(414e) Colloidal Dispersion Stability of CuPc Aqueous Dispersions: Effects of Electrostatic and Other Forces | AIChE

(414e) Colloidal Dispersion Stability of CuPc Aqueous Dispersions: Effects of Electrostatic and Other Forces

Authors 

Dong, J. - Presenter, Pursue University
Corti, D. S. - Presenter, Purdue University
Hanson, E. - Presenter, Hewlett-Packard Laboratories, Hewlett-Packard Co.


Dispersions of copper phthalocyanine (CuPc) pigments are used as major colorants of commercial printing inks. The CuPc particles are crystalline, rod-like or cube-like, with sizes in the range from 50 to 100 nm. Their colloidal stability is essential for their shelf life and for their behavior in various printing processes. The particles are functionalized with sulfonate groups, and they are negatively charged.

To test the role of electrostatic forces in their stability, a series of dynamic measurements of dispersed particle sizes was done with dynamic light scattering (DLS) and spectroturbidimetry (ST) at various concentrations of NaNO3 and CaCl2 at 25 °C. The effects of counterion valence and concentration are significant, indicating strong electrostatic repulsions.

The results were used to determine the initial stability ratio W (the inverse of which is a measure of the probability that a collision will lead to coagulation). The DLVO ( Derjaguin-Landau-Verwey-Overbeek) theory was applied to make predictions of W for a simple model of monodisperse spheres in dilute dispersion. The Hamaker constant was calculated with a novel combination of an ab initio and an empirical methodology. The DLVO theory was used with two new models for spheres and cubes to predict the potential energy barrier Φmax, which is directly related to W. Electrostatic forces are inferred to play major roles in stabilizing the dispersions. Nonetheless, as the interparticle distance at Φmax becomes smaller than about 2 nm, the DLVO theory predictions for spheres are inaccurate, and inadequate for predicting W. Hence, other forces (e.g. hydration or other) may play important roles, and increase the values W compared to the DLVO-based predictions.