Direct electrochemical cortisol detection via transition-resolved interrogation at a defect-engineered graphene interface
Year: 2026
Type: preprint
Abstract: Continuous tracking of cortisol is central to understanding human stress physiology, yet direct electrochemical detection without biological receptors remains challenging despite its promise for stable and dynamic sensing. Electrochemical reduction of cortisol typically occurs at highly negative potentials, where parasitic interfacial currents, hydrogen evolution, and substantial capacitive background overlap with the cortisol reduction signal, preventing accurate quantification. We overcome this barrier through an integrated material-measurement strategy combining a defect-engineered graphene interface with a transition-resolved interrogation (TRI) measurement strategy. First, we engineered polybenzimidazole-derived laser-induced graphene containing nitrogen-rich defects while suppressing oxygen-derived functionalities which reduced parasitic background currents within the same cathodic potential regime. Next, we designed TRI to leverage differences in the time-dependent evolution of overlapping cathodic processes to isolate a localized cortisol-associated electrochemical reduction transition. Derivative-domain projection coupled with background estimation enables its reliable quantification. This integrated sensing architecture enables sensitive, selective, and dynamic cortisol detection in both artificial and biological interstitial fluids at low nanomolar concentrations. The response remains reproducible across physiologically relevant variations in pH, ionic strength, temperature, and repeated cycling. Together, these capabilities provide a basis for continuous electrochemical cortisol monitoring for future study of stress physiology.
Authors: Alam Mahmud, Chuanzhen Zhao, Chibuike Uwakwe, Kuang-Jung Hsu, Il Rok Choi, Tianyang Chen, Brian C. DeFelice, Ira J. Gray, Jihyun (Luna) Hwang, Dan Ilyn, Thomas W. Redvanly, Laura Rijns, Shiyuan Wei, Ines Weber, Diego Uruchurtu Patino, Yangju Lin, Weilai Yu, Hao Lyu, Yuelang Chen, Chengyi Xu, Baiyu Shi, Andrea Sedano, Jeffrey Heo, Joseph M. DeSimone, Zhenan Bao
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
Funders: National Science Foundation, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Nederlandse Organisatie voor Wetenschappelijk Onderzoek, National Institutes of Health, National Cancer Institute, National Institute of General Medical Sciences, Division of Electrical, Communications and Cyber Systems, Stanford Cancer Institute
Awards: NNCI: nano@stanford, Conductive, hybrid hydrogels with cell type specificity for precision electronic medicine, G4089419421, G5442025106, Wireless Neurotransmitter Monitoring in vivo with Nanomaterial-enhanced Electrochemical Sensors, G8065195062, Mechanistic study on single Fe atom deposited single-layer graphene for ultrasensitive neurotransmitter sensing, G9000213186, Medical Scientist Training Program
OpenAlex ID: W7213410862
