Presented by: Adam Gormley, Ph.D., Rutgers University, and Eric Seymour, Wyatt Technology
Presented Live: March 24, 2022
Machine learning and AI models are positioned to revolutionize materials chemistry by deconstructing complex structure-function relationships. However, large amounts of data are required to sufficiently train these models. In this webinar, we will show how data from high-throughput dynamic light scattering (HT-DLS) instruments utilizing microwell plates can inform these complex models. In an example, we will show how these models can be used to design complex synthetic copolymers.