CAREER: Tunable Graphene Microdevices for Multiplexed Detection of Biomolecules Beyond Diffusion Limit

Existing and emerging electrochemical biosensors can achieve high sensitivity, specificity, and stability in detecting biochemical molecules. However, label-free and tunable sensors for detecting multiple biomolecules (multiplexed detection) with high sensitivity and short measurement time are still beyond maturity. The goal of this program is to lay the foundations for engineering novel graphene-based biosensors to address these needs with biogenic amine neurotransmitters as testbed. The research component of this CAREER program will significantly advance the field of electrochemical sensing by 1) enhancing our understanding of fundamental questions involving convergence of material-device-readout knobs in design of electrochemical sensors, revealing the effect of interface engineering and electrical gating on tuning sensor response, and elucidating the impact of multimodal sensing and data fusion on enhancing accuracy, specificity, and reliability, and 2) utilizing this knowledge in innovating a new class of reliable, multiplexed, and tunable devices. The research outcomes will provide a foundation for educational activities focused on training graduate and undergraduate students. Multiple initiatives are integrated to increase public engagement in biosensing science and technology, including creating new laboratory modules for a biosensor-themed course, a summer workshop for teachers, and a summer camp for pre-college students. This program aims at creating tunable and multiplexed electrochemical biosensors with high sensitivity, specificity and rapid response by developing new data-fused hybrid droplet-graphene microdevices. This CAREER program integrates both experimental and modeling investigations which include 1) elucidating the correlation between plasma-assisted functionalization of graphene and analyte-device interface engineering to enhance sensitivity and tune specificity of graphene microdevice array; 2) developing a learning-based multimodal electrochemical system for reliable classification of bioanalytes and multiplexing; 3) understanding the fundamental limits of sensitivity versus response time in a time-evolving system; 4) elucidating the fundamental mechanisms for electrical gating as an in-situ knob to tune the reaction kinetics at the graphene-analyte interface and hence the sensor response; and 5) demonstrating the application of this system with a well-studied drug screening neurosecretion cell model. This project is anticipated to have a long-term impact on biosensor engineering by elucidating how interface and device engineering influence detection limit and response time in time-evolving electrochemical systems and how convergence with multimodal readout can significantly enhance accuracy, specificity, and reliability of label-free diagnostics. In addition, the outcomes will advance utilization of the growing field of 2D material functionalization and devices in diagnostics, bioelectronics, and life science. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.