Date of Award
May 2024
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Mechanical Engineering
First Advisor
Hallie Chelmo
Abstract
The effects atmospheric aerosols have on climate are not fully understood due to the limited knowledge of the interaction between aerosols and clouds. This interaction, known as the indirect effect of aerosols, is an area of interest within the field of atmospheric science. The presence of surfactants in the atmosphere due to natural and anthropogenic sources is known to negatively affect cloud formation, and is a contributor to the indirect effect. Quantifying how surfactants affect atmospheric aerosols will improve the understanding of the indirect effect. This work explores a statistically mechanically derived surface tension model for surfactant aqueous solutions, which applies adsorption isotherms to solution interfaces and considers surface-bulk partitioning behavior of individual solutes and solute groups, or mixtures. This behavior is complex, and there is a lack of consistent predictions of mixture surface tensions. Prior studies , such as the one performed by Bhuiyan,14 showed success in modeling surfactant mixture data using the single parameter, as well as their own reduction to a zero parameter model. The purpose of this work is to validate the single and new zero parameter model by examining bulk, binary aqueous solution data, then test this approach to picoliter volume droplets that have micrometer sizes in diameters. It was determined that the single and zero parameter model accurately predict surface tension values for bulk solution data based on the returned RMSE values. Conversely, the model did not predict accurate surface tension values for droplet data when compared to the bulk results. However, the new approach to create the zero parameter model by relating r and the surface tension at the CMC proved to be effective. The RMSE values between the single and zero parameter results were almost identical. Future work will be needed to further analyze the models on additional droplet datasets, as well as to create a more general relationship between r and the surface tension at CMC.
Recommended Citation
Mohr, Douglas, "A Statistical Model For The Surface Tension Of Microdroplet Surfactants And Multicomponent Mixtures" (2024). Theses and Dissertations. 6383.
https://commons.und.edu/theses/6383