Date of Thesis
This paper details a new technique to measure the mechanical properties of ETTMP PEGDA hydrogels using Hertz Contact Theory and simultaneously analyze both the model drug release and gel erosion in situ. This method involves curing a drug loaded hydrogel in a standard cuvette and placing a glass bead and phosphate buffer solution (PBS). Over time, the cross-linked network of the hydrogel breaks down, and, as a result, the ball sinks into the hydrogel. This method provides a macroscopic and inexpensive way to continuously and passively measure properties of the hydrogel as the hydrogel degrades. By plotting both the hydrogel erosion and model drug release of the hydrogel, the full dynamic release and degradation is simultaneously evaluated over a period of time. A machine learning algorithm is implemented to predict the behavior of the hydrogel under different experimental conditions. Data from the experiments trains a machine learning model and creates an optimized decision tree which uses mean square error analysis to predict the appropriate polymer weight percent of the hydrogel vessel based on the properties of the drug enclosed and desired degradation time.
hydrogel degradation, mechanical properties, Hertz Contact Theory, machine learning, drug release
Bachelor of Science in Chemical Engineering
Minor, Emphasis, or Concentration
Rosh-Gorsky, Avery, "Determination of Hydrogel Degradation by Passive Mechanical Testing" (2021). Honors Theses. 585.
Available for download on Tuesday, May 24, 2022