Nanoscale Advances Project
Innovative Machine-Learning Technique Enables Low-Cost Detection of Neurochemicals
A collaborative effort between Chemical Engineering and Health Sciences departments has resulted in a new sensing method capable of rapidly classifying monoamine neurotransmitters using plasmonic UV autofluorescence and ML. Published in Nanoscale Advances journal, this research points toward accessible, scalable tools for monitoring chemical markers linked to stress, mood, and mental health.
Read the highlighted news from University Research Impact at the link below:
U Students Lead Breakthrough in Low-Cost Neurochemical Detection


