This National Science Foundation (NSF) award under the Mathematical and Physical Sciences (CFDA 47.049) program is providing $680,000 to the University of Delaware and Oklahoma State University to develop new computational tools and methods for "soft sensing" in chemical industry applications. The project aims to apply data science techniques to infer key process indicators and critical process parameters when these attributes cannot be directly measured by physical sensors. The team is developing excitation-emission matrix fluorescence as an online/inline soft sensor for monitoring virus-like particle production processes, as well as improved hyperspectral imaging methods to detect polymer contaminants and immobilized biocatalytic enzymes. The work involves industry collaborations with Merck and Arkema to address challenges in biopharmaceutical manufacturing and polymer production. The award supports graduate and undergraduate student training in chemical data science and machine learning.
Generated 2/25/25, 5:33 AM