  Google Scholar 

  26. Verros, G.D.: On the validity of the Onsager reciprocal relations in multi-component diffusion. Phys. Lett. A 365, 34–38 (2007)

    Article  CAS  Google Scholar 

  27. Verros, G.D.: On the validity of the Onsager reciprocal relations in simultaneous heat and mass transfer. Phys. A 385, 487–492 (2007)

    Article  CAS  Google Scholar 

  28. Miller, D.G.: Application of irreversible thermodynamics to electrolyte solutions. I. Determination of ionic transport coefficients l ij for isothermal vector transport processes in binary electrolyte systems. J. Phys. Chem. 70, 2639–2659 (1966)

    Article  CAS  Google Scholar 

  29. Nauman, E.B., Savoca, J.: An engineering approach to an unsolved problem in multicomponent diffusion. AIChE J. 47, 1016–1021 (2001)

    Article  CAS  Google Scholar 

  30. Miller, D.G.: Ternary isothermal diffusion and the validity of the Onsager reciprocity relations. J. Phys. Chem. 63, 570–578 (1959)

    Article  CAS  Google Scholar 

  31. Flory, P.J.: Principles of Polymer Chemistry. Cornell University Press, Ithaca (1953)

    Google Scholar 

  32. Verros, G.D.: Application of non-equilibrium thermodynamics and computer aided analysis to the estimation of diffusion coefficients in polymer solutions: the solvent evaporation method. J. Membr. Sci. 328, 31–57 (2009)

    Article  CAS  Google Scholar 

  33. Krantz, W.B., Greenberg, A.R., Hellman, D.J.: Dry-casting: Computer simulation, sensitivity analysis, experimental and phenomenological model studies. J. Membr. Sci. 354, 178–188 (2010)

    Article  CAS  Google Scholar 

  34. Verros, G.D., Malamataris, N.A.: Computer-aided estimation of diffusion coefficients in non-solvent/polymer systems. Macromol. Theory Simul. 10, 737–749 (2001)

    Article  CAS  Google Scholar 

  35. Verros, G.D., Malamataris, N.A.: Multi-component diffusion in polymer solutions. Polymer 46, 12626–12636 (2005)

    Article  CAS  Google Scholar 

  36. Yilmaz, L., McHugh, A.J.: Analysis of nonsolvent–solvent–polymer phase diagrams and their relevance to membrane formation modeling. J. Appl. Polym. Sci. 31, 997–1018 (1986)

    Article  CAS  Google Scholar 

  37. Shojaie, S.S.: Polymeric dense films and membranes via the dry-cast phase inversion process. Modeling, casting and morphological studies. Ph.D. thesis, Boulder, Colorado (1992)

  38. Shojaie, S.S., Krantz, W.B., Greenberg, A.R.: Dense polymer film and membrane formation via the dry-cast process. Part I. Model development. J. Membr. Sci. 94, 255–280 (1994)

    Article  CAS  Google Scholar 

  39. Shojaie, S.S., Krantz, W.B., Greenberg, A.R.: Dense polymer film and membrane formation via the dry-cast process. Part II. Model validation and morphological studies. J. Membr. Sci. 94, 281–298 (1994)

    Article  CAS  Google Scholar 

  40. Greenberg, A.R., Shojaie, S.S., Krantz, W.B., Tantekin-Ersolmaz, S.B.: Use of infrared thermography for temperature measurement during evaporative casting of thin polymeric films. J. Membr. Sci. 107, 249–261 (1995)

    Article  CAS  Google Scholar 

  41. Ohya, H., Sourirajan, S.: Determination of concentration changes on membrane surface as function of time during evaporation of reverse-osmosis film casting solutions. J. Appl. Polym. Sci. 15, 705–713 (1971)

    Article  CAS  Google Scholar 

  42. Ju, S.T., Duda, J.L., Vrentas, J.S.: Influence of temperature on diffusion of solvents in polymers above the glass transition. Ind. Eng. Chem. Prod. Res. Dev. 20, 330–335 (1981)

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to George D. Verros.

