(392f) Calculation of Glass Transition Using Sanchez-Lacombe - Eos


Calculation of glass
transition using Sanchez-Lacombe - EOS

Margarete Roericht, Kirstin Taufertshöfer, Sabine Enders

Karlsruhe Institute of Technology, Institute of Technical
Thermodynamics and Refrigeration Engineering, Engler-Bunte-Ring 21, 76131 Karlsruhe,

Email: margarete.roericht@kit.edu,
kirstin.taufertshoefer@kit.edu; sabine.enders@kit.edu

Key words: Glass
transition temperature of polymers and polymer blends, Sanchez-Lacombe Model,
generalized entropy theory


The development of reliable approaches for the prediction
of the thermodynamic properties of polymer systems is crucial for the rational
design of polymer materials and polymer processing in a wide range of polymer
applications (for example energy storage, electronics, food, controlled drug
delivery systems, medical devises). Glasses are disordered materials that lack
the periodicity of crystals but behave mechanically like solids.

The assumption that the glass transition is basically
thermodynamic in nature was used to derive a theoretical framework for the
calculation of the glass transition temperature (Tg) of polymers,
copolymers and polymer blends [1,2,3]. The theory is a synthesis of a thermodynamic equation
of state suitable for polymers, the generalized
entropy theory for glass-formation in polymer materials, and the rigorous
Kirkwood-Buff theory for concentration fluctuations in binary mixtures [2,3].

In the present contribution this theoretical framework
is applied in order to compare the theoretical results with experimental data
taken from the literature. We apply the Sanchez-Lacombe equation of state
(SL-EOS) [4], because the pure-component parameters for several different
polymers (polystyrene, (PS); poly(vinyl methyl ether), (PVME); poly(methyl methacrylate), (PMMA); poly(p-phenylene oxide), (PPO))
as well as for the statistical copolymer consisting of styrene
and acrylonitrile (PSAN) are available. Unfortunately, the parameters for
polyacrylonitrile (PAN) are not
available, because no PVT data can be measured with high accuracy. The reason
for this finding is the thermal instability of this polymer. Therefore, the
pure-component parameter for PAN were estimated using PS and PSAN data

Using the above mentioned theoretical
framework [1] the Tg of pure polymers was calculated as function of
the molecular weight, and compared to experimental data. The analysis shows,
that one adjustable parameter per pure polymer is required to match experimental
Tg data. Regarding the molecular weight dependency, the theory
predicts correctly that the Tg tends towards a limiting value for
high molecular weight polymers. This concept can also be applied to statistical
copolymers (i.e. PSAN), where the Tg is predicted as function of the
chemical composition in excellent agreement with experimental data taken from
the literature [5].

This theoretical method can also be applied for
polymer blends, where the Kirkwood-Buff formalism
serves for the determination of the concentration fluctuation. These
calculations were performed for blends made of PS and PVME, where the Tg
was investigated as function of blend composition [6]. Blends made of PS and
PPO serve as an additional example, where experimental data are taken from [7].
In both cases, the Tg runs monotonically from the Tg of
one pure polymer to the Tg of the other pure polymer. In contrast,
the Tg as function of blend composition made of PSAN + PMMA [8] runs
through a maximum.

The obtained values agree very nicely with experimental data [6,7,8].


[1] J.
Dudowicz, K.F. Freed, J.F. Douglas, Adv. Chem. Physics 137 (2008) 125.

[2] J. Dudowicz, J.F. Douglas, K.F.
Freed, J. Chem. Phys. 140 (2014) 244905.

[3] J. Dudowicz, J.F. Douglas,
K.F. Freed, J. Chem. Phys. 141 (2014) 234903.

[4] I.C. Sanchez, R.H. Lacombe, Macromolecules 11
(1978) 1145.

[5] L. Fan, D. Zhao, C. Bian, Y. Wang,
G. Liu, Polym.
Bull. 67 (2011) 1311.

[6] E. Leroy, A. Alegría, J. Colmenero, Macromolecules 35 (2002) 5587.

[7] W.M. Prest, R.S. Porter, J. Polym. Sci. A-2 10
(1972) 1639.

[8] G. Wen, L. An, J. Appl. Polym. Sci. 90 (2003) 959.