Machine learning reveals new candidate materials for biocompatible electronics

Machine learning tools developed by Andrew Ferguson, Associate Professor of Molecular Engineering at the Pritzker School of Molecular Engineering, and his collaborators are able to screen self-assembling peptides to find the best candidates for electronic, biocompatible materials.