Appendix

Appendix

The starting point for the derivation of Miller’s equation in the case of a diffusing polymer ternary solution close to equilibrium and in the absence of external forces is the dissipation function Ψ (see Eq. 7):

$$ \varPsi = TS = \sum\limits_{i = 1}^{3} {J_{i}^{ \ne } X_{i}^{{}} } $$
(36)

Obviously, the thermodynamic force \( X_{i} = \frac{{\partial \left( {\mu_{i} } \right)_{T,p} }}{\partial z} \) is subject to the Gibbs–Duhem restrictions:

$$ \sum\limits_{i = 1}^{3} {\rho_{i} X_{i} = 0} . $$
(37)

By taking into account that the fluxes are linearly dependent and there is no volume change during the diffusion experiment, the following equation holds true:

$$ \sum\limits_{i = 1}^{3} {V_{i} J_{i}^{ \ne } = 0} $$
(38)

where \( V_{i} \) represents the partial specific volume of the i-th substance. By further using Eq. 3638 the dissipation function can be written as:

$$ \varPsi = J_{1}^{ \ne } Y_{1} + J_{2}^{ \ne } Y_{2} $$
(39)

where

$$ \begin{aligned} Y_{1} & = \left[ {1 + \frac{{\rho_{1} V_{1} }}{{\rho_{3} V_{3} }}} \right]X_{1} + \left[ {\frac{{\rho_{2} V_{2} }}{{\rho_{3} V_{3} }}} \right]X_{2} = \alpha X_{1} + \beta X_{2} \\ Y_{2} & = \left[ {\frac{{\rho_{1} V_{2} }}{{\rho_{3} {\text{V}}_{3} }}} \right]X_{1} + \left[ {1 + \frac{{\rho_{2} {\text{V}}_{2} }}{{\rho_{3} {\text{V}}_{3} }}} \right]X_{2} = \gamma X_{1} + \delta X_{2} \\ \end{aligned} $$

By applying the linearity postulate in the above equations the following law is derived:

$$ J_{1}^{ \ne } = L_{11} Y_{1} + L_{12} Y_{2} ;\,J_{2}^{ \ne } = L_{12} Y_{1} + L_{22} Y_{2} $$
(40)

where the L ij are the mass conductivity coefficients.

Fick’s law for a ternary diffusing system can be written in terms of the mass concentration ρ i as:

$$ \begin{aligned} J_{1m} & = - D_{11} \frac{{\partial \rho_{1} }}{\partial z} - D_{12} \frac{{\partial \rho_{2} }}{\partial z} \\ J_{2m} & = - D_{21} \frac{{\partial \rho_{1} }}{\partial z} - D_{22} \frac{{\partial \rho_{2} }}{\partial z} \\ \end{aligned} $$
(41)

By using the chain rule to write the partial derivatives appearing in Fick’s law in terms of chemical potential and by comparing the coefficients with the reported coefficients in Eq. 40 one obtains:

$$ \begin{aligned} - D_{11} & = \left[ {\alpha \mu_{11} + \beta \mu_{21} } \right]L_{11m} + \left[ {\gamma \mu_{11} + \delta \mu_{21} } \right]L_{12m} = aL_{11} + bL_{12} \\ - D_{12} & = \left[ {\alpha \mu_{12} + \beta \mu_{22} } \right]L_{11m} + \left[ {\gamma \mu_{12} + \delta \mu_{22} } \right]L_{12m} = cL_{11} + dL_{12} \\ - D_{21} & = aL_{21} + bL_{22} \\ - D_{22} & = cL_{21} + dL_{22} \\ \end{aligned} $$
(42)

where a, b, c, d denote the terms in the corresponding square brackets and μ ij stands for \( \frac{{\partial \left( {\mu_{i} } \right)_{T,p} }}{{\partial \rho_{j} }} \). Solution of Eq. 42 for L ij then yields:

$$ \begin{aligned} L_{11} & = \frac{{bD_{12} - dD_{11} }}{ad - bc},\,L_{12} = \frac{{cD_{11} - aD_{12} }}{ad - bc} \\ L_{21} & = \frac{{bD_{22} - dD_{21} }}{ad - bc},\,L_{22} = \frac{{cD_{21} - aD_{22} }}{ad - bc} \\ \end{aligned} $$
(43)

The necessary and sufficient condition that L 12 = L 21 (ORR) is

$$ aD_{12} + bD_{22} = cD_{11} + dD_{21} ,\,ad - bc \ne 0 $$
(44)

Obviously, Eq. 44 satisfies both the ORR and the quasi-equilibrium postulate.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Verros, G.D., Xentes, G.K. Development of a Unifying Framework for Modeling Multi-component Diffusion in Polymer Solutions. J Solution Chem 43, 206–226 (2014). https://doi.org/10.1007/s10953-013-0125-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10953-013-0125-4

Keywords

Navigation