The Wisconsin MRSEC has developed machine learning techniques that enable the design of new toxin sensors using liquid crystal droplets that respond to the presence of different bacterial toxins and at extremely low concentrations by changing shape and appearance. Machine learning enables computers to automatically analyze the droplet responses to measure toxin concentration and type automatically at high accuracy. More generally, these results demonstrate that the machine learning approach can quickly extract valuable information from complex datasets.
Month: June 2020
Newly Awarded Superseed and Seed Projects Will Forge Research Paths for MRSEC
Two Superseed projects and one Seed project have been awarded funding to pursue research as part of the Wisconsin Materials Research Science and Education Center (MRSEC). The collaborative Superseed and Seed projects will enhance the ongoing materials research of the Center and support the exploration of transformative new directions.