Behavior of oil droplets on an electrified solid metal surface immersed in ionic surfactant solutions.

The present study investigates the change in the shape of oil droplets immersed in an ionic surfactant solution when the droplets are in contact with metal surfaces to which an electrical potential is applied. The three-phase system of aqueous solution-oil-steel was subjected to low-voltage electric potentials, which resulted in sometimes dramatic changes in droplet shape and wetting. This electric potential was applied to the conductive steel surface directly, and the counter electrode was immersed in the solution. Changes in both the shape and wetting extent of hexadecane and phenylmethyl polysiloxane were observed for voltages between +/-3.0 V in both sodium dodecyl sulfate and cetyl trimethylammonium bromide solutions. The droplets' behavior was opposite to what would be expected for traditional electrowetting. In one instance, hexadecane droplets in sodium dodecyl sulfate solutions with a voltage of -3.0 V, a rapid and repeating droplet elongation and detachment was observed. Additionally, the impact of the observed phenomena on electrowetting enhanced ultrasonication is presented to demonstrate the potential improvements in industrial ultrasonic cleaning processes. The observations lead to the possibility of employing simple electrowetting techniques in the removal of oil from metal surfaces in a manner that could greatly improve the environmental and economic performance of aqueous cleaning techniques.

Thermodynamic method for prediction of surfactant-modified oil droplet contact angle.

A model applying surfactant self-assembly theory and classical thermodynamics has been developed to aid in the prediction of solid surface cleaning by aqueous surfactant solutions. Information gained from a combination of surfactant self-assembly behavior and cleaning system parameters, such as oil species, surfactant type, temperature, alkalinity, and solid surface type has been shown to provide insight into surface cleaning. The model combines minimization of free energy, pertinent component distribution mechanisms, and surfactant self-assembly processes to provide a methodology for the predicting of oil droplet contact angles. Such predictive capabilities will allow for the development of beneficial environmental and economic changes to industrial and commercial surface cleaning and degreasing processes. Results from the model will be compared to experimental data to verify the capability of the theory to account for the effect of solutions parameters on oil droplet behavior. The model, while approximate in nature, has shown a remarkable quantitative predictive ability.