Direct analysis in real time mass spectrometry (DART-MS) of ionic liquids.

Direct analysis in real time mass spectrometry (DART-MS) was used to analyze ionic liquids (ILs) containing either imidazolium or phosphonium cations combined with different types of inorganic and organic anions. Ionic liquids were directly inserted into the ionization source using a glass probe without dissolution into organic solvents. Mass spectra of the ILs were collected in both positive and negative mode with a linear ion-trap instrument. The intact cation of the compound was typically the dominant peak in positive mass spectra and cluster ion formation was present. Some individual anions were not readily observed in the negative mass spectra (based on the type of anion); however, the mass difference of adjacent cluster ions equal the mass of a complete IL and the anion mass could be verified by subtracting the known cation mass. The degree and intensity of the cluster ion formations was found to be dependent on the nature of the specific ILs as well as the DART temperature gas stream.

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.