AI-Driven Modeling and Prediction of Rheological Behavior of Complex Suspensions

This project aims to develop artificial intelligence (AI) models to accurately predict the rheological properties of complex suspensions based on compositional parameters. Using experimental data previously reported in the literature with machine learning techniques, the project will identify key features influencing viscosity, yield stress, and shear thinning behavior. The ultimate goal is to enable rapid, data-driven formulation and process optimization, reducing reliance on time-consuming experiments.