Huggins coefficient polymers

Gundert F, Wolf BA (1986) Viscosity of dilute polymer solutions molecular weight dependence of the Huggins coefficient Makromol Chem 187 2969... 

Here kH is the Huggins coefficient. The intrinsic viscosity decreases and the Huggins coefficient increases, as micelles become smaller. On micellization, ijsp/c has been observed to increase for some systems but to decrease for others, and unfortunately there are no firm rules governing which case will prevail for a given block copolymer solution. The viscosities of polymer solutions are measured in capillary flow viscometers, which are described in detail by Macosko (1994). 

Here, the intrinsic viscosity [r ] is defined as the infinite dilution limit of the reduced viscosity and kH is Huggins coefficient. This result is valid up to the second order in concentration. The PFPE solvent interaction is related to kfj [r ]2. For flexible polymer chains in a theta solvent, kn has been found to vary from 0.4 to 1.0 [110]. From the intercept and slope, we obtain [r ] and kH. These values... 

Freed KF, Edwards SF (1975) Huggins coefficient for the viscosity of polymer solutions. J Chem Phys 62(10) 4032-4035... 

Table 1.4 Representative Mark-Houwink and Huggins coefficients of linear polymers...

Determination of the intrinsic viscosity for three different polybutadiene samples in tetrahydrofuran at 25°C. Each sample exhibits linear Huggins (filled symbols) and Kraemer (open symbols) plots that extrapolate to the intrinsic viscosity at zero concentration. All three polymers have Huggins coefficients of 0.37. 

The relationship between observed viscosity and intrinsic viscosity depends on the volume occupied by the polymer chains (dependent on the first power of their concentration) and the interactions between polymer chains (in the dilute and semi-dilute regions, dependent on the second power of their concentration). The resulting equation, eqn. (4.17), is known as the Huggins equation, with kii being the (dimensionless) Huggins coefficient, which measures chain-chain interaction ... 

Viscometry measurements were also conducted. The Huggins coefficients increase with increasing molecular weight for the amine-capped polymers. This behavior is consisted with a star-like structure. For the zwitterionic samples constant kn values, around 1.1 were obtained, meaning that rather compact structures exist in solution. 

The Hory-Huggins coefficient x plays an important role. If this coefficient is above a critical value, then phase separation into a polymer-rich phase and polymer-lean phase takes place. Since the polymer-solvent interaction is adverse, decreased temperature increases the importance of this interaction energy as the random thermal motion is decreased, and the temperature-concentration phase... 

The Huggins coefficient is constant for a given polymer-solvent system. However, the slope of the curves in Fig. 4.4 also depends on the intrinsic viscosity squared according to Eq. (4.9). Whereas for polymer samples with low molar masses and low intrinsic viscosities the curves in Fig. 4.4 almost seem to be inde-... 

In commonly occurring polymer solutions, the Huggins coefficient takes the value in the range 0.3-0.7 (see Figure 2.11). 

The Flory-Huggins solute-polymer interaction parameter may be also calculated from activity coefficients [16,39]. In the case of pure solvents the equation is ... 

Here k2 is the Huggins coefficient, which characterizes interactions between pairs of polymer chains. Matsuoka and Cowman propose k2 = (ki) /2l, ks — (k ) /3l, and so forth, so that the, n > 2, are coefficients in a power series for exp(kic[ri]). The Matsuoka-Cowman equation has been tested successfully for a variety of systems including modified polysaccharides(9). 

The Huggins coefficient, k, is observed to lie in the range 0-1. On the experimental side, Staudinger s own data refuted his Law. Flory and Mark also collected extensive data of intrinsic viscosity as a function of molecular weight. The observed exponent for random coil polymers in good solvents was in the range 0.6-0.8. There was still more to be done on this problem, but Alfrey summarized it brilliantly. 

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