We are developing a data-driven approach to biosensor design by combining electrochemical studies of single-chiral carbon nanotubes with AI-assisted modelling of analyte–surface interactions. Moving beyond trial-and-error, our goal is to make sensor development more efficient and reliable. As a proof of concept, we will demonstrate simultaneous detection of dopamine and serotonin in a biological sample using a tailored carbon nanotube sensor array.

2026

2